1.
Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
Decentralised Capacity-Support for
Distribution Networks: The Economics of
Distributed Energy Resources
24th November 2003
Industrial Research Limited
PO Box 20028, Bishopdale
Christchurch 8001
New Zealand
Tel: +64-3-358-6802
Fax: +64-3-358-9506
Email: i.sanders@irl.cri.nz
Web address: http://www.irl.cri.nz
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Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
Contents
Page Section Heading
3 Glossary
4 Abstract
5 Terms of Reference
6 Acknowledgements
7 Summary
8 Introduction
11 Scenarios Examined
13 Distributed Generation Operating Scenarios
17 MCLM Operating Scenario
21 IPP Operating Scenario
24 Other Potential Benefits Available from these Technology Combinations
Scenarios
25 Resource Inputs
26 Main Results of the Scenarios
36 Further Discussion of Results
40 Conclusions
44 References
45 Appendix One: Key Assumptions
46 Appendix Two: MGB Model Terms and Conditions
55 Appendix Three: IDES Simulation Modelling Capability
61 Appendix Four: Capacity Metering for General Customers
69 Appendix Five: Legislative Frameworks for DG Facilitation
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Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
Glossary
AC Assessed Capacity
BDG Biodiesel Generator / Genset
BDG-WTG Biodiesel-Wind Hybrid
CHP Combined Heat and Power
CPD Control Period Demand
DE Distributed Energy
DE(R) Distributed Energy (Resources)
DG Diesel Generator / Genset
DG-WTG Diesel-Wind Hybrid
EGB Electricity Governance Board
FRST Foundation for Research, Science and Technology
GCLM General Customer Load Management / Manager
GHG Green House Gas
GXP Grid Exit Point
IDES Integrated Distributed Energy Systems / Solutions
IPP Independent Power Production / Producer
IRR Internal Rate of Return
MARIA Metering And Reconciliation Information Agreement
MCLM Major Customer Load Management / Manager
MGB Maria Governance Board
MORST Ministry of Research, Science and Technology
MTCCDG Model Terms and Conditions for Connection of Distributed Generation
NPV Net Present Value
PPD Peak Period Demand
RDE Renewable Distributed Energy
ROI Return On Investment
TOU Time Of Use
WTG Wind Turbine Generator
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Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
Abstract
This report describes some of the opportunities identified by Industrial Research for
investing in distributed generation technologies under existing electricity market
arrangements. Some adjustments to existing market practices to produce a “more level
playing field” for distributed generation are recommended.
In particular we demonstrate the importance of supply capacity in the economics of
distributed generation.
The delivery of capacity and fair reward from network operators to the providers of this
service at all levels is key to the viability of distributed energy technologies in a network
environment.
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Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
Terms of Reference
The New Zealand Foundation for Research, Science and Technology (FRST) is funding a
program of research to evaluate and demonstrate opportunities for Renewable Distributed
Energy (RDE) technologies in New Zealand. The study on which this report is based was
undertaken under this program (FRST Contract Number: CO8X0203).
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Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
Acknowledgements:
This report is largely the work of Industrial Research Limited staff but we would like to
acknowledge the practical support and advice particularly from Orion Networks staff and
local technology developers.
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Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
Summary
S1. New Zealand needs to implement both sustainable generation technologies and
sustainable network management practices. Hybrid generation systems involve the
combination of two or more conversion technologies, for instance a diesel generator
set and a renewable energy photovoltaic collector system. This approach is now
well proven in the remote area market where the cost of energy is high. A network
connected combination that provides local energy and capacity could have wider
application in providing solutions to weak grid and other distribution system
constraints, as well as achieving the desirable goal of delivering substantial energy
from sustainable resources.
S2. This report shows results of an analysis of the costs of grid-connected mini-scale
(550kW) wind, diesel and hybrid diesel-wind generator systems. It is shown that
valuation of the capacity supplied by a hybrid system under present energy and
capacity pricing regimes, can be cost-effective in many regions with specific peak
demand or capacity constraints. As grid-sourced electricity costs rise, the diesel-
wind hybrid combination can become economic in regions with lower wind speeds,
but only if the market rewards the value of the capacity delivered.
S3. Our analysis shows that the electricity delivery price schedule proposed by Orion
New Zealand Limited for major customer connections and embedded generation
significantly improves the financial viability of grid-connected mini-scale wind-
diesel hybrid generation in the Canterbury region, where sufficient wind energy
regimes exist, or where capacity-support requirements are restricted to no more than
several hundred hours per year. Furthermore, the network company benefits from
targeted grid-connected Renewable Distributed Energy (RDE) sites might easily
surpass the benefits captured by independent network users.
S4. Wind-diesel hybrid distributed generation currently offers the best combination in
modest to high wind areas for spreading the risk of alternative energy supply.
