Twenties deliverable 10.3 Providing flexibility with a virtual power plant

Providing flexibility with a virtual power plant
Virtual power plant demonstration showing that ancillary services can be provided through
distributed generation and flexible load units at lower voltage levels on a large scale to
balance the intermittent renewable energy and stabilise the grid
Final Demo Report
Deliverable no: 10.3
EC-GA nº 249812

www.twenties-project.eu Page 2 of 275
Document info sheet
Document Name: Final Demo Report
Responsible Partner: DONG Energy
WP: WP #10
Task: Tasks 10.1-10.5
Deliverable no.: 10.3
Revision: 01
Revision Date: 18.01.2013
Diffusion list
All partners.
Approvals
Final draft version to be submitted to the Technical Committee members.
Name Company
Author/s Jan Hansen (Main author) DONG Energy
Anders Birke DONG Energy
Simon Børresen DONG Energy
Peter Vinter DONG Energy
Andreas Bjerre DONG Energy
Thomas Kudela DONG Energy
Kim Ilskær DONG Energy
Pia Apel Hansen DONG Energy
Nicolai Depenau Rasmussen DONG Energy
Ivan Kristian Pedersen DONG Energy
Jonathan Dybkjær DONG Energy
Kristian Edlund DONG Energy
Michael Ølund DONG Energy
Mads Jacobsen DONG Energy
Morten Stryg DONG Energy
Task
Leader
Anders Birke
(andbi@dongenergy.dk)
DONG Energy

Document history
Revision Date Main modification Author
01 18.01.2013 First internal release Jan Hansen
02 05.03.2013 Send to approval Jan Hansen
03 11.07.2013 Review comments from TC handled Jan Hansen
04 09.08.2013 Additional demo reports added to Appendix Jan Hansen
05 24.09.2013 Last review comments included Anders Birke

Executive Summary
The EU has set ambitious targets for integrating renewable energy in the future European energy
system, which is clearly stated in the EU 20-20-20 strategy. The additional renewable energy will
primarily come from wind and solar, which incurs the challenge of variability in the energy system. As
the key obligation of the energy system will still be to secure a stable power supply when the
consumers need it.
Introduction of large amounts of intermittent renewable power production will create challenges to the
power system like: How to produce power when there is no wind, how to shift consumption to periods
with excess power on windy days, how to quickly compensate when wind power production fluctuate
very fast up or down and how to secure spinning reserves and reactive power in high wind situations
where there is no need for energy from the traditional power plants that supplies these services today.
To manage the challenges, new technologies, solutions, regulation, market designs and business
models will have to be introduced in the European energy system. The virtual power plant technology
is one of the most promising new technologies to help solve these challenges. Twenties demo 2 aims
to show the full potential of the virtual power plant technology and show how it can be part of the
solution for a future stable low carbon energy system.
Twenties Demo 2 has demonstrated how virtual power plant technology can help integrate an
increased share of intermittent renewable energy in the European power system. The demonstration
has been done by developing an advanced VPP that operates in Denmark on commercially terms and
are active in the ancillary services and power markets on a daily basis.
The main conclusions from this deliverable are:
 It is technically possible and economical attractive to build virtual power plants that controls a
wide variety of producing and consuming distributed energy resources.
 Virtual power plants can deliver a wide range of services, that will all be needed from new
sources when the future low carbon power system has to be balanced.
 Virtual power plants can transform the flexibility in a portfolio of units with stochastic behaviour
into reliable services while still fulfilling the primary purpose of the industrial units.
 It is a challenging task to mobilize industrial units to participate in virtual power plants. The unit
owner has to learn about economic potential in asset capabilities, be convinced Power Hub
will not influence his industrial output, and be given an attractive and simple economic offer.
 Barriers exist towards scaling up VPP technology in relation to regulation and market
structures. Transformation into a low carbon energy system requires changes in the regulatory
regime to make it work optimally.
To get a more detailed but still short description of the project and the results read the 7 page
conclusion in this report. Twenties demo 2 was made in a collaboration between DONG Energy,
Fraunhofer IWES, Red Eléctrica de España and Energinet.dk.

Table of Contents
1. INTRODUCTION......................................................................................................................6
1.1 The Nordic electricity market..................................................................................................6
1.2 Challenges in a power system based on wind power production ...........................................8
1.3 Description of a VPP..............................................................................................................9
1.4 Reading guide......................................................................................................................11
1.5 Glossary ..............................................................................................................................11
2. LARGE SCALE VPP ..............................................................................................................14
2.1 Purpose and scope..............................................................................................................14
2.2 Results ................................................................................................................................14
3. CORE COMPETENCIES OF A VPP ......................................................................................21
3.1 VPP platform with diversified offering...................................................................................21
3.2 VPP platform that maximises the value of the flexibility in the local units .............................44
3.3 VPP platform that creates attractive value propositions to all stakeholders..........................61
3.4 VPP platform with multiple local units mobilisation strategies tested....................................70
3.5 VPP platform that is portable, scalable and secure ..............................................................86
4. FEATURES FOR TODAY'S POWER SYSTEM....................................................................101
4.1 VPP platform able to integrate and control wind power ......................................................101
4.2 VPP platform showing how to use aggregators and integrators .........................................119
5. FEATURES FOR TOMORROW'S POWER SYSTEM ..........................................................132
5.1 VPP platform delivering reactive power control..................................................................132
5.2 VPP platform as an island solution delivering fast frequency demand response ................144
5.3 VPP platform that delivers micro grid balancing.................................................................162
6. CONCLUSION......................................................................................................................172
7. APPENDIX ...........................................................................................................................178
7.1 Appendix 1: Log for integration and control of WTGs to deliver ancillary services..............178
7.2 Appendix 2: Attachment to the demonstration of island solution delivering fast frequency
demand response.........................................................................................................................190
7.3 Appendix 3: Log for long-term demonstration of island solution delivering fast frequency
demand response.........................................................................................................................192
7.4 Appendix 4 – Investigation, purpose & results of raising customer awareness...................206
7.5 Appendix 5 – White label ...................................................................................................209
7.6 Appendix 6 – The process of reducing RTU costs .............................................................230
7.7 Appendix 7 – Investigation, purpose & results on flexibility forecast...................................234
7.8 Appendix 8 - Investigation, purpose & results on price forecast and stochastic optimisation
240
7.9 Appendix 9 – Coupled Units...............................................................................................268

1. INTRODUCTION
This section introduces the Nordic power system to the reader followed by a presentation of the
challenges that the power system faces today and which will become even more distinct in the near
future as more intermittent power production from wind turbines will be present in the power grid. A
solution to these challenges is to use virtual power plants (VPPs), which is introduced as a concept. A
reading guidance to this report is presented at the end of the introduction.
1.1 The Nordic electricity market
This section aims at giving a brief introduction to the Nordic electricity markets by introducing the
players in the markets and describing the wholesale products traded in these markets.
It is important to mention that the following describes the status quo. Legislation concerning
liberalisation of the European electricity market and facilitation of market integration are likely to
change the requirements in future.
1.1.1 Roles in the electricity sector
Generally, the value chain can be said to be divided into power generation, power transport
(transmission and distribution) and power sales to end customers. The organisation of each activity
depends on whether or not undertaking that specific function can lead to a monopoly status in the
market. See Figure 1. Principally, power generation can be done by any supplier and the activity is
not exclusive, hence this activity is commercially based. On the other hand, owning the transportation
grid results in a monopoly status since – if not regulated – the owner would have the possibilities to
abuse the market power of being able to control whose electricity the grid should transport. When it
comes to selling power to end customers, again this activity could be exercised by any sales company
without excluding other players, and therefore sales activities are commercially based.
Figure 1: The value chain can be said to be divided into power generation, power transport (transmission and
distribution) and power sales to end customers.
The organisation of each activity in Figure 1, depends on whether or not undertaking that specific
function can lead to a monopoly status in the market.

In the Nordic countries, the electricity grid is operated by non-commercial monopolies. For each local
area, there is a local grid operator, a distribution system operator (DSO), who handles the local low-
voltage grid. The high-voltage grid is operated by the transmission system operator (TSO). The TSO
must be a non-commercial organisation, neutral and independent of commercial players.
In addition to owning and operating the high-voltage grid, the TSO is responsible for the security of
supply and thus rules and controls the electricity system in their country. By assuming this role, the
TSO is system responsible. In other words, the TSO is responsible for the commodity (electricity)
arriving at the end users’ sites.
1.1.2 Wholesale electricity markets
The Danish electricity market is part of a common Nordic market. Energy is traded in a number of
different markets each defined by the time from the market’s closure to the hour of operation.
Contracts traded on forward markets are aggregated and optimised together with the positions on
day-ahead and intraday markets resulting in daily schedules. These daily schedules are used by the
Danish TSO Energinet.dk to calculate imbalances from the transmission grid in real time and
financially settle with the parties responsible for them, according to the specifications in the balancing
arrangement.
The first settlement between energy supply and demand in a given hour of operation happens in the
day-ahead baseload market, which in the Nordic countries is called Elspot. When the Elspot market
closes, a price where the expected production meets the expected consumption is found. However,
as the hour of operation approaches, this expected balance might need adjustment as the
expectations regarding eg wind power production or consumption change. Therefore, a new
settlement between production and consumption is found, first on the Elbas intraday market and then
on the regulating power intrahour market.
Within the hour of operation, minor adjustments to ensure a continuous balance between production
and consumption might be needed. The services that balance out minor disruptions within the hour
are called ancillary services. Products in the ancillary service markets are sold to the respective TSOs
and are typically tendered to uphold power reserves (MW) to secure the balance of consumption and
production.
The suppliers of ancillary services receive a fixed reservation payment for upholding these reserves.
For some ancillary services such as Secondary and Tertiary Reserve, the supplier gets a payment per
MW for being available in these markets. If the capacity is activated it is settled at a payment per
activated MWh. The main difference between the ancillary services is the requirement for response
time after activation, which ranges from a few seconds for Primary Reserves up till 15 minutes for
Tertiary Reserves used for regulating power.
The market division is illustrated in Figure 2.

Figure 2: Forward markets and Ancillary Services.
The requirements differ depending on the ancillary service in question. Further, there are also
variations between DK1 and DK2 because the two areas are not part of the same synchronised area.
All reserves include up as well as down-regulation reserves. See Figure 3.
Figure 3: Market division in Denmark
The technical requirements and framework conditions for each product can be found in the relevant
sections throughout the document.
1.2 Challenges in a power system based on wind power production
The EU has set ambitious targets on introducing renewable energy production technologies in its 20-
20-20 plan. The new, additional renewable power sources are likely to be wind and solar-based
production. Other renewable technologies are either too expensive or difficult to extend beyond their
existing capacity.