S5. The New Zealand supply industry has enjoyed a number of years in an environment
where they make the rules. This has not led to a favourable environment for
distributed generation. It is imperative that other network operators and retailers in
New Zealand follow and challenge the lead taken by Orion Networks in offering
rewards for network support. If a common set of principles for fair payment is not
quickly adopted voluntarily by supply authorities throughout the country, regulation
to force fair practice is the only alternative.
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Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
Introduction
1. For the last five years, Industrial Research has been evaluating a wide range of
resource opportunities for adopting Renewable Distributed Energy (RDE)
technologies in New Zealand. The objective has been to demonstrate the techno-
economic viability of micro- (less than 100kW capacity), mini- (between 100kW
and 1000kW capacity) and small-scale (between 1MW and 10MW capacity) RDE
systems in New Zealand. In the process specialised tools and methodologies have
been developed to fulfil this purpose. (Unless ‘scale’ is specifically mentioned, the
term ‘small’ will refer to anything from micro-scale to small-scale inclusive).
2. Our research to introduce distributed energy-based systems has been motivated by
the promise of more efficient energy utilisation and the opportunity for capturing
local renewable energy resources with minimal use of additional infrastructure.
This is possible through:
I. Local generation solutions that relieve distribution network capacity while
maintaining utilisation.
II. Technology that will provide alternatives to uneconomic network sections.
III. Creating the means for large numbers of small distributed generators to export
individually modest quantities of electricity from otherwise uneconomic
network assets to different network users.
IV. Ability to track slow growth in demand with small matching incremental steps
in generation, thus avoiding or delaying major upgrades.
These potential network benefits contrast with the more popular view that
distributed generation threatens the traditional electricity supply infrastructure by
taking away energy delivery but not alleviating capacity demands.
3. In the main, small-scale technology developers have been preoccupied with
reducing the costs of their own particular product in the high volume micro- / mini-
scale embedded generation marketplace. Unfortunately, no single technology can
yet provide the quality of service delivered by the distribution network, at the
distribution network price. For example, a wind generator cannot guarantee firm
capacity, so the network must provide this; and, while a diesel genset can deliver
capacity the cost of energy from a diesel genset is generally too high, so it is
relegated to a standby function. This report evaluates the ability of these two
technologies to deliver matching energy and firm capacity to complement grid
based electricity services.
4. A network connected electricity user can potentially save money by either reducing
energy consumed or by restricting the demand on power capacity for the few hours
of the year when the network ability to deliver the capacity demanded is under
stress. In the latter case, because the invested capacity of the whole delivery
infrastructure is at stake, the cost savings can be substantial. The cost of capacity to
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Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
supply power (measured in kVA) is often not appreciated – it ranges from around
one to over 10 times the cost of actual grid energy delivered (measured in kWh).
5. If the financial instruments are in place to reward the network user for releasing
capacity (e.g. via customer load management) or supplying capacity (e.g. via
network-embedded generation) when and where it is required, the benefits may be
substantial. Embedded generation can extend to injecting both active and reactive
power into the network (i.e. capacity support through distributed generation). The
capacity value of active power is higher than reactive power. Reactive power has
no energy value, i.e. it can do no work, but because it can be used in the distribution
system to maintain conditions for power flow, it is worth paying for at times of
system stress.
6. A previous publication by Industrial Research Limited has shown that a mix of
renewable and dispatchable Distributed Energy Resources (DER) can potentially
provide energy and capacity at a reasonable cost, compared with the cost of
investing in new assets or upgrading existing infrastructure1. This study extends
these principles to show that in some circumstances the wind-diesel genset
combination can provide good returns, not only as an alternative to upgrades but
also as a third party investment based on current supply industry contract pricing
structures.
7. Because of the scale and case-specific conditions that apply to these projects, easily
implemented but accurate costing of each project is required. Most of the DER
techno-economic evaluation tools available today, are either too specialised (very
detailed but narrowly focused – leaving out most of the strategic decision-making
process and alternative solutions available), or too broad (providing global coverage
but insufficient detail – leaving out most of the tactical decision-making process
and data critical for providing optimum solutions) to evaluate micro- to small-scale
renewable generation opportunities2. We have developed the tools and methods to
address these techno-economic evaluation shortfalls, and applied them to
“Integrated Distributed Energy Systems” or IDES scenarios outlined in this report3.
8. Our analysis shows that micro- and mini-scale “own-use” wind energy is not
generally financially viable under existing market conditions in New Zealand.4 The
smaller the wind turbine, the less viable grid connection becomes. These results
can be reversed if in addition to energy income, payment can be gained from
guaranteeing capacity-support to a local load or to the distribution network during
designated “Peak” and / or “Control” Period Demand (PPD and CPD
respectively5,6) The easiest way to do this is to add a diesel genset or similar
dispatchable generator to the distributed generation mix. The analysis in this report
simply uses the genset to complement the available wind generation and deliver a
fixed level of capacity support during network peak demand periods. There are
other modes of operation, including the provision of standby power and generating
at times of high prices that could add further value. The application of the
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Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
technology combination is restricted to rural areas, with at least modest wind
regimes.