The main problem with RESs such as wind and solar energy is that they are dependent on very
variable and intermittent sources of energy. Yet the power system is still obliged to deliver electricity
when the consumers need it.
As more power production will originate from RESs, the more the traditional - and reliable - power
plants (CHPs using coal, oil, gas, etc.) will be surplus and unnecessary. A consequence of this is that
the baseload in the power grid will be dependent on intermittent power production, meaning that new
solutions to leverage this challenge must be developed. The intermittency and volatility of wind and
solar requires flexibility from other stakeholders in the power system. These stakeholders also include
the large amounts of small units, including household installations. And if these units can be
aggregated and made flexible, they might help the integration of intermittent RES. One technological
solution that comply with this is to develop a virtual power plant to intelligently optimise the power
consumption and production to stabilise the grid.
1.3 Description of a VPP
Power Hub is a VPP; a system that controls the behaviour of a large number of local units (LUs). The
LUs are both power-consuming and power-producing units. The producing units could eg be small
hydro plants, emergency gensets or wind turbines. The consuming units could eg be cold storage
facilities, greenhouses or drainage pumps. In between production and consumption units is the
storage units, eg electrical vehicles that can both consume (charge) and produce (decharge) power.
The important aspects of the units are that they have some flexibility in how they consume or produce
energy. Power Hub has to control the units in such a way that they support the energy system when
power consumption and production are not in balance. See Figure 4.
Figure 4: Power Hub is a VPP capable of integrating different technologies (production, consumption and storage
units) and to utilise the flexibility by optimising and selling it across different markets.
A VPP can deliver services of which the future low carbon energy system will be in short supply. It

is capable of delivering ancillary services like regulation power, do load shifting
from eg day to night when the power consumption is lower, and additional services like reactive power
control, spinning reserves and load shedding.
The conceptual VPP solution consists of:
• An IT system that knows how to operate the LUs
• Interfaces to the TSO and the power markets
• A solution for how to communicate with the LUs and take control of the LUs
• A solution for how to measure the provided services
• Getting the VPP approved as a supplier to the markets.
Attraction and installation of LUs consist of:
• A strategy for which LUs to attract
• A strategy for how to attract the LUs (sales meetings, payment schemes, other)
• The practical implementation of communication with and control of the LUs
• Establishing metering of the LUs.
Running the daily operation of the VPP:
• Forecasting the flexibility of each LU
• Forecasting the need for flexibility in the different markets
• Bidding into the regulating power markets and the day-ahead and intraday markets
• Controlling the LUs to create the services that were sold to the markets
• Measuring the services created
• Settling with the markets
• Settling with the LU owners.

1.4 Reading guide
The report is built around eleven distinct demonstrations that can be read individually and
independent of each other. They are divided into four sections: 1) Large scale VPP, 2) Core
competencies of a VPP, 3) Features for today’s power system and 4) Features for tomorrow’s power
system (see
Figure 5). In the Appendix six additional demonstrations can be found.
Figure 5: The report is built around eleven distinct demonstrations that can be read individually and independently.
Providing flexibility
with a virtual power
plant
Large scale VPP
Core competencies
of a VPP
Features for today's
power system
Features for
tomorrow's power
system
Appendix
VPP platform…
• 2)…with diversified offerings
• 3)…that maximises the value of the flexibility in the local units
• 4)…that creates attractive value propositions to all stakeholders
• 5)…with multiple local unit mobilisation strategies tested
• 6)…that is portable, scalable and secure
VPP platform…
• 7)…able to integrate and control wind power
• 8)…showing how to use aggregators and integrators
VPP platform…
• 9)…delivering reactive power control
• 10)…as an island solution delivering inertia
• 11)…that delivers micro grid balancing
• 1) Large scale VPP
• Investigation, purpose & results of raising customer
awareness
• White Label
• The process of reducing RTU costs
Investigation, purpose & results on flexibility forecast
Investigation, purpose & results on price forecast and
stochastic optimisation
• Coupled units

1.5 Glossary
Term Abbreviation Definition
Ability forecast
A forecast in 5 minute resolution stating LU’s maximum and
minimum power levels. Power levels must be respected by Power
Hub.
Aggregator
An entity that collects a cluster of units which, seen from the
outside, appears as one unit.
Balance
Responsible Party
BRP
A Balance Responsible Party is an organisation that plans and
achieves an hourly balance between the supply and consumption of
electricity.
Binary Unit
A unit that may either be switched on (and run at nominal capacity)
or switched off. Cannot be regulated by an external setpoint. Is
sometimes referred to as On/Off.
Capacity
An option that can be traded on a market to change
production/consumption if needed.
Cluster
A collection of LUs that provides flexibility to a higher level. It does
not act on a market on its own.
Combined Heat and
Power unit
CHP
Generation unit capable of simultaneously producing electricity and
useful heat.
Decentralised
Control System
DCS
The system that controls and monitors the LUs. The LU owner
normally has a DCS that ensures the unit fulfils its primary purpose.
Desciption of Work DoW The description of the work in the Twenties project.
Distributed Energy
Ressource
DER
Distributed generators (that are able to deliver electrical power) or
distributed bidirectional storage units (that are able to deliver
electrical power after storing it).
Distribution
Management
System
DMS
A real-time system for distribution grid monitoring, network
restoration, congestion management, energy loss reduction and
voltage control.
Flexibility
An LU’s potential for moving power or energy
consumption/production in time.
Integrator
An entity that collects a cluster of units but exposes them as
individual units to the outside world.
Integrator
An entity that collects a cluster of units but exposes them as
individual units to the outside world.
Local Unit LU
General term for the units controlled by the Virtual Power Plant. The
units can be both power consuming or producing units, that has the
possibility of shifting energy in time.
Local Unit Owner
The entity that carries the financial consequences of the LU’s
actions and has the influence to make manual decisions on behalf
of the LU.
Market A place to trade energy or ancillary services.
Market integration
The possibility for a VPP or LU to perform trades directly on the
market.

OLE for Process
Control
OPC
OLE for Process Control is a standard which specifies the
communication of real-time plant data between control devices from
different manufacturers.
Photo Voltaic PV A production unit based on solar energy.
Power Hub PH Instance of the VPP concept, implemented by DONG Energy.
Remote Terminal
Unit
RTU
Electronic device controlled by a microcontroller that interfaces with
physical objects to a Distributed Control System or Supervisory
Control And Data Acquisition (SCADA) system by transmitting
telemetry data to the system and receiving telecontrol orders from
the system.
Renewable Energy
Sources
RES
Energy production that is based on natural resources (sunlight,
wind,…).
Site
A site is a virtual entity that aggregates local units contractually
connected to one power supplier and thus also under joint balance
responsibility. Power Hub consists of several sites that are based on
the same software, but functionally and aggregation-wise
independent. It is not allowed to aggregate production and
consumption under joint balance responsibility in Denmark.
Supervisory Control
and Data Acquisition
system
SCADA
A power grid tool which serves two purposes. One is data
acquisition, where the SCADA system is used to collect, store and
analyse numerous grid information, the other is to disseminate
control commands among controllable grid components using novel
communication infrastructures.
Transmission
System Operator
TSO
A Transmission System Operator is the operator of the electrical
transportation grid.
Virtual Power Plant VPP
A collection of DERs that act as one unit seen from a market
perspective.
Virtual Private
Network
VPN
Virtual Private Network is a technology to securely connect to
remote networks.
X509
X509 is a security certificate standard for use in a public key
infrastructure (PKI).

2. LARGE SCALE VPP
2.1 Purpose and scope
The purpose of this demonstration is to document the number and different types of local units (LU)
integrated to the Power Hub, and the services delivered from them during the project period. And to
hold this up against the goals for the Power Hub (PH) project. These are the KPIs for the project, as
they were set in the Description of Work (DoW) document.
This demonstration will present only the results of the KPIs. Descriptions of what has been done, and
what solutions have been developed to achieve these results are found in detail in other
demonstrations. The statement period is up to and including November 2012.
2.2 Results
Table 1: The KPIs for Power Hub divided into subgroups.
Name of KPI Sub group KPI in DoW Results by the end of
November 2012
Units integrated B2B 100 42
B2C 2,000 5
Cluster 300 15
Technologies (LU types) 8 15
Available capacity Spot market 100MW 38.3MW
Ancillary services 50MW 30.7MW
Energy realized Spot market 10,000MWh 25,570MWh
Ancillary services 2,000MW 9,746MW
Available reactive capacity 10MVAr 0.7MVAr
The figures for the KPIs is shown in Table 1 as they were specified in the Description of Work
document, and finally the results by the end of November 2012.
2.2.1 Defining the KPIs
2.2.1.1 Units integrated
It is the ownership of the control of the unit that determines if the unit is a business to business (B2B)
unit or a business to custumer (B2C) unit. Examples: A normal wind turbine is a B2B unit, because it
is seen as a professional investment, while a micro wind turbine or a small solar cell installation in a
household is a B2C unit. An electric vehicle would be a B2C unit even though it can be owned by a
company. Cluster units are units controlled via an aggregator or an integrator. A unit is only counted
as either B2B or B2C, but units in a cluster are also counted as B2B or B2C units. So the total sum of
units integrated is the figure for B2B added to the figure for B2C.
The counting of LUs for the KPIs “units integrated B2B“, “units integrated B2C“ and “units integrated
Cluster“ in Table 1 is made up in equivalent units. The integration process for each LU is divided into
five phases: idea, analysis, maturation, execution and evaluation. Each time a phase is finished for a
LU, it is marked in the weekly status update. These markings are summed up for all units having
finished an arbitrary phase that week and divided by five to make it equivalent to whole finished units.
The number of equivalent units per week is shown in Figure 6 aggregated week by week. To

emphasize, one unit in Table 1 and Figure 6 might very well resemble the completion of one single
phase in five different local units.
Figure 6: Number of finished equivalent units aggregated week by week 2011 – 2012.
To see the details on the phases for the LUs in process by the end of November 2012, please refer to
2.2.2 Overview of units in integration process.
2.2.1.2 Technologies (LU types)
A production process that is conducted by the use of certain machinery or the machinery in itself is
defined as a “technology“ if it conforms to the list in Table 2 defined by Power Hub. All machinery is
either supplied with electrical power from or delivers electrical power to the public grid. The Power
Hub project has been engaged with units covering all technologies from the list, but a technology is
only counted into the KPI in Table 1 if the integration process concluded with full Power Hub control of
the unit, which means controllable by Power Hub in an intelligent manner.
Table 2: Overview of all technologies covering all units been worked with during the project period.
Technology Abbreviation Explanation
Battery BAT A device consisting of one or more electrochemical cell that converts
stored chemical energy into electrical energy
Cold Storage CST Plant or process utilising a refrigerating engine
Diesel Genset DGS Diesel engine with a power generator
Drain Pump Station DPS Water pumps to drain land below sea level
Drinking Water
Pump(s)
DWP Pumps used for the supply of drinking water
0
5
10
15
20
25
30
35
40
45
50
2011-1
2011-5
2011-9
2011-13
2011-17
2011-21
2011-25
2011-29
2011-33
2011-37
2011-41
2011-45
2011-49
2012-1
2012-5
2012-9
2012-13
2012-17
2012-21
2012-25
2012-29
2012-33
2012-37
2012-41
2012-45
2012-49
Number of LUs
Weeks
Number of local units integrated 2011-2012
Finished LUs