9. An Integrated Distributed Energy System is a distributed electrical energy system
which uses local energy resources to help deliver local services, and is connected in
parallel to a conventional supply (which may be a grid supplied distribution system,
or a diesel genset etc. It may include electrical generation and heat capture, and
electrical and heat storage. The four key characteristics of IDES are that they are:
œ Integrated – embedding combinations of energy supply technologies
(including non-electrical options) within existing infrastructure.
œ Distributed – matching micro- to small-scale supply and use (<10MW / site).
œ Energy driven – providing power and heat and storage as required.
œ Systems providing solutions – delivering energy services that are sustainable,
reliable and at an acceptable cost.
These applications are fully detailed in the “ IDES-Introduction” Report and the
“ IDES-Overview” Presentation3. A summary of the IDES Simulation modelling
capability is given in appendix three.
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Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
Scenarios Examined
10. The network supplies both energy and capacity in delivering an energy service to a
customer. A local generator can potentially offer both of these functions, but will
only do so if the rewards are adequate. Obviously, the combined financial return
from these two components of service is potentially higher than simply the delivery
of energy alone, with no time constraints.
11. A large number of different hybrid Distributed Energy (DE) system sizes and
environments have been modelled using the IDES tools and methodologies. This
report describes just one detailed study of a 550kW Westwind-550 Wind Turbine
Generator (WTG) and a 550kW Diesel Generator (DG) for deployment within the
Orion network region of New Zealand.
12. The economic assessment presented uses actual capacity pricing schedules that
Orion has / or is proposing to make available to its major customers and network-
embedded DE operators5. Typical energy pricing schedules available to major
customers (energy users) are used to model realistic market conditions. An analysis
of the Net Present Value (NPV), Internal Rate of return (IRR), Return on
Investment (ROI), payback period and the equivalent cost / revenue over lifetime in
$ / kWh electricity generated was undertaken.
13. Financial results were compared for average annual wind speeds of 5, 7 and 9 m/s,
using 10-minute average wind data. A comparison was made between releasing
capacity from the network (DE operating as a Major Customer Load Manager7, i.e.
MCLM Operating Scenario), and supplying capacity to the network (DE operating
as an Independent Power Producer, i.e. IPP Operating Scenario).
14. Under the first scenario, the MCLM used locally on site all the energy and capacity
produced to reduce an actual load (so that both the energy bought from the energy
retailer and the capacity required from the distribution network were reduced); and
under the second, the IPP exported all the energy and capacity produced to the local
distribution network (so that all the energy produced was purchased by the energy
retailer, and all the capacity delivered over defined periods was purchased by the
distribution network). Although the net impact on energy flows is identical, at
present the supply industry treats these two scenarios quite differently.
15. These two scenarios are selected as representing opposite ends of the spectrum for
DE deployment. A combination of these scenarios exists for a wide range of DE
applications, where the system functions either as a net-importer or a net-exporter
of energy and / or capacity-support. The MCLM and IPP Operating Scenarios
compare the economic and technical performance of the following DE systems (see
figures 1 and 2 respectively):
A. 550kW Wind Turbine Generator by itself, WTG-Only ($2,725 / kW over life);
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Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
B. 550kW Combined Diesel-Wind Turbine Generator Hybrid, DG-WTG Hybrid;
C. 550kW Diesel Generator by itself, DG-Only ($399 / kW over life without
fuel).
DISTRIBUTION NETWORK DISTRIBUTION NETWORK DISTRIBUTION NETWORK
CUSTOMER CUSTOMER CUSTOMER
LOAD LOAD LOAD
DIESEL DIESEL
GENSET GENSET
A. WTG ONLY MCLM B. DG-WTG HYBRID MCLM C. DG ONLY MCLM
Figure 1: WTG-Only, DG-WTG Hybrid & DG-Only Major Customer Load Management (MCLM) Operating Scenarios
DISTRIBUTION NETWORK DISTRIBUTION NETWORK DISTRIBUTION NETWORK
DIESEL DIESEL
GENSET GENSET
A. WTG ONLY IPP B. DG-WTG HYBRID IPP C. DG ONLY IPP
Figure 2: WTG-Only, DG-WTG Hybrid & DG-Only Independent Power Production (IPP) Operating Scenarios
16. Under the IPP operating regimes illustrated in figure 2, it is assumed that the energy
associated with running and maintaining the IPP facility itself is negligible. A more
detailed list of assumptions used to evaluate the IPP and MCLM operating
scenarios is provided in appendix one. The key results are shown in the “ Main
Results of the Scenarios” section of this report.
17. The next three sections summarise the energy and capacity payment options
assumed to be available.
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Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
Distributed Generation Operating Scenarios
Major Customers: A Distribution Network Definition
18. The MCLM scenario is only relevant to “ major customers” who are charged
according to Time-Of-Use (TOU) capacity taken from the network. According to
Orion’ s “ Electricity Delivery Pricing for Major Customer Connections” (Issue
three, 31Jan 2003), any connection may be classified as a “ Major Customer
Connection” , as long as charges are paid according to the basis given in Orion’ s
“ Electricity Delivery Price Schedule for Major Customer Connections” . In
particular, a “ Minimum Assessed Capacity” of 300kVA is chargeable (as a major
customer). “ The calculated Assessed Capacity (AC) of a connection is the average
of the 12 highest half-hourly kVA demands from those occurring on working
weekdays between 7.30am and 8.30pm (i.e. half hours ending 8.00am and 8.30pm),
during (the previous) 12-month period as long as the average of the 12 highest
anytime half-hourly kVA demands is not greater by more than 20% of this value” 7.
The figure for AC that is put in place at the start of the season (e.g. on the 1st
October for Zone A Winter-based connections) is applied on all invoices through to
30th September of the following year. The twelve highest demands that are
recorded during this twelve-month billing period are then used to determine the AC
value that will be in place from 1st October of the following year. The AC value is
apportioned on a daily basis over the 12-month period. “ If the average of the 12
highest half-hourly kVA demands measured at any time during the 12-month period
exceeds the “ Calculated AC” by more than 20%, then specific consideration will be
given with regard to the implications on Orion’ s network investment and Orion will
negotiate an appropriate “ Adjusted AC” with the Contracted Party” 7.
19. From a distribution network perspective, major customers are typically energy users
not requiring the use of the 400V distribution network infrastructure. Customers
connected to the 400V distribution network are typically referred to as general
customers, and they normally include all domestic energy users and most small to
medium sized commercial energy users. This level of energy delivery service is
significantly more expensive to provide than that used by major users (typically
large commercial and industrial energy users) who are connected to the distribution
network directly at 11kV for example5. This study does not evaluate the potential
of distributed energy capacity support to the network by general customers, but a
further report in 2003, entitled “The Economics of Micro-Scale Embedded Wind-
Diesel Generation” will do so.
Major Customers: An Energy Retailer Definition
20. From an energy retailer’ s perspective, a major customer is typically one that has
Time-Of-Use (TOU) metering. A TOU meter records energy in half-hourly
intervals (the intervals in which it is bought and sold in the wholesale market).
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Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
Meridian Energy’ s major customers typically spend over $30,000 per site, per year,
on total electricity costs8.
Major Customers: Energy and Capacity
21. Meridian Energy will charge major customers either by a TOU price related to a
fixed or variable energy purchase volume contract (of typically one to three years
duration), or will charge the wholesale spot price (plus some administration charge)
related to the actual half-hourly electricity wholesale energy market price. Orion
New Zealand Limited will charge major customers for capacity: (a) during a
specified demand period, known as a “ Control Period Demand” (CPD); and, (b) at
anytime for an “ Assessed Capacity” (AC). CPD and AC charges are priced in $ /
kVA / year.
General Customers: Energy and Capacity Charges
22. Meridian Energy will typically charge general customers a domestic and / or
commercial tariff that may / may not be affected by the time the electricity is used
(depending on the tariff(s) selected by the customer). Orion New Zealand Limited
will charge the Retailer for their general customers for an estimate of the capacity
they used during the specified demand period, known as a “ Peak Period Demand”
(PPD). This estimate is subsequently washed up on the Retailer invoices when the
actual Retailer peak is known at the end of the season. This peak demand charge is
re-priced by the Retailer as part of the Retailer bundled energy charge. For
example, a price of 12.86 cents / unit (kWh) for a residential customer of Meridian
is such a bundled charge. The government has imposed an arbitrary cap on the
fixed charge component that a network company can charge domestic customers for
their share of the PPD cost. If this fixed charge component exceeds the 10% cap,
then some of the PPD capacity cost is transferred to a variable charge based on
average energy use.
Major Customers as Generators: Energy and Capacity Payments
23. Energy retailers (for example Meridian Energy), will typically buy energy from
major customers at a TOU price that is either: (a) directly related to the wholesale
market spot price, or (b) a fixed / variable energy volume pricing contract. Orion
New Zealand Limited is willing to pay network-embedded generators for providing
capacity during the PPD time periods (see later for an explanation), whether or not
they are operating as major customer connections5. This payment will include real
and reactive power support.
General Customers as Generators: Energy and Capacity Payments
24. We (the authors) are not directly aware of any contractual arrangements / legal
prerequisites, obliging energy retailers to purchase electricity from an embedded
generator operated by a general customer (but net metering is an option in this
case). General customers without TOU metering will require alternative energy and
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Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
capacity monitoring arrangements to reconcile costs with payments for the
distribution and transmission networks, the energy retailer and the general
customer. Orion New Zealand Limited (as indicated above) will make payments to
Retailers (since Orion does not have contractual arrangements with General
Customers) for passing on to General Customers for providing capacity during the
PPD5 via network-embedded generation. This payment will include real and
reactive power support. Energy supplied by a generator will have to be bought by
an energy retailer at a pre-determined price or under a pre-determined contractual
arrangement.