Feeder FED Medium voltage supply to a part of a distribution grid. For Power Hub it
is equivalent with the circuit breaker.
Fuel Cell(s) FUC A device that converts chemical energy from fuel into electricity through
a chemical reaction with oxygen or another oxidising agent
Gas Turbine
Generator
GTG Gas turbine with a power generator
Greenhouse
Growth Light
GGL Assembly of light sources used for growth light in a greenhouse
Heating Ventilation
Air Cooling
HAC Equipment for heating/cooling the air for building ventilation. The
interesting machinery will at most be the cooling compressor
Heat Pump HPP A device that transfers heat energy from a heat source to a heat sink by
use of the vapour compression cycle
Hydro Turbine
Generator
HTG Hydro turbine with a power generator
Metal Foundry FOU Broad concept covering all kinds of metal founding or metal surface
treatment
Photo Voltaic
Panel(-s)
PVP A packaged, connected assembly of photovoltaic (solar) cells
Waste-Water
Treatment
WWT The process of removing physical, chemical and biological
contaminants from waste water. The interesting machinery will at most
be the bioaeration blower
Wind Turbine
Generator
WTG Wind turbine with a power generator
2.2.1.3 Available capacity
The nominal (rated) power for all units fully controllable by Power Hub is counted into the KPI
“available capacity, spot market“. The counting is a mixture of nominal power from production units
and consumption units.
The flexible part of the power from the same units is counted into the KPI “available capacity, ancillary
services“ irrespective of which service the flexible power actually could be used for.
The nominal power and the flexible part of the power from the units not fully controllable by Power
Hub are not counted into the KPIs. Details can be found in 2.2.2 Overview of units in integration
process.
2.2.1.4 Energy realised
For a production unit, the power produced and delivered to the public grid must be measured
separately. For the consumption units integrated up to the end of November 2012, Power Hub has
measurements of the electrical power supplied to all individual units controlled by Power Hub. These
figures are summed up with the figures from production units and counted into the KPI “energy
realised, spot market“.
The flexible part of the power from all units, both production and consumption, which is applicable for
ancillary services is offered to the ancillary service market. All accepted offers are counted into the
KPI “energy realised, ancillary services“. Up to now, only flexible power from production units
applicable for primary control (PC) has been offered.

The energy realised on the spot market and the power sold to the ancillary market during the whole
project period aggregated per month and for all units as they have consecutively been commissioned
is shown in Figure 7.
Figure 7: Energy realised via Power Hub on the spot market and power sold to the ancillary market continuously
aggregated per month over the whole project period for all units.
2.2.1.5 Available reactive capacity
Since there is no market for reactive power in Denmark, the Power Hub project has integrated only
one unit for demonstrating the ability to handle the service.
2.2.2 Overview of units in integration process
Details for all the units in the integration process during the whole project period can be seen from
Table 3 for units in Denmark and Table 4 for units on the Faroe Islands. The Power Hub project has
been engaged with far more units than mentioned in the tables. Only units where the screening (=
idea phase) succeeded in the decision to continue the integration process for that unit are mentioned
in the tables. The names of the units, the technologies with the abbreviations from Table 2, the
nominal and the flexible power are shown in the tables. The expected services that may be delivered
from the units are also stated in the column “Service ability“ by the abbreviations further explained in
Table 5. The most likely service is the first one mentioned for each unit.
Not all units are fully integrated by the end of November 2012 as explained in paragraph 2.2.1.1 Units
integrated. Fully integrated is defined as “controllable by Power Hub in an intelligent manner“. It

means that the integration of the unit must at least have finished the “execution“ phase. The journey
for a unit from the very beginning of the integration process to fully controllable by Power Hub goes
through the phases: idea, analysis, maturation, execution and evaluation. In the last column
’Integration phase’ in Table 3 and Table 4 the latest finished phase for the unit is stated. It means that
the unit may actually be in the next phase, if the integration process is continued for that unit.
Table 3: Units in integration process in Denmark.
Unit name Technology Nominal
power
[MW]
Flexible
power
[MW]
Service
ability
Integration
phase
Audebo Pumpestation DPS 0,13200 0,13200 SO, TC Evaluation
Bring Frigo CST 0,40000 0,20000 PC, SO Idea
Claus Sørensen A/S, Engesvang CST 1,50000 1,50000 SO Idea
Damhusåen 1 WTG 0,22500 0,22500 SO Evaluation
Damhusåen 2 WTG 0,25000 0,22500 SO Evaluation
Dantherm 00 FUC 0,00092 0,00092 SO Execution
DONG Energy, GTF HAC 0,94500 0,94500 SO, TC (PC) Maturation
DONG Energy, GTF PVP 0,08900 0,08900 SO, TC (PC) Evaluation
DONG Energy, GTF WTG 0,00800 0,00800 SO, TC (PC) Evaluation
DONG Energy, GTF, G2 DGS 0,80000 0,80000 SO, TC Evaluation
DONG Energy, GTF, G3 DGS 0,80000 0,80000 SO, TC Evaluation
DONG, GTF, G2 DGS 0,70000[MVAr] 0,70000[MVAr] Q Evaluation
Easyfood CST 0,50000 0,50000 SO Idea
Frankerup 1 WTG 0,75000 0,75000 SO Evaluation
Frankerup 2 WTG 0,75000 0,75000 SO Evaluation
Fredericia Spildevand 1 WWT 0,48000 0,48000 PC, SO Maturation
Fredericia Spildevand 2 WWT 0,48000 0,48000 PC, SO Execution
Furesø Vandforsyning DWP 0,15000 0,10000 SO, TC Evaluation
Gudenaacentralen HTG 1,40000 0,50000 SO, PC Evaluation
Harteværket G1 HTG 0,35000 0,30000 SO, PC Evaluation
Harteværket G2 HTG 0,22000 0,19000 SO, PC Maturation
Harteværket G3 HTG 0,35000 0,30000 SO, PC Evaluation
Hedensted Renseanlæg WWT 0,11400 0,02000 PC, SO Maturation
Herning Varmforzinkning FOU 0,80000 0,50000 PC, SO Analysis
Hørsholm Skøjtehal HHP 0,20000 0,20000 PC, SO Analysis
Juelminde Renseanlæg WWT 0,11400 0,02000 PC, SO Maturation
Kr. Helsinge 1 WTG 0,75000 0,75000 SO, SO Evaluation
Kr. Helsinge 2 WTG 0,75000 0,75000 SO Evaluation
Kramnitze pumpestation 1 DPS 0,30000 0,30000 SO, TC Evaluation
Kramnitze pumpestation 2 DPS 0,30000 0,30000 SO, TC Evaluation
Legro Gartneri GGL 0,15000 0,15000 SO, TC Execution
Lille Linde 1 WTG 0,60000 0,60000 SO Evaluation
Lille Linde 2 WTG 0,60000 0,60000 SO Evaluation
Naturmælk CST 0,05000 0,05000 PC Execution
Novo Nordisk GTG 5,00000 1,00000 PC, SO Evaluation

RISØ DTU, FlexHouse HAC 0,02000 0,02000 SO, TC Evaluation
S&D / NORDEA DGS 2,70000 2,70000 SO, TC Maturation
Skærbækværket DGS 2,00000 2,00000 SO, TC Analysis
Træløse 1 WTG 0,66000 0,66000 SO Evaluation
Træløse 2 WTG 0,66000 0,66000 SO Evaluation
Vestas Battery Demo BAT 3,20000 1,60000 PC Evaluation
Vestas 1 WTG 3,00000 3,00000 PC Evaluation
Århus Vand WWT 0,15000 0,07500 SO (PC) Idea
Table 4: Units in integration process on the Faroe Islands.
Unit name Technology Nominal
power
[MW]
Flexible
power
[MW]
Service
ability
Integration
phase
Bergfrost CST 0,150 0,150 FFDR Evaluation
Fútaklettur HHP 0,035 0,035 FFDR Evaluation
Fútaklettur DGS 0,950 0,950 PC Analysis
Føroya Tele DGS 0,880 0,880 PC Analysis
Nordasta Horn FED 1,000 1,000 FFDR Evaluation
Pelagic CST 4,900 4,000 FFDR Execution
Sunnari Ringvegur FED 0,600 0,600 FFDR Evaluation
Table 5: Explanation of the possible services from the Power Hub units.
Service Abbreviation Explanation
Fast Frequency
Demand
Response
FFDR If the electricity systems stability is threatened due to a sudden loss in
production, this service can be activated with a response time of a few
seconds. It will be experienced as an increase of system inertia, similar to
’Virtual Inertia’ services from modern wind turbines and energy storage
systems. Power Hub sources FFDR from the shedding of individual
industrial loads
Primary Control PC Primary control maintains the balance between generation and demand in
the network. It is an automatic activated, decentralised function with a
response time of less than 30 seconds. Power Hub sources PC from
analogue controllable rapid units. It could also be delivered from binary
units and consumption units. These features are not yet fully developed
Secondary
Control
SC Secondary control maintains the balance between generation and demand
within each control area / block as well as the system frequency within the
synchronous area. It also releases the primary reserves. It is an automatic
centralised activated function with a response time up to typically 15
minutes after an incident. The feature is not yet developed by Power Hub
Tertiary Control TC Tertiary control is usually activated manually by the TSOs
in case of observed or expected sustained activation of secondary control.
It is primarily used to free up the automatic secondary reserves. It is a
manually centralised activated function with a response time of up to

typically 15 minutes. The feature is not yet developed by Power Hub
Spot
Optimization
SO Based on a price forecast and a unit flexibility, Power Hub can delay or
advance the power production or consumption from the unit (load shifting)
to a price optimal time
Reactive Power Q Supply or consumption of reactive power

3. CORE COMPETENCIES OF A VPP
This section covers the core competencies of a VPP, i.e. the minimum capabilities of a VPP. This is
demonstrated based on the core competencies of Power Hub.
 3.1 explains the different services offered by Power Hub.
 3.2 demonstrates how Power Hub maximises the value across different markets.
 3.3 demonstrates how Power Hub creates value to all its stakeholders.
 3.4 documents the learnings achieved in the testing of different mobilisation strategies.
 3.5 documents and demonstrates that Power Hub is based on a portable, scalable and secure
IT platform.
3.1 VPP platform with diversified offering
3.1.1 Purpose
The purpose of this demonstration is to show that Power Hub offers flexibility and delivers services
from its local units to all available power markets in Denmark such as Nord Pool Spot or the Danish
TSO, Energinet.dk’s provision of ancillary services.
In order to participate in the markets, technical requirements have to be met by the local units and
market interfaces have to be established. The flexibility of the local units can then be offered to the
markets according to their technical capabilities and generate monetary income. Local units can be
distributed generation or controllable load for demand response.
The relevant markets interfaces for this demonstration are the TSO-operated markets Primary,
Secondary and Tertiary Reserves, as well as the two complementary markets Elspot for day-ahead
trading and Elbas for intraday trading.
3.1.2 Scope
Energy is traded in a number of different markets each defined by the time from the market’s closure
to the hour of operation and its response time after activation as described in 1.1 The Nordic
electricity market. Within the scope of demonstrating Power Hub’s diversified offerings, we show
market participation in following markets of the Danish electricity market:
 Primary Reserve
 Secondary Reserve
 Tertiary Reserve
 Intraday offer
 Baseload load shifting (Price optimisation on Elspot)
 Load shifting by environmental optimisation
Primary Reserves and Baseload load shifting are demonstrated by real market participation with
existing market interfaces.
For prequalification for the Secondary Reserve market, it is necessary to uphold the reserve at all
times for a whole month and prequalification for Tertiary Reserve market requires a minimum bid size
of 10MW. It is presently not possible for Power Hub to uphold a reserve for such a long period with its
portfolio, neither can the minimum bid size be matched by aggregation with the limited amount of local
units in Power Hub’s portfolio. Hence, the Secondary Reserve, Tertiary Reserve and Intraday markets

are emulated interfaces since there is no contractual business set up for those markets yet, and the
emulation of these markets is as real as it could be done in practice within the project scope.
However, Power Hub is technically able to deliver services to those markets from its units and market
rules can be complied with in future by an increasing number of local units to increase the total
capacity of the portfolio.
There is currently no market mechanism that covers environmental optimisation from a consumption
side load shift point of view. There are emission trading mechanisms such as the EUETS (European
Union Emission Trading Scheme), however, these mechanisms are targeted towards the generation
and not the consumption. It is possible for consumers to buy allowances from the market in order to
remove emission permits – often corresponding to the consumer’s emissions, but this does not give
any indications whether it is environmentally most beneficial to consume power in one hour or the
other. Power Hub is based on an economical optimisation engine and in order to demonstrate Power
Hub’s capabilities for environmental load shift optimisation, a wind forecast based ‘environmental
energy cost’ is proposed and used forecast in comparison to the day-ahead baseload price forecast.
3.1.3 Setup
The setup to demonstrate market participation in the markets defined in the scope is described in this
section. The setup is the implemented system architecture within the Power Hub User Interface. For
each market the following test activities are performed chronologically (also see Figure 8).
1. Power Hub retrieves ability forecasts that describe the technical capabilities of local units
2. Power Hub retrieves market price forecasts
3. Power Hub generates offers based on the forecasts and sends market offers to the relevant
market before gate closure
4. Power Hub receives market feedback via market contracts
5. Power Hub schedules the delivery of contracted volumes
6. Delivery is verified by measurements
Local Unit 1
Local Unit 2
Power Hub Market
1. Ability forecast
1. Ability forecast
2. Market price
forecasts
3. Market offer
4. Market contract
5. Delivery of Market
contract
5. Delivery of Marketcontract
Figure 8: Demonstration setup.
3.1.4 Log and results
This section describes the specific test activities and the results for each market.

3.1.4.1 Primary Reserve
The participation in the Primary Reserve market is demonstrated with Novo Nordisk’s gas turbine
for10/11/2012. The unit is offering into the Frequency-controlled normal operation reserve (FNR)
market in DK2. FNR is an automatically regulated reserve to keep the balance in the grid by keeping
the grid frequency close to 50Hz. The minimum bid size is 0.3MW and bids of hour-by-hour volumes
are traded. The Gate Closure for submitting offers is 9/11/2012 20.00 which is the day prior to
delivery. The Reserve has to be upheld in the contracted hours on 10/11/2012.
The forecasts available at the time of gate closure as well as already traded services, eg baseload
traded at the day-ahead Spot market, are taken into account in the optimisation algorithms used to
determine the optimal market offers.
According to the unit’s ability forecast in Table 6, the unit must run on a minimum load of 1500kW and
can produce up to 2500kW, during the whole day.
Table 6: Ability Forecast for Novo Nordisk Gasturbine.
Timestamp
(Local Time) Pmin [kW] Pmax [kW]
10/11/2012 00.00 1500 2500
The Spot and FNR price forecasts for 10/11/2012 are shown in Table 7. The price forecasts for FNR
are assumed to be high since there are currently no reliable FNR price forecasts available. The actual
FNR prices are much lower than our forecasts. However, our forecast stimulates the attractiveness of
submitting an offer to the FNR market. The Spot prices are retrieved from a third party supplier and
are from the VPP’s perspective based on a black box algorithm.
Table 7: Price forecasts for Spot and FNR.
Market Spot FNR
Timestamp
(local time) DKK/[MWh/h] DKK/[MW]
10/11/2012 00.00 250 5000
10/11/2012 01.00 238 5000
10/11/2012 02.00 219 5000
10/11/2012 03.00 211 5000
10/11/2012 04.00 203 5000
10/11/2012 05.00 206 5000
10/11/2012 06.00 215 5000
10/11/2012 07.00 234 5000
10/11/2012 08.00 244 5000
10/11/2012 09.00 257 5000
10/11/2012 10.00 258 5000
10/11/2012 11.00 262 5000
10/11/2012 12.00 258 5000
10/11/2012 13.00 256 5000
10/11/2012 14.00 264 5000
10/11/2012 15.00 268 5000
10/11/2012 16.00 286 5000

10/11/2012 17.00 323 5000
10/11/2012 18.00 331 5000
10/11/2012 19.00 288 5000
10/11/2012 20.00 264 5000
10/11/2012 21.00 251 5000
10/11/2012 22.00 247 5000
10/11/2012 23.00 231 5000
Power Hub generates market offers for Baseload and FNR, as depicted in Table 8 based on the
forecasts above. The offers are sent to the markets before gate closure. Power Hub’s optimisation
ensures that the offers stay within the limits of the ability forecasts in Table 6.
Table 8: Baseload and FNR market offer.
Timestamp
(local time)
Price independent
baseload
[MW]
FNR (Symmetric)
[MW]
10/11/2012 00.00 2 0.5
10/11/2012 01.00 2 0.5
10/11/2012 02.00 2 0.5
10/11/2012 03.00 2 0.5
10/11/2012 04.00 2 0.5
10/11/2012 05.00 2 0.5
10/11/2012 06.00 2 0.5
10/11/2012 07.00 2 0.5
10/11/2012 08.00 2 0.5
10/11/2012 09.00 2 0.5
10/11/2012 10.00 2 0.5
10/11/2012 11.00 2 0.5
10/11/2012 12.00 2 0.5
10/11/2012 13.00 2 0.5
10/11/2012 14.00 2 0.5
10/11/2012 15.00 2 0.5
10/11/2012 16.00 2 0.5
10/11/2012 17.00 2 0.5
10/11/2012 18.00 2 0.5
10/11/2012 19.00 2 0.5
10/11/2012 20.00 2 0.5
10/11/2012 21.00 2 0.5
10/11/2012 22.00 2 0.5
10/11/2012 23.00 2 0.5
Table 9 shows that 0.5MW of FNR was contracted with a gas turbine from the company Novo Nordisk
for the whole day.

Table 9: Contracted volume for delivery allocated at Novo Nordisk's Gas Turbine.
Timestamp
(local time)
Price independent
baseload [MW]
FNR (Symmetric)
[MW]
10/11/2012 00.00 2 0.5
10/11/2012 01.00 2 0.5
10/11/2012 02.00 2 0.5
10/11/2012 03.00 2 0.5
10/11/2012 04.00 2 0.5
10/11/2012 05.00 2 0.5
10/11/2012 06.00 2 0.5
10/11/2012 07.00 2 0.5
10/11/2012 08.00 2 0.5
10/11/2012 09.00 2 0.5
10/11/2012 10.00 2 0.5
10/11/2012 11.00 2 0.5
10/11/2012 12.00 2 0.5
10/11/2012 13.00 2 0.5
10/11/2012 14.00 2 0.5
10/11/2012 15.00 2 0.5
10/11/2012 16.00 2 0.5
10/11/2012 17.00 2 0.5
10/11/2012 18.00 2 0.5
10/11/2012 19.00 2 0.5
10/11/2012 20.00 2 0.5
10/11/2012 21.00 2 0.5
10/11/2012 22.00 2 0.5
10/11/2012 23.00 2 0.5
The actual delivery of the contracted volume on 10/11/2012 is depicted in Figure 9. On 10/11/2012,
Novo Nordisk’s gas turbine had a baseload setpoint at 2MW and was contracted to uphold 0.5MW of
FNR. FNR is activated automatically depending on the grid frequency, hence the gas turbine will up
and down regulate 0.5MW from its setpoint.
Figure 9 depicts the Novo’s ideal delivery of FNR and the actual delivery depending on the grid
frequency. It can be seen that Novo Nordisk’s gas turbine is delivering up- and down- regulation
following the trend of the ideal behaviour.

Figure 9: Activation of FNR dependent on the grid frequency at Novo Nordisk's gas turbine.
3.1.4.2 Secondary Reserve
The Secondary Reserve market in Denmark is a 1-month market where requirements are published
at the Danish TSO’s Energinet.dk’s website on the tenth day of the previous month at the latest. The
units used in this demonstration cannot technically uphold the reserve at all times for a whole month
yet. It is therefore assumed that the Secondary Reserve market is a 1-hour market in order to perform
this demonstration.
Secondary reserve (SR) is activated automatically responding to a signal from Energinet.dk. The
activation signal is sent online with reference to the offer. The reserve must be fully supplied within 15
minutes.
It is assumed that there are two products available, Secondary Reserve up- and down-regulation. Up-
regulation means that production units must increase the production whereas consumption units must
decrease their load. Vice versa for down-regulation. This is different to the existing Secondary
Reserve market design, where there is only one symmetrical product.
The forecasts available at the time of market closure as well as already traded services, eg baseload
traded at the day-ahead Spot market, are taken into account in the optimisation algorithms used to
determine the optimal market offers.
Secondary Reserve supplied from consumption
The participation in the Secondary Reserve market is demonstrated with Furesø district water supply
station on 22/11/2012. Furesø district water supply consists of 27 fresh water pumps that are
controlled by Power Hub as one aggregated system.
1400
1600
1800
2000
2200
2400
2600
49,88
49,95
49,97
49,98
49,98
49,99
50,00
50,00
50,01
50,01
50,02
50,02
50,03
50,03
50,03
50,03
50,04
50,04
50,05
50,06
50,06
50,07
50,08
50,10
Power[kW]
Frequency [Hz]
Current Power
Ideal

The unit is offering into an emulated Secondary Reserve market in this demonstration. The
Secondary Reserve market is emulated because there is no contractual business setup between
Power Hub and Energinet.dk to deliver this service, mainly because it does not match the minimum
bid size of 1MW and the bid horizon of one month. However, this demonstration shows that Power
Hub is technically able to deliver Secondary Reserve from consumption units.
The ability forecast in Table 10 shows that the Furesø station has to run on a minimum load of -60kW
and can run on a maximum of -150kW during operating day. The values are denoted negative,
because the station is classified as a consumption unit in contrary to production units that use positive
values in their plans.
Table 10: Ability Forecast for Furesø district water supply station.
Timestamp
22/11/2012 00.00 -60 -150
The Spot and Secondary Reserve price forecasts for 22/11/2012 from 09.00 until 12.00 are shown in
Table 11. The price forecast for SR is a very rough assumption to emulate that the Secondary
Reserve up-market is attractive to submit an offer during hours 10.00-12.00.
Table 11: Price forecasts for Spot and Secondary Reserve.
Market Spot SR up SR down
Timestamp
(local time) DKK/[MWh/h] DKK/[MW] DKK/[MW]
22/11/2012 09.00 200 0 0
22/11/2012 10.00 200 3000 0
22/11/2012 11.00 200 3000 0
22/11/2012 12.00 200 0 0
After Power Hub’s optimisation, the market offers submitted to the market are depicted in Table 12.
As expected, Power Hub submits an offer of 70kWh/h to the Secondary Reserve up-market for hours
10.00-12.00. It is assumed that the unit must run on maximum baseload within this timeframe. The
market is emulated to accept the offer, therefore the market contract is identical to the market offer.
The water station must uphold 70kWh/h capacity for up-regulation in the relevant timeframe. That
means that the station must be able to decrease consumption up to 70kW when requested.
Table 12: Market offer and contract for Baseload and Secondary Reserve.
Price independent
baseload SR up
SR
down
Timestamp (local time) [kWh/h] [kW] [kW]
22/11/2012 09.00 -150 0 0
22/11/2012 10.00 -150 70 0
22/11/2012 11.00 -150 70 0
22/11/2012 12.00 -150 0 0