25. Net-metering is the practice of using bi-directional metering to measure
consumption and generation of electricity by a small generation facility (such as a
house with a wind or solar photovoltaic system). The energy produced or consumed
is purchased from or sold to the facility at the same price. Metering using a
reversible meter, has been advocated as a low cost means of accounting for net
purchases / sales by small consumers, using appropriate energy / capacity profiles
fitting the electricity delivery schedule as a basis for determining costs and
payments5. The disadvantage of using such a method is that it cannot account for
different TOU energy costs or for capacity support, and so we do not see this
approach as adequate. (For metering exported energy at any level, we recommend
the minimum installation should be a two-rate meter, switchable by ripple control or
a similar control signal). The value of this approach is addressed in a further paper.
The Influence of Distributed Generation on Major Customers
26. In the next two sections we will describe the MCLM and IPP operating scenarios.
The MCLM operating scenario describes the impact of on-site distributed
generation on a major customer’ s energy consumption and capacity requirement
costs / savings. The IPP operating scenario describes the impact of energy
production and capacity delivery on a network-embedded generator’ s costs /
savings (the generator may or may not be owned by a major customer – but will be
considered here to be so – in order to describe contractual arrangements for selling
electricity to a retailer).
27. Options for embedded generation capacity payments to or from Orion are complex.
In the Orion network, there are three mechanisms: (1) Assessed Capacity (AC), (2)
Control Period Demand (CPD), and (3) Peak Period Demand (PPD). AC and CPD
apply to major customers only, operating under the MCLM scenario. The AC is
determined by the load (capacity) drawn at anytime by a major customer. Major
customers operate under either a summer (representing pre-dominantly rural loads)
or winter (representing predominantly urban loads) CPD regime, depending on their
location in the network. PPD is used to calculate line rental fees for general
customers, and to pay network-embedded generators operating under the IPP
scenario (whether they are classified as general or major customers). Embedded
generators also operate under either a summer or winter PPD regime, depending on
their location in the network. The different payment options for these two extremes
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Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
are summarised in figure 3 below. Note that in the GCLM / MCLM scenario,
embedded generation if present, does not export power so it simply modifies the
energy and capacity requirements of the load connections, as seen by the supply
system.
Customer Status Scenario Payment Options (Typical)
Line Rental Fee
(GCLM) Load
Management Single / Multiple Energy Tariff(s)
(may / may not be time-related)
General Customer (GC)
Connection Fee
(IPP) Peak Period Demand Pricing
Generation
TOU Energy Pricing or
Net-metering
Connection Fee
(MCLM) Load Assessed Capacity (AC) Pricing
Management
Control Period Demand (CPD)
Pricing
TOU Energy Pricing
Major Customer (MC)
Connection Fee
(IPP)
Generation Peak Period Demand (PPD)
Pricing
TOU Energy Pricing
Figure 3: Summary of Typical Payment Options for the Different Operating Scenarios
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Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
MCLM Operating Scenario
Energy Payment Options
28. Energy savings possible are simply determined from the energy wholesale pricing
schedule negotiated between the IPP or MCLM and the energy retailer. An energy
pricing schedule proposed by Meridian Energy was used in this study. This
schedule is shown in table 1 below. The average energy purchase price in this
schedule is 5.47 cents / kWh.
Table 1: Typical Wholesale Energy Pricing Schedule
PRICE SCHEDULE - Variable volume for 3 Years
Area: Christchurch
Customer: Industrial Research Ltd
Business Day Non-Business day
Month 0000-0330 0400-0730 0800-1130 1200-1530 1600-1930 2000-2330 0000-0330 0400-0730 0800-1130 1200-1530 1600-1930 2000-2330
Mar-03 3.55 4.51 6.72 6.10 5.79 5.06 3.92 3.40 4.78 4.30 4.25 4.14
Apr-03 3.56 4.51 6.73 6.10 5.79 5.06 3.92 3.41 4.79 4.30 4.25 4.14
May-03 4.62 5.37 7.10 6.11 7.59 6.21 4.86 3.48 4.98 4.42 6.25 4.86
Jun-03 5.16 6.00 7.93 6.83 8.48 6.93 5.42 3.89 5.56 4.94 6.98 5.43
Jul-03 5.00 5.81 7.67 6.61 8.21 6.71 5.25 3.76 5.38 4.78 6.76 5.26
Aug-03 4.91 5.71 7.54 6.50 8.07 6.60 5.16 3.70 5.29 4.70 6.64 5.17
Sep-03 4.22 4.91 6.49 5.59 6.94 5.68 4.44 3.18 4.55 4.04 5.72 4.45
Oct-03 3.45 4.38 6.53 5.92 5.62 4.92 3.81 3.31 4.65 4.18 4.13 4.02
Nov-03 2.75 3.49 5.21 4.72 4.48 3.92 3.03 2.64 3.70 3.33 3.29 3.21
Dec-03 2.50 3.17 4.72 4.28 4.07 3.56 2.75 2.39 3.36 3.02 2.98 2.91
Jan-04 2.67 3.38 5.04 4.57 4.34 3.80 2.94 2.55 3.59 3.22 3.18 3.11
Feb-04 3.12 3.95 5.90 5.34 5.07 4.44 3.44 2.99 4.19 3.77 3.72 3.63
Mar-04 3.96 5.02 7.48 6.78 6.44 5.63 4.36 3.79 5.32 4.78 4.73 4.61
Apr-04 3.96 5.02 7.49 6.79 6.44 5.64 4.36 3.79 5.33 4.79 4.73 4.61
May-04 5.14 5.98 7.90 6.80 8.45 6.91 5.40 3.87 5.54 4.92 6.95 5.41
Jun-04 5.74 6.68 8.82 7.60 9.44 7.71 6.04 4.32 6.19 5.50 7.77 6.05
Jul-04 5.56 6.46 8.54 7.35 9.13 7.47 5.84 4.19 5.99 5.32 7.52 5.85
Aug-04 5.46 6.35 8.39 7.23 8.98 7.34 5.74 4.11 5.89 5.23 7.39 5.75
Sep-04 4.70 5.47 7.22 6.22 7.73 6.32 4.94 3.54 5.07 4.50 6.36 4.95
Oct-04 3.84 4.87 7.27 6.59 6.26 5.47 4.24 3.68 5.17 4.65 4.59 4.48
Nov-04 3.06 3.89 5.79 5.25 4.99 4.36 3.38 2.93 4.12 3.70 3.66 3.57
Dec-04 2.78 3.52 5.26 4.76 4.52 3.96 3.06 2.66 3.74 3.36 3.32 3.24
Jan-05 2.97 3.76 5.61 5.09 4.83 4.22 3.27 2.84 3.99 3.59 3.54 3.46
Feb-05 3.47 4.40 6.56 5.95 5.65 4.94 3.82 3.32 4.67 4.19 4.14 4.04
Mar-05 4.22 5.36 7.99 7.25 6.88 6.02 4.66 4.05 5.69 5.11 5.05 4.92
Apr-05 4.23 5.36 8.00 7.25 6.88 6.02 4.66 4.05 5.69 5.11 5.05 4.92
May-05 5.49 6.39 8.43 7.27 9.02 7.38 5.77 4.14 5.92 5.26 7.43 5.78
Jun-05 6.13 7.13 9.42 8.12 10.08 8.24 6.45 4.62 6.61 5.87 8.30 6.46
Jul-05 5.94 6.90 9.12 7.86 9.76 7.98 6.24 4.47 6.40 5.68 8.03 6.25
Aug-05 5.84 6.79 8.96 7.72 9.59 7.84 6.13 4.39 6.29 5.59 7.89 6.14
Sep-05 5.02 5.84 7.71 6.64 8.25 6.75 5.28 3.78 5.41 4.81 6.79 5.29
Oct-05 4.10 5.21 7.76 7.04 6.68 5.84 4.52 3.93 5.52 4.96 4.90 4.78
Nov-05 3.27 4.15 6.19 5.61 5.33 4.66 3.61 3.13 4.40 3.96 3.91 3.81
Dec-05 2.97 3.77 5.61 5.09 4.83 4.23 3.27 2.84 3.99 3.59 3.55 3.46
Jan-06 3.17 4.02 5.99 5.43 5.16 4.51 3.49 3.04 4.26 3.83 3.79 3.69
Feb-06 3.70 4.70 7.01 6.35 6.03 5.28 4.08 3.55 4.99 4.48 4.43 4.32
4.17 5.06 7.11 6.30 6.83 5.77 4.49 3.55 5.03 4.49 5.33 4.62
5.87 Business Day (Average) 4.58 Non-Business Day (Average)
251 Days 5.471 Overall Average 114 Days
In this study, only the average wholesale energy price (5.47 cents / kWh) was used
in the simulations. (The IDES tools may be used however, to accommodate entire
pricing schedules like the one shown in table 1 above). The impact on the accuracy
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18.
Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
of the results from using only the average wholesale price in this study, was found
to be negligible for the energy pricing schedules used and distributed generation
scenarios evaluated.
Capacity Payment Options
29. There are several ways an MCLM may obtain savings for reducing capacity
demand from the distribution company. These will vary depending on the rules that
the distributor decides to apply6. For major customers on the Orion network,
capacity savings may be made by minimising peak demand at all times, based on
the Assessed Capacity (AC) pricing schedule, and in addition, more specifically
during the seasonal Control Period Demand (CPD)7. The CPD capacity for a major
customer is simply the average capacity drawn from the network during every
control period scheduled by the network company for a particular season
(depending on location, the customer operates under a winter or summer season
regime). In order to achieve maximum CPD capacity reduction savings, it is
necessary to schedule operation of embedded generation to coincide with every
CPD in the season. For general customers operating on the 400V distribution
network, CPD and AC benefits are not currently available.