There is currently no interface established between Energinet.dk and Power Hub to demonstrate the
activation of Secondary Reserve. The activation is therefore emulated manually by change of the load
plan every 5 minutes in real-time by adding the activation request as shown in Table 13.
Table 13: Secondary Reserve up-regulation request.
Timestamp
(local time)
SR up-regulation request
[kW]
22/11/2012 10.25 0
22/11/2012 10.30 0
22/11/2012 10.35 50
22/11/2012 10.40 70
22/11/2012 10.45 20
22/11/2012 10.50 0
22/11/2012 10.55 60
22/11/2012 11.00 40
22/11/2012 11.05 60
22/11/2012 11.10 70
22/11/2012 11.15 70
22/11/2012 11.20 70
22/11/2012 11.25 70
22/11/2012 11.30 70
22/11/2012 11.35 70
22/11/2012 11.40 70
22/11/2012 11.45 0
22/11/2012 11.50 0
22/11/2012 11.55 0
22/11/2012 12.00 0
22/11/2012 12.05 0
22/11/2012 12.10 0
22/11/2012 12.15 0
22/11/2012 12.20 0
The result of Secondary Reserve up-regulation activation at Furesø district water supply station is
depicted in Figure 10. From 10.00-12.00, Furesø district water supply station was scheduled to run at
baseload of -150kW. At the same time, 90kW of up-regulation Secondary Reserve was upheld. From
10.35-11.50, Power Hub emulated an activation request for up-regulation. The result can be seen
below. The water supply station is following the activation setpoint closely.
The values are negative, because it is classified as a consumption unit contrary to production units
that use positive values in their plans.

Figure 10: Activation of SR up-regulation.
Secondary Reserve supplied from production
The Secondary Reserve market is a 1-month market where the gate closes via tenders ahead of the
month. This requirement technically disqualifies wind power from participating in the Secondary
Reserves market. In order to still be able to demonstrate that WTGs can provide a Secondary
Reserve like service, it is – in this demonstration – assumed that the Secondary Reserve market is a
1-hour market. The forecasts available at the time of market closure as well as already traded
services, eg baseload traded at the day-ahead Spot market, are taken into account in the optimisation
algorithms used to determine the optimal market offers.
The participation in the Secondary Reserve market and the delivery of the contracted volume from
generation is demonstrated with wind turbine generators (WTG). This demonstration activity has been
performed in collaboration with the Danish wind turbine manufacturer VESTAS.
 Flexibility forecast – Hourly forecasted WTG load constraints (Volume [kW]). The forecasted
WTG load constraints are received from a pre-sales version of the ‘Vestas Analogue
Ensemble-Based Power Forecasting’ tool. This is shown in Table 14.
 Forecasted Secondary Reserve market prices. This is shown in Table 15.
 Market optimisation result - Market offers at the TSO operated market for Secondary Reserve.
The markets are emulated for the purpose of this demonstration – For the demonstration
purpose, the bid duration of the Secondary Reserve market is assumed to be two hours which
is opposed to the one-month bid duration used in the Danish Secondary Reserve market. This
is shown in Table 16.
 Market contracts. For the purpose of the demonstration, the market offers are assumed
accepted for a period of two consecutive hours. This is shown in Table 17.
 Distribution optimisation result – load schedules for the WTGs. This is shown in Table 18.
 Online measurements
o VPP activation setpoints for WTGs – The Secondary Reserve activation has been
emulated by a sine curve with a period of 2 hours. (Power)
o Realised production for WTGs (Power)
o Alternative WTG-production measurement – The estimated production in case the
WTG setpoints were not manipulated in order to activate the Secondary reserve
-160
-140
-120
-100
-80
-60
-40
-20
0
10:20 10:30 10:40 10:50 11:00 11:10 11:20 11:30 11:40 11:50
Power[kW]
Time
SR Activation Setpoint
Current Power
Baseload

Hour 1 Hour 2
Pmin [MW] Pmax
[MW]
Pmin
[MW]
Pmax
[MW]
WTGs 0 11.2 0 8.3
Table 14 Ability forecast for the WTGs. Pmin [MW] denotes the minimum power constraint for the relevant hour.
Pmax [MW] denotes the maximum power constraint for the relevant hour.
Hour 1 Hour 2
Price SR up
[DKK/MW]
Price SR
down
[DKK/MW]
Price SR up
[DKK/MW]
Price SR
down
[DKK/MW]
Market 500 500 500 500
WTGs 400 400 400 400
Table 15 Forecasted Secondary Reserve market prices [DKK/MW] and asset costs of maintaining the reserves
[DKK/MW].
For the WTGs, the costs are derived from opportunity costs related to maintaining the reserves.
Supplying down-reserve only results in losses of income from the activation of the Secondary
Reserve whereas supplying up-reserve from the WTGs requires them to be down-regulated in the
periods where the reserve is to be maintained, thus resulting in a far bigger cost of supplying the up-
reserve from WTGs. The market for Secondary Reserves in Denmark requires symmetric offers,
however the optimisation engine in Power Hub treats them as two markets that must have the
symmetric volumes.
Hour 1 Hour 2
Volume
[MW]
Price
[DKK/MW]
Volume
[MW]
Price
[DKK/MW]
SR offer 2.0 800 2.0 800
Table 16 Market optimisation results for the emulated Secondary Reserve market in terms of volume in [MW], and
price in [DKK/MW].
Power Hub has aggregated the two control-directions into one symmetric market offer of which the
price (shown in table 16) is the sum of costs for the two ‘submarkets’. The symmetric offer is a market
requirement for secondary reserve in DK. The reserves are constrained to 2MW as this is the defined
technical limit for supplying Secondary Reserve from these specific WTGs.
Hour 1 Hour 2
Volume
[MW]
Price
[DKK/MW]
Volume
[MW]
Price
[DKK/MW]
SR
contract
2.0 1000 2.0 1000
WTG
Spot
market
contract
9.2 - 6.5 -
Table 17 Market contracts from the emulated Secondary Reserve market in terms of volume in [MW], and price in
[DKK/MW].
For reasons of simplicity, it assumed that the forecasted market prices are also the realised market
prices, and according to table 15, the contracted price is higher than the offered price. As the

Secondary Reserve is only to be demonstrated for two hours, it is assumed that the offers are only
accepted in the two hours of relevance. The lower row in the table shows the market contract for the
WTGs at the emulated day ahead Spot market for the hours in question. The market offers at the
emulated day-ahead Spot market were found using the optimisation algorithms, assuming the reserve
market more profitable.
Hour 1 Hour 2
SR down
[MW]
SR up
[MW]
SR down
[MW]
SR up
[MW]
WTGs 2.0 2.0 2.0 2.0
Table 18 Load schedules for maintaining Secondary Reserve from the WTGs.
Table 18 shows the resulting load schedule for the WTG’s, and it shows that the WTG’s are reserved
for both up- and down-regulation at the same time. The WTG’s will thus be capable of providing either
up-regulation or down-regulation in the same hour of operation.
Figure 11 shows the activation profile of the WTGs throughout the 2-hour (7200 seconds)
demonstration period. As the figure shows, most of the time the theoretically available power from the
WTGs calculated by the park controller lies above the forecast of the maximum production from the
WTGs. When this is the case, the optimisation of load schedules and reserves has left room for the
reserve to be fully activated at any time. However about 20 minutes (approximately 1200 seconds)
into the demonstration, the wind drops suddenly for a couple of minutes reducing the capacity of the
WTGs for those minutes. Apart from this short time instance, the WTGs follow the setpoint with a high
degree of precision.
Note that the baseload is lowered about 0.5MW between the 2 hours of demonstration (at 3600
seconds) causing the second half of the sine curve to be lowered a little compared to the first half.
This is due to the forecast of the maximum production being lower in the second hour compared to
the first hour. The delivery of Secondary Reserves is defined as being relative to the load schedule
and thus the skewness of the sine curve is both correct and desired.
Figure 11 Secondary Reserve supplied from WTGs.

The baseload of the WTGs is placed lower than the forecasted maximum possible production from
the WTGs in order to ensure the availability of the reserve. The activation of the Secondary Reserve,
for the purpose of the demonstration emulated with one period of a sine curve, corrects the setpoint of
the WTGs relative to the baseload.
3.1.4.3 Tertiary Reserve
Tertiary Reserve (TR) is a part of Ancillary Services to balance the grid and is determined based on
the reserve’s ability to cover the largest possible outage in the control area.
In Denmark, the Tertiary Reserve market is a one-hour market where the gate closes the day ahead
at 09.00. The forecasts available at the time of market closure as well as other expected service
deliveries, eg baseload that will be traded later at the day-ahead Spot market, are taken into account
in the optimisation algorithms used to determine the optimal market offered.
There are two products available, Tertiary Reserve up- and down-regulation. Up-regulation means
that production units must increase the production, and consumption units must decrease their
consumption. Vice versa for down-regulation.
The process of being activated in the Regulating Power market is that offers are submitted to a merit
order list commonly shared between the Nordic TSOs, the Nordic Operational Information System
(NOIS) list. If contracts are received for Tertiary Reserves, offers of at least the reserved volume must
be submitted to the NOIS list for the relevant hours. The local TSO calls for the activation when it
becomes relevant. In the case of this demonstration, it is assumed that the TSO calls for full activation
of the up-reserve in the last 45 minutes of the first hour and that the TSO calls for full activation of the
down-reserve in the last 45 minutes of the second hour.
The participation in the Tertiary Reserve market and the delivery of the contracted volume is
demonstrated with wind turbine generators (WTG).
 Flexibility forecast – Hourly forecasted WTG load constraints (Volume). The forecasted WTG
load constraints are received from a pre-sales version of the ‘Vestas Analogue Ensemble-
Based Power Forecasting’ tool. This is shown in Table 19.
 Forecasted Tertiary/Manual Reserve market prices. This is shown in Table 20.
 Market optimisation results - Market offers at the TSO operated market for Tertiary/Manual
Reserve as well as the baseload offered into the Spot Market. The markets are emulated for
the purpose of this demonstration. For the demonstration purpose, the minimum bid size of the
Tertiary/Manual Reserve market is assumed 2MW which is opposed to the 10MW minimum
bid size used in the Danish Tertiary/Manual Reserve market. This is shown in Table 21.
 Market contracts for Tertiary/Manual Reserves – For the purpose of the demonstration, the
market offers are assumed accepted for a period of two consecutive hours. This is shown in
Table 22.
 Forecasted Regulating Power market prices. This is shown in Table 23.
 Market optimisation results for offers for activating the Tertiary/Manual Reserve, i.e., offers to
the Regulating Power market – Getting accepted at the markets for Tertiary/Manual Reserve
entails mandatory posting of market offers at the TSO operated market for Regulating Power.
This is shown in Table 24.
 Market contracts for reserve activation – For the purpose of the demonstration, the market
offers are assumed accepted in both directions (up and down regulation). This is shown in
Table 25.

 Distribution optimisation result – load schedules for the WTGs. This is shown in Table 26.
 Online measurements
o VPP activation setpoints for WTGs (Power)
o Realised production for WTGs (Power)
o Alternative WTG-production measurement – The estimated production in case the
WTG setpoints was not manipulated in order to activate the Tertiary reserve
Hour 1 Hour 2
Pmin
[MW]
Pmax
[MW]
Pmin
[MW]
Pmax
[MW]
WTGs 0 10.3 0 10.3
Table 19 Flexibility forecast for the WTGs for the energy storage.
Pmin [MW] denotes the minimum power constraint for the relevant hour. Pmax [MW] denotes the
maximum power constraint for the relevant hour.
Hour 1 Hour 2
Price TR up
[DKK/MW]
Price TR
down
[DKK/MW]
Price TR up
[DKK/MW]
Price TR
down
[DKK/MW]
Market 800 100 800 100
WTGs 750 50 750 50
Table 20 Forecasted Tertiary Reserve market prices [DKK/MW] and asset costs of maintaining the reserves
[DKK/MW].
For the WTGs, the costs are derived from opportunity costs related to maintaining the reserves.
Supplying down-reserve only results in losses of income from the activation of the Tertiary Reserve
whereas supplying up-reserve from the WTGs requires them to be down-regulated in the periods
where the reserve is to be maintained, thus resulting in a far bigger cost of supplying the up-reserve
from WTGs.
Hour 1 Hour 2
Volume
[MW]
Price
[DKK/MW]
Volume
[MW]
Price
[DKK/MW]
TR up
offer
2.0 750 2.0 750
TR down
offer
2.0 50 2.0 50
Table 21 Market optimisation results for the emulated Tertiary Reserve market in terms of volume in [MW], and price
in [DKK/MW].
Due to the forecasted market prices Power Hub has found that it is profitable to offer the WTGs as
both up- and down-regulation. The reserves are constrained to 2MW, as this is the defined technical
limit for supplying Tertiary Reserve from these specific WTGs.

Hour 1 Hour 2
Volume
[MW]
Price
[DKK/MW]
Volume
[MW]
Price
[DKK/MW]
TR up
contract
2.0 800 2.0 800
TR down
contract
2.0 100 2.0 100
WTG
Spot
market
contract
10.2 - 8.2 -
Table 22 Market contracts from the emulated Tertiary Reserve market in terms of volume in [MW], and price in
[DKK/MW].
prices. As the Tertiary Reserve is only to be demonstrated for two hours, it is assumed that the offers
are only accepted in the two hours of relevance. The lower row in the table shows the market contract
for the WTGs at the emulated day ahead Spot market for the hours in question. The market offers at
the emulated day-ahead Spot market were found using the optimisation algorithms, assuming the
reserve market more profitable.
Hour 1 Hour 2
Reg.Price up
[DKK/MWh]
Reg.Price
down
[DKK/MWh]
Reg.Price up
[DKK/MWh]
Reg.Price
down
[DKK/MWh]
Regulating
Market
100 800 100 800
WTGs 50 750 50 750
Table 23 Forecasted Regulating Power market prices [DKK/MWh] and asset costs of activating the reserves
[DKK/MW].
The costs are derived from the marginal costs of up-regulating the WTGs, given that the opportunity
costs have already been covered by the contracted up-directional Tertiary Reserve, i.e., the marginal
costs related to producing the power. In the down-direction, the costs are derived from the opportunity
costs related to not producing the energy and thus not receiving subsidiaries.
Hour 1 Hour 2
Volume
[MW]
Price
[DKK/MWh]
Volume
[MW]
Price
[DKK/MWh]
Reg.up
offer
2.0 50 2.0 50
Reg.down
offer
2.0 750 2.0 750
Table 24 Market optimisation results for the emulated Regulating Power market in terms of volume in [MWh], and
price in [DKK/MWh].
Due to the forecasted market prices Power Hub has found that it is profitable to offer the WTGs as
down-regulation and the energy storage as up-regulation. The Down reserve - from the WTGs - is
constrained to 2MW, as this is the defined technical limit for supplying Tertiary Reserve from these
specific WTGs.

Hour 1 Hour 2
Volume
[MW]
Price
[DKK/MWh]
Volume
[MW]
Price
[DKK/MWh]
Reg.up
contract
2.0 100 0.0 -
Reg.down
contract
0.0 - 2.0 800
Table 25 Market contracts from the emulated Regulating Power market in terms of volume in [MWh], and price in
[DKK/MWh].
prices. As the Tertiary Reserve and the activation thereof is only to be demonstrated for two hours, it
is assumed that one offer is accepted each hour. In order to emphasize the activation of the
Regulating Power, it is assumed that the activation messages from the TSO are received 15 minutes
into hour 5 and 6, resulting in activations in the last 45 minutes of the two hour slots.
Hour 1 Hour 2
TR down
[MW]
TR up
[MW]
TR down
[MW]
TR up
[MW]
WTGs 0.0 2.0 2.0 0.0
Table 26 Load schedules for activating the Tertiary Reserve, i.e., supplying the Regulating Power from the WTGs.
Figure 12 shows the activation profile of the WTGs throughout the 2-hour (7200 seconds)
demonstration period. As the figure shows, most of the time the theoretically available power from the
WTGs calculated by the park controller lies above the forecast of the maximum production from the
WTGs. When this is the case, the optimisation of load schedules and reserves has left room for the
reserve to be fully activated at any time. However about 20 minutes (approximately 1200 seconds)
into the demonstration, the wind drops suddenly for a couple of minutes reducing the capacity of the
WTGs for those minutes. Apart from this short time instance, the WTGs follow the setpoint with a high
degree of precision.
Figure 12 Tertiary Reserve supplied from WTGs.

The baseload of the WTGs is placed lower than the forecasted maximum possible production from
the WTGs in order to ensure the availability of the reserve. The activation of the reserve is invoked
using an emulated market for Regulating Power.
3.1.4.4 Intraday
Intraday markets generally provide continuous power trading 24 hours a day, seven days a week,
covering individual hours. For the Nordic intraday market ELBAS, trading is possible up to one hour
prior to delivery. The traded products are normally one-hour long power contracts. The intraday
market allows participants to adjust the day-ahead trade in case of deviations of the day-ahead
because of eg forecast errors.
The intraday market is emulated and it is assumed that the market is liquid such that all intra-day
trades are feasible.
Intraday supplied from consumption
This case demonstrates offering into the intraday market and delivering the contracted volume from
consumption units and is a continuation of the demonstration of Secondary Reserve in chapter
3.1.4.2. The offer submitted to the intraday market is emulated. However, the demonstration shows
the technical capability to deliver the contracted volume.
The ability forecast is still the same as in Table 10 and the price forecast for intraday is assumed to be
DKK 3000/MWh in the hour between 12.00-13.00. This is a high estimate to stimulate the
attractiveness of the intraday market.
Table 27: Intraday price forecast.
Market Spot Intraday
Timestamp
(local time) DKK/[MWh/h] DKK/[MWh/h]
22/11/2012 10.00 200 0
22/11/2012 11.00 200 0
22/11/2012 12.00 200 3000
22/11/2012 13.00 200 0
22/11/2012 14.00 200 0
Since Secondary Reserve was contracted until 12.00 from the water station (see Table 12) flexibility
is available to decrease the consumption from 12.00 that can be offered into the intraday market.
Power Hub chooses to offer 75kWh in that hour. The market is emulated to contract the offer
completely without changes.
Table 28: Market offer and contract for Intraday.
Price independent baseload Intraday
Timestamp (local time) [kWh/h] [kWh/h]
22/11/2012 10.00 -150 0
22/11/2012 11.00 -150 0
22/11/2012 12.00 -150 75
22/11/2012 13.00 -150 0
22/11/2012 14.00 -150 0

Figure 13 shows the delivery of 75kWh of contracted volume from the intraday market between 12.00-
13.00. The water station is scheduled to decrease its consumption from -150kW to -75kW at 12.00 to
deliver the contracted intraday volume. At 13.00 the unit is scheduled to return to the initial baseload
setpoint of -150kW. The unit is following the setpoint closely.
Figure 13: Delivery of Intraday volume.
Intraday supplied from production
The Intraday market integration for production is demonstrated with wind turbine generators (WTG).
This demonstration activity has been performed in collaboration with the Danish wind turbine
manufacturer VESTAS. For this demonstration, the following data will be shown.
 Flexibility forecast – Hourly forecasted WTG load constraints. The forecasted WTG load
constraints are received from a pre-sales version of the ‘Vestas Analogue Ensemble-Based
Power Forecasting’ tool. [MW]
 Market contracts – Results of the emulated Day-ahead Spot Market auction as well as results
of emulated intra-day trades. [MWh/h]
 Realised production (Energy) – Measurements of the WTG’s production [MWh/h]
 Imbalance between expected and realised production [MWh/h]
Day-ahead Intra-day Imbalances
Time
Pmin
[MW]
Pmax
[MW]
Day-
ahead
Spot
[MWh/
h]
Pmin
[MW]
Pmax
[MW]
Intra-
day
trade
[MWh/
h]
Produc
tion
[MWh/
h]
Day-
ahead
Spot
[MWh/
h]
Intra-
day
[MWh/
h]
28-11-2012
13.00 3 4,339 4,339 1,301 1,301 -3,038 2,785 -1,554 1,484
28-11-2012
14.00 3 3,882 3,882 0,277 0,277 -3,605 3,397 -0,485 3,120
-160
-140
-120
-100
-80
-60
-40
-20
0
22-11-2012 11:45 22-11-2012 12:15 22-11-2012 12:45
Power[kW]
Time
Intraday adjustment setpoint
Current Power
Baseload