30. CPD is used by Orion to determine the capacity cost contributions from major
customers for maintaining the distribution network and to encourage major
customer demand reductions at times of network constraint. A major customer
control period will be at least 15 minutes long and will be preceded by a 15 minute
warning sent by a ripple control signal. The overall financial advantage of
providing capacity-support during a CPD depends on the unpredictable duration of
CPD over the season.
31. Depending on their location in the network, customers operate under either a winter
or summer season CPD regime. During winter, because of the impact of heating
demand (which is temperature dependent), the load connected to the Islington,
Addington, Bromley and Papanui Grid Exit Points (GXPs) is managed through the
application of CPD. This is also known as the winter peaking zone (or zone A),
which is primarily urban and has significant industrial, commercial and residential
components to the load. During summer, because of the impact of rural irrigation
loads (which are rainfall and hydro-storage dependent), the load connected to the
Springston and Hororata GXPs is managed through the application of CPD. This is
also known as the summer peaking zone (or zone B), which is primarily rural and
has a significant irrigation pump component to the load.
32. Summer load management is between 1 November and end of February, and winter
load management is between 1 May to 31 August. Total seasonal duration of CPD
varies from a few minutes up to 150 hours5. Data for the past three summer and
nine winter CPD seasons was available for analysis. The duration of chargeable
major customer control periods over the past three seasons for the summer seasonal
CPD is shown in table 2 below. The duration of chargeable major customer control
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19.
Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
periods over the past nine seasons for the winter seasonal CPD is shown in table 3
below.
Table 2: Summer Control Period Demand for the Past Three Seasons
Chargeable Major Customer Control Periods
Season Control Period Covered Cumulative Duration
Summer 2000-01 1 Nov 00 – 28 Feb 01 81.1 Hours
Summer 2001-02 1 Nov 01 – 28 Feb 02 1.6 Hours
Summer 2002-03 1 Nov 02 – 28 Feb 03 31.4 Hours
Average over 3 years 2000-2003 Control Periods 38.0 Hours
Table 3: Winter Control Period Demand for the Past Nine Seasons
Chargeable Major Customer Control Periods
Season Control Period Covered Cumulative Duration
Winter 1994 1 May 94 – 31 Aug 94 61.1 Hours
Winter 1995 1 May 95 – 31 Aug 95 80.9 Hours
Winter 1996 1 May 96 – 31 Aug 96 52.1 Hours
Winter 1997 1 May 97 – 31 Aug 97 53.8 Hours
Winter 1998 1 May 98 – 31 Aug 98 9.6 Hours
Winter 1999 1 May 99 – 31 Aug 99 34.6 Hours
Winter 2000 1 May 00 – 31 Aug 00 20.0 Hours
Winter 2001 1 May 01 – 31 Aug 01 181.6 Hours
Winter 2002 1 May 02 – 31 Aug 02 111 Hours
Average over 9 years 1994-2002 Control Periods 67.2 Hours
33. Under Assessed Capacity (AC) charges, load management (which includes on-site
distributed generation) can also be used to reduce AC costs. The AC cost is
generally determined by the running average of the 12 highest half-hourly kVA
demands that have occurred between 7.30am and 8.30pm weekdays for a prior
fixed 12-month period. The pricing regime for major customers on the Orion
distribution network is shown in table 4 below5.
Table 4: Capacity Pricing Schedule for Major Customers in the Orion Network
Pricing Definition Line Transmission Delivery
Fixed (Connection) - $500.05 ----- - $500.05/year
Control Period Demand - $60.00 - $21.92 - $81.92/kVA/year
Assessed Capacity - $24.40 - $22.00 - $46.40/kVA/year
(A “-” sign is used to indicate payment from the customer).
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Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
34. Since AC is charged on the basis set out in paragraph 18, and apportioned on a daily
basis over a 12-month period, a control algorithm must attempt to keep all peaks
below a certain level to avoid AC costs creeping up, or attempt to clip demand
peaks to achieve a lower average. When the diesel genset is used to reduce
consumption, fuel is consumed at a cost higher than energy purchased from the
network. Therefore excessive use of the genset to reduce capacity charges will
result in negative overall savings. Customers who have taken measures to reduce
their Assessed Capacity – even after its value has been set for the next 12-month
period (see paragraph 18) – may still be able to make special arrangements with
Orion Networks Limited for their daily apportioned AC value to be modified
appropriately. CPD costs are charged on the average demand over all the control
periods in the season. If the cumulative duration of total clip times is long, it may
be more cost effective not to deliver full capacity at times to restrict diesel running
costs through increased efficiency and reduces fuel costs, and this introduces some
interesting profile dependent operating choices.
35. AC was calculated in this study before and after the impact of distributed
generation on a major customer’ s demand was considered. Using 12 months of
load profiling data from an experimental site, the impact of distributed generation
on lowering the highest AC demand peaks was determined. Our analysis showed
that – due to the shape of the load profile – by far the greatest cost-effective AC
reduction occurred by clipping only the four highest peaks in the year. AC cost
reduction gained by clipping more peaks was negligible. (In other words, an
uneconomic amount of diesel was involved with clipping additional peaks in order
to bring the AC cost down further).
36. The CPD schedule for the summer 2002-03 is given in table 5 below for reference.
Table 5: Duration of Chargeable Control Period Demand
for Major Customers during the Summer 2002-03 Season
CPD Date Start Time End Time CPD Duration
11 Feb 2003 11:00 11:17 17 mins
07 Jan 2003 20:03 01:46 343 mins
07 Jan 2003 18:09 19:36 87 mins
06 Jan 2003 17:56 00:49 413 mins
05 Jan 2003 00:22 00:57 35 mins
04 Jan 2003 23:24 23:39 15 mins
03 Jan 2003 23:23 01:07 104 mins
03 Jan 2003 22:03 22:49 46 mins
03 Jan 2003 18:04 19:33 89 mins
03 Jan 2003 00:23 01:09 46 mins
02 Jan 2003 23:26 23:44 18 mins
01 Jan 2003 00:26 01:09 43 mins
30 Dec 2002 23:29 23:52 23 mins
26 Nov 00:42 00:42 0 mins
2002
07 Nov 17:50 21:14 204 mins
2002
06 Nov 23:20 01:23 123 mins
2002
06 Nov 17:57 22:51 294 mins
2002
Total 31 Hrs 40 Minutes
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Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
IPP Operating Scenario
Energy Payment Options
37. An energy pricing schedule was proposed for use in this study (see table 1).
Meridian Energy agreed in principle to pay the energy prices given in the table 1
energy pricing schedule, less a 10% administration charge on all prices: for every
kWh of energy exported by a network-embedded generator at a major customer’ s
site. This of course means that for the IPP scenario, a return for energy of 10% less
than the MCLM case is available. The average energy export price under this
arrangement for the pricing schedule given in table 1, is 4.92 cents / kWh (5.47
cents / kWh, less 10%), and this figure was used in the study.
Capacity Payment Options
38. A pure IPP operator is not able to gain benefit from CPD and AC, because no
significant demand is taken from the distribution network. Depending on their
location in the network, network-embedded generators will operate under either a
winter or summer season PPD regime. As for the CPD, the summer PPD applies to
the predominantly rural portion of the network and the winter PPD applies to the
mostly urban portion of the network. However the PPD times are different from the
CPD periods discussed earlier (compare tables 5 and 9).
39. Summer PPD load management is between 1 October and 31 March, and winter
load management is between 1 April to 30 September. Total seasonal duration of
PPD is approximately two to three times the seasonal CPD duration, or up to
approx-imately 450 hours5. This means that to collect PPD payments, a generator
operating as an IPP must typically operate for 2 to 3 times as long as a generator
operating under MCLM, but as can be seen by comparison between tables 4 & 8,
the payments are substantially higher. Data for the past three summer and two
winter PPD seasons was available for analysis. The total duration of chargeable
half-hourly peak demand periods over the past three seasons for the summer
seasonal PPD are shown in table 6 below. The total duration of chargeable half-
hourly peak demand periods over the past two seasons for the winter seasonal PPD
are shown in table 7 below.
Table 6: Summer Peak Period Demand for the Past Three Seasons
Chargeable Peaks for Generator Capacity Pricing
Season Peak Period Covered Cumulative Duration
Summer 2000-01 1 Oct 00 – 31 Mar 01 307.5 Hours
Summer 2001-02 1 Oct 01 – 31 Mar 02 53 Hours
Summer 2002-03 1 Oct 02 – 31 Mar 03 108.5 Hours
Average over 3 years 2000-2003 Peak Periods 156.3 Hours
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Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
Table 7: Winter Peak Period Demand for the Past Two Seasons
Chargeable Peaks for Generator Capacity Pricing
Season Peak Period Covered Cumulative Duration
Winter 2001 1 Apr 01 – 30 Sep 01 318.5 Hours
Winter 2002 1 Apr 02 – 30 Sep 02 233 Hours
Average for 2 years 2001-2003 Peak Periods 275.8 Hours
40. The summer PPD tends to be less than the winter PPD, as borne out by the results
displayed in tables 6 and 7 for the past two or three seasons. Any fuel-driven
generator will therefore cost more to run under the winter PPD. Furthermore, the
Grid Exit Points (GXPs) associated with summer PPD correspond to predominantly
rural regions of the distribution network, while the GXPs associated with winter
PPD correspond to urban regions where planning consents for this technology
combination may be much harder to acquire and utilise. In this study, the site
selected was connected to a summer PPD GXP.
41. The target network peak demand for summer and winter is set in consultation
between Orion and the retailers. A