28-11-2012
15.00 3 3,729 3,729 1,603 1,603 -2,126 3,364 -0,365 1,761
28-11-2012
16.00 3 6,002 6,002 0,524 0,524 -5,478 1,367 -4,635 0,843
28-11-2012
17.00 3 4,262 4,262 0,488 0,488 -3,774 0,906 -3,356 0,418
28-11-2012
18.00 3 5,936 5,936 0,666 0,666 -5,27 1,654 -4,282 0,988
28-11-2012
19.00 3 5,989 5,989 2,405 2,405 -3,584 2,594 -3,395 0,189
28-11-2012
20.00 3 7,777 7,777 3,000 3,992 -3,785 3,903 -3,874 -0,089
28-11-2012
21.00 3 5,996 5,996 2,92 2,92 -3,076 4,221 -1,775 1,301
28-11-2012
22.00 3 5,941 5,941 2,496 2,496 -3,445 4,466 -1,475 1,970
28-11-2012
23.00 3 4,439 4,439 2,731 2,731 -1,708 4,192 -0,247 1,461
29-11-2012
00.00 3 5,104 5,104 2,972 2,972 -2,132 4,660 -0,444 1,688
Table 29: How intra-day trading can reduce imbalances (demonstration data).
The columns sorted under ‘Day-ahead’ show the flexibility forecasts [MW] defining the technically
defined lower limit for the WTGs’ production (Pmin), the weather-forecast derived expected upper limit
(Pmax), and the resulting (emulated) trades at the day-ahead Spot market [MWh/h]. The columns
sorted under ‘Intra-day’ show the updated flexibility forecasts (Pmin and Pmax) [MW], the resulting
(emulated) intra-day trades [MWh/h], and the measured production from the WTGs. The intra-day
market is assumed liquid and the optimisation goal is to trade intra-day relying fully on the updated
forecasts. The last two columns show the imbalances as they would have been according to to
respectively the day-ahead Spot trades and the intra-day updated trades.
The market is an hourly market where the gate closes for trading 1 hour ahead of the production-hour.
In this demonstration, wind power forecasts are received twice a day at approximately 12.00 and
00.00 for a period of 36 hours ahead in time. It is therefore possible to optimise the day-ahead trades
via intraday trades for a period of 12 hours.
Figure 14 shows how Production measurements and imbalances caused by day-ahead trades and
how those trades can be re-optimised via intraday trades. The production measurements show the
actual measured production from the WTGs. The imbalance bars show the size of the imbalances
caused by day-ahead trading alone and intra-day re-optimised trading. The imbalance bars have
been biased, such that the total height of the bars indicate how much was traded in the current hour,
eg 6MWh was traded day ahead in the fourth hour. This would have resulted in an imbalance of
approximately 4.5MWh.
The intraday re-optimised trade for that hour resulted in a total of 2.2MWh, reducing the imbalances to
less than 1MWh. As the figure shows, re-optimising intra-day using the updated forecasts is not
economically optimal for each individual hour. However the overall reduction of imbalances through
intra-day trading is significant.

Figure 14 Production measurements and imbalances caused by day-ahead trades and day-ahead trades that are re-
optimised via intra-day trades.
The production measurements show the actual measured production from the WTGs. The imbalance
bars show the size of the imbalances caused by day-ahead trading alone and intra-day re-optimised
trading. The imbalance bars have been biased, such that the total height of the bars indicate how
much was traded in the current hour, eg 6MWh was traded day ahead in the fourth hour. This would
have resulted in an imbalance of approximately 4.5MWh. The intraday re-optimised trade for that hour
resulted in a total of 2.2MWh, reducing the imbalances to less than 1MWh.
3.1.4.5 Baseload Load Shifting
Baseload Load Shifting is demonstrated by optimising the load schedule of Fuersø district water
supply station according to the day-ahead Spotprice forecast. In the Nordic region, the spotmarket
Elspot is an hourly market with gate closure at noon day-ahead.
Fuersø district water supply consists of 27 fresh water pumps that are controlled by Power Hub as
one aggregated system. The station will be scheduled in a cost-effective way respecting the technical
limitations of the station.
Table 30: Ability Forecast for Furesø district water supply station.
Timestamp
22/11/2012 00.00 -60 -150
The ability forecast is shown in Table 30. Moreover, the water station’s water reservoir represents an
energy limit of how much water can be pumped during the day.
Based on the price forecast, the price optimisation results in a market offer as shown in Table 31. The
offer is emulated to be accepted as submitted.

Table 31: Spotprice forecast and Baseload offer.
Spot Baseload offer
Timestamp
(local time)
DKK/[MWh/h] [kWh/h]
30/11/2012 00.00 265 -85.07
30/11/2012 01.00 261 -85.07
30/11/2012 02.00 257 -85.07
30/11/2012 03.00 250 -85.07
30/11/2012 04.00 256 -85.07
30/11/2012 05.00 265 -60.00
30/11/2012 06.00 288 -60.00
30/11/2012 07.00 449 -60.00
30/11/2012 08.00 491 -60.00
30/11/2012 09.00 460 -60.00
30/11/2012 10.00 457 -60.00
30/11/2012 11.00 434 -60.00
30/11/2012 12.00 389 -60.00
30/11/2012 13.00 378 -60.00
30/11/2012 14.00 377 -60.00
30/11/2012 15.00 403 -60.00
30/11/2012 16.00 457 -60.00
30/11/2012 17.00 498 -60.00
30/11/2012 18.00 367 -60.00
30/11/2012 19.00 313 -60.00
30/11/2012 20.00 293 -60.00
30/11/2012 21.00 284 -60.00
30/11/2012 22.00 270 -60.00
30/11/2012 23.00 260 -60.00
The spot prices are relatively high from 5.00 compared to the hours before. The unit is scheduled to
run on a minimum baseload in the respective hours.
Figure 15 shows the delivery of the optimised loadplan from 00.00-06.30. The current power
consumption follows the setpoint closely and hence delivers the contracted baseload volume within
this period.

Figure 15: Delivery of Baseload load shifting.
3.1.4.6 Load Shifting by environmental optimisation
Load Shifting by environmental optimisation is demonstrated by optimising the load schedule of the
Furesø district water supply station that consists of 27 fresh water pumps which are controlled by
Power Hub.
The loadplan is optimised according to wind speed forecasts. The wind speeds are converted into a
Spot price according to Figure 16. It is assumed that the lowest anticipated wind speeds are
converted into a high price of DKK 300/MWh where the highest anticipated windspeeds are converted
to a low price of DKK 50/MWh.
Figure 16: Conversion of wind speed into price.
Consequently, the water station will be scheduled in a cost-effective way according to the converted
wind forecast in Table 32. The technical limitations of the station, as well as the water reservoir’s
energy limits must be respected.
0
50
100
150
200
250
300
350
10 12 14 16 18 20 22
Price[DKK/MWh]
Wind speed [knots]

Power Hub’s optimisation results in a baseload market offer as shown in the table below. In the most
expensive hours from hours 00.00-05.00 Power Hub offers -60kWh/h which is the forced minimum
load of the unit according to the ability forecast in Table 30. In the cheapest hours 16.00-21.00
consumes up to its maximum of -150kWh/h.
Table 32: Wind speed forecasts converted into price and Baseload offer.
Wind speed Spot price Baseload offer
Timestamp
(local time) [knots] DKK/[MWh/h] [kWh/h]
29/11/2012 00.00 11 275 -60
29/11/2012 01.00 12 250 -60
29/11/2012 02.00 13 225 -60
29/11/2012 03.00 14 200 -60
29/11/2012 04.00 14 200 -60
29/11/2012 05.00 15 175 -104
29/11/2012 06.00 16 150 -146
29/11/2012 07.00 16 150 -146
29/11/2012 08.00 16 150 -149
29/11/2012 09.00 16 150 -113
29/11/2012 10.00 16 150 -60
29/11/2012 11.00 16 150 -60
29/11/2012 12.00 16 150 -64
29/11/2012 13.00 17 125 -135
29/11/2012 14.00 17 125 -120
29/11/2012 15.00 17 125 -61
29/11/2012 16.00 18 100 -120
29/11/2012 17.00 19 75 -150
29/11/2012 18.00 18 100 -113
29/11/2012 19.00 18 100 -90
29/11/2012 20.00 18 100 -150
29/11/2012 21.00 17 125 -60
29/11/2012 22.00 17 125 -60
29/11/2012 23.00 18 100 -101
The offer is emulated to be accepted as submitted. An outtake of the physical delivery of the
contracted volume is depicted in Figure 17.
Figure 17 shows the delivery of the optimized loadplan from 00.00-08.00. Furesø water supply station
has certain energy limits that have to be respected. The figure below includes the energy level and
the maximum energy level of the water reservoirs. The maximum energy level represents the
maximum amount of water that can be pumped into the reservoirs.
Practically this means that it is beneficial to pump water into the reservoirs before a price peak is
expected, so that the pumps can be inactive during the highly priced hours.

It is shown that the metered current power consumption of the station is following the setpoint closely
most of the time and hence delivering the contracted baseload volume from the day-ahead spot
market.
Between 05,00-07.00 the setpoint is deviating slightly from the contracted day-ahead baseload. This
is because the energy level is close to its maximum and therefore not much more water should be
pumped into the reservoirs. Consequently, the setpoint is adjusted down compared to the contracted
baseload and the station is not consuming as much as it was forecasted day-ahead. Eventually, the
contracted baseload volume is delivered more precisely from 08.00 again.
Figure 17: Delivery of load shifting.
3.1.5 Conclusion
This demonstration shows that Power Hub can offer and deliver its flexibility to all different existing
Danish power markets.
Some markets were emulated mostly because the minimum offer requirements for participating in
those markets cannot be matched at the moment. However, Power Hub is able to deliver the
contracted services technically with a low amount of units. As Power Hub’s portfolio increases, the
minimum requirements will be matched eventually.
3.1.6 Perspectives
The demand for Balancing Services, such as Ancillary Services and Intraday trading is expected to
increase significantly in the future, mainly due to an increased share of intermittent renewable energy
production. Hence, there will be an increased demand for utilising flexibility. Power Hub can enable
units to monetarise the unit’s flexibility via market participation.
The harmonisation of balancing market rules and its technical specifications on a pan-European level
will ease cross-border trading on those markets. Power Hub’s upscaling potential on a European level
will hence increase, since market participation and access to bigger market volumes will be facilitated.

3.2 VPP platform that maximises the value of the flexibility in the local units
3.2.1 Purpose
The purpose of this demonstration is to show that Power Hub can maximise the income from power
markets through an economical optimisation of market prices and the available flexibility of Power
Hub’s portfolio.
The demonstration ‘VPP platform with diversified offerings’ shows that local units from Power Hub’s
portfolio offer their flexibility to the power markets. Power Hub can additionally optimise the portfolio’s
flexibility cost-effectively towards different markets. The optimisation is based on market price
forecasts and the availability of assets in the portfolio.
3.2.2 Scope
Within the scope of this demonstration, we show that Power Hub is able to optimise the load schedule
of its portfolio towards different Danish power markets. This includes two main activities:
 Optimise a single unit towards several power markets
o Show that a unit can optimise between different day-ahead and intraday markets and
maximise the income generated by the unit based on market forecasts
o Show that optimised load plans are generated for the unit
 Optimise a portfolio of units towards several markets.
o Show that a portfolio of units can optimise between different day-ahead and intraday
markets and maximise the income based on market forecasts
o Show that optimised load plans are generated for the units in the portfolio
The relevant power markets for this demonstration are described in 1.1 The Nordic electricity market.
There is no contractual business set up with the unit owners for optimising towards those markets yet.
In order to show the capabilities of Power Hub’s optimisation process, the markets and units are
emulated. The actual delivery of services is not within the scope of this demonstration, but was shown
in the demonstration ‘VPP with diversified offerings’.
3.2.3 Set up
The setup is the implemented system architecture within the Power Hub User Interface. For this
demonstration the setup is as following:
1. Power Hub extracts ability forecasts that describe the technical capabilities of the emulated
local units
2. Power Hub extracts market price forecasts
3. Power Hub generates market offers based on the forecasts and sends market offers to
emulated markets
4. Power Hub receives market feedback via market contract
5. Power Hub generates an optimised loadplan to schedule the delivery of contracted volume
In this section, the markets are usually considered in 1-hour blocks. However, the emulated PR
market setup only allows block offers. This means that the unit can only make offers in 4-hour blocks
from 00.00-04.00, 04.00-8.00, 08.00-12.00, 12.00-16.00, 16.00-20.00, 20.00-24.00 and must uphold
the reserve continuously in the respective blocks. This market setup is currently used in Western
Denmark.

Emulated
Local Unit 1
Emulated
Local Unit 2
Power Hub
Emulated
Market
1. Ability forecast
1. Ability forecast
2. Market price
forecasts
3. Market offer
4. Market contract
5. Optimised
loadplan
5. Optimisedloadplan
Figure 18: Demonstration setup
3.2.4 Log and Results
This section describes the specific test activities and results. The test cases are performed on Power
Hub’s test environment in order to use the relevant emulators for markets and units.
Demo Case 1 and 2 show an optimisation of one local unit towards the day-ahead baseload market
and the Primary Reserve (PR) market.
In Demo Case 3, it is shown that a local unit’s offer is rejected and an offer to an alternative market is
submitted after a re-optimisation.
In Demo Case 4, price forecasts of the baseload and PR market are evaluated and a single local unit
is optimised and scheduled according to the market attractiveness.
Demo Case 5 demonstrates that two local units that cannot offer into the PR up market individually,
can be optimised in a way to make an offer together as being part of a portfolio.
Demo Cases 6 and 7 show that a portfolio of two local units can deliver the contracted volume in a
cost-efficient way. Power Hub optimises its portfolio so that the unit with the lowest marginal
production costs delivers first.
Demo Case 1
This case shows an optimisation between the day-ahead baseload market and the Primary Reserve
market. Primary Reserves (PR) is an automatically regulated reserve to keep the balance in the grid
by keeping the grid frequency close to 50Hz. There are two products available, up- and down-
regulation. The gate closure for PR is set to be after gate closure for the baseload market.
The optimisation is demonstrated with an emulation of Tangeværket hydro plant on 16.11.2012.
The marginal price for producing one MWh of power is DKK 600. According to the unit’s ability
forecast in the table below, Tangeværket must run on a minimum load of 900kW and can deliver up to
1400kW during the whole day.
Table 33: Ability Forecast for Tangeværket for Case 1.
Timestamp
16/11/2012 00.00 900 1400
The assumption is that the Primary Reserve up-price forecast is more attractive than the baseload
price forecast. The price forecast is a very rough estimate to illustrate the attractiveness of the market.

The actual PR prices are much lower than our forecasts. As a result, the unit’s Baseload plan will be
on its minimum load and the PR up reservation is maximised.
The price forecasts for Baseload and PR are shown in the table below.
Table 34: Price forecast for Baseload and PR for case 1.
Timestamp
(local time)
Baseload
DKK/[MWh/h]
PR down
DKK/[MW]
PR up
DKK/[MW]
16/11/2012 00.00 228 0 5000
16/11/2012 01.00 227 0 5000
16/11/2012 02.00 226 0 5000
16/11/2012 03.00 236 0 5000
16/11/2012 04.00 245 0 5000
16/11/2012 05.00 258 0 5000
16/11/2012 06.00 364 0 5000
16/11/2012 07.00 374 0 5000
16/11/2012 08.00 369 0 5000
16/11/2012 09.00 351 0 5000
16/11/2012 10.00 335 0 5000
16/11/2012 11.00 330 0 5000
16/11/2012 12.00 328 0 5000
16/11/2012 13.00 274 0 5000
16/11/2012 14.00 273 0 5000
16/11/2012 15.00 284 0 5000
16/11/2012 16.00 394 0 5000
16/11/2012 17.00 290 0 5000
16/11/2012 18.00 272 0 5000
16/11/2012 19.00 255 0 5000
16/11/2012 20.00 253 0 5000
16/11/2012 21.00 247 0 5000
16/11/2012 22.00 242 0 5000
16/11/2012 23.00 243 0 5000
Power Hub generates Tangeværket’s market offer for Baseload and PR based on the forecasts
above. The offers are sent to the markets before gate closure. In this case, the emulated markets
accept the market offer. The contracted volumes are therefore identical to the market offer.
Table 35 shows the loadplan for Tangeværket after the optimisation. The unit is scheduled to run on
the forced minimum load. Furthermore, the unit offers 500KW/h PR up during the whole day, since
prices for PR up are forecasted to be high. The unit stays within its ability limits as defined in Table 6.

Table 35: Loadplan for Case 1.
Timestamp
(local time)
Offer
Baseload
[kWh/h]
Offer PR down
[kW]
Offer PR up
[kW]
16/11/2012 00.00 900 0 500
16/11/2012 01.00 900 0 500
16/11/2012 02.00 900 0 500
16/11/2012 03.00 900 0 500
16/11/2012 04.00 900 0 500
16/11/2012 05.00 900 0 500
16/11/2012 06.00 900 0 500
16/11/2012 07.00 900 0 500
16/11/2012 08.00 900 0 500
16/11/2012 09.00 900 0 500
16/11/2012 10.00 900 0 500
16/11/2012 11.00 900 0 500
16/11/2012 12.00 900 0 500
16/11/2012 13.00 900 0 500
16/11/2012 14.00 900 0 500
16/11/2012 15.00 900 0 500
16/11/2012 16.00 900 0 500
16/11/2012 17.00 900 0 500
16/11/2012 18.00 900 0 500
16/11/2012 19.00 900 0 500
16/11/2012 20.00 900 0 500
16/11/2012 21.00 900 0 500
16/11/2012 22.00 900 0 500
16/11/2012 23.00 900 0 500
Demo Case 2
Case 2 shows another optimisation of Tangeværket towards the Baseload and Primary Reserve
market. The main difference from Case 1 is that the optimisation is allowed to shut down the unit, if it
is not beneficial to run it. Although, the baseload price forecast is below the marginal price for
producing power, Power Hub’s optimisation will keep the unit running to have an opportunity to bid on
PR up market.
The Baseload price forecast is the same as in Table 34. The marginal price for producing one MWh of
power is DKK 600. The ability forecast in Table 36 shows that Tangeværket can choose not to run
(Pmin=0). If the unit is scheduled to run it still needs to run on a minimum load of 900kW.
Timestamp
(Local Time)
Pmin
[kW]
Pmax
[kW]
16/11/2012 00.00 0 1400

The loadplan is optimised and Power Hub generates market offers. The market accepts the offers and
therefore the contracted volumes are the same as the market offer.
The loadplan below shows that the unit is scheduled to deliver 900kWh/h during the whole day
although baseload price is below marginal production price. The unit has to run though to be available
to uphold PR up which is commercially very attractive.
Table 37: Loadplan for Case 2.
Timestamp
(local time)
Offer Baseload
[kWh/h]
Offer PR down
[kW]
Offer PR up
[kW]
16/11/2012 00.00 900 0 500
16/11/2012 01.00 900 0 500
16/11/2012 02.00 900 0 500
16/11/2012 03.00 900 0 500
16/11/2012 04.00 900 0 500
16/11/2012 05.00 900 0 500
16/11/2012 06.00 900 0 500
16/11/2012 07.00 900 0 500
16/11/2012 08.00 900 0 500
16/11/2012 09.00 900 0 500
16/11/2012 10.00 900 0 500
16/11/2012 11.00 900 0 500
16/11/2012 12.00 900 0 500
16/11/2012 13.00 900 0 500
16/11/2012 14.00 900 0 500
16/11/2012 15.00 900 0 500
16/11/2012 16.00 900 0 500
16/11/2012 17.00 900 0 500
16/11/2012 18.00 900 0 500
16/11/2012 19.00 900 0 500
16/11/2012 20.00 900 0 500
16/11/2012 21.00 900 0 500
16/11/2012 22.00 900 0 500
16/11/2012 23.00 900 0 500
Demo Case 3
This case shows that the PR price forecast is attractive to make an offer, the offer gets rejected
though. This opens up another opportunity to make an offer on a different market, eg intraday market.
Timestamp
(Local Time)
Pmin
[kW]
Pmax
[kW]
16/11/2012 00.00 900 1400
The marginal price for producing power is 600 DKK/MWh. The price forecasts for the markets are
depicted in Table 39. The PR up price is the highest while Intraday price forecast is higher than the

marginal production price during the whole day.
Table 39: Price forecast for Baseload, PR and Intraday for Case 3.
Timestamp
(local time)
Baseload
DKK/[MWh/h]
PR down
DKK/[MW]
PR up
DKK/[MW]
Intraday
DKK/[MWh/h]
21/11/2012 00.00 228 0 5000 700
21/11/2012 01.00 227 0 5000 700
21/11/2012 02.00 226 0 5000 700
21/11/2012 03.00 236 0 5000 700
21/11/2012 04.00 245 0 5000 700
21/11/2012 05.00 258 0 5000 700
21/11/2012 06.00 364 0 5000 700
21/11/2012 07.00 374 0 5000 700
21/11/2012 08.00 369 0 5000 700
21/11/2012 09.00 351 0 5000 700
21/11/2012 10.00 335 0 5000 700
21/11/2012 11.00 330 0 5000 700
21/11/2012 12.00 328 0 5000 700
21/11/2012 13.00 274 0 5000 700
21/11/2012 14.00 273 0 5000 700
21/11/2012 15.00 284 0 5000 700
21/11/2012 16.00 394 0 5000 700
21/11/2012 17.00 290 0 5000 700
21/11/2012 18.00 272 0 5000 700
21/11/2012 19.00 255 0 5000 700
21/11/2012 20.00 253 0 5000 700
21/11/2012 21.00 247 0 5000 700
21/11/2012 22.00 242 0 5000 700
21/11/2012 23.00 243 0 5000 700
The optimisation results in a market offer for Baseload and PR. We emulate the PR up market not to
accept the provided PR up offer, hence the market contract for PR up is zero. The leaves a volume
from the PR bid, which can be placed on Intraday market as shown in Table 41.
In this specific demonstration, the unit is forced to run with a minimum load. But even if the
optimisation could stop the unit, the gate closure of the spot market is prior to the offer on the primary
reserve market. Therefore, when the offer was rejected on the PR up market, the unit still had to run
at 900kW throughout the day, since that amount was already sold. Thus leaving only the rejected
amount of PR reserve available to the intraday market. Of course allowing the unit to stop, would
enable the optimisation to buy 900kW on the intraday market and shut down the unit instead. The
choice of buying the obligation to deliver 900kWh per hour would only be made if the intraday prices
are lower than the production cost. This is not the case in this specific case.
Intraday markets generally provide continuous power trading 24 hours a day, seven days a week,
covering individual hours, up to one hour prior to delivery. The traded products are normally one-hour
long power contracts. Power Hub chooses to place the offer at the first available opportunity, which is
the hour between 00.00-01.00. The Intraday offer for the respective hour is emulated to be accepted.

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Twenties deliverable 10.3 Providing flexibility with a virtual power plant

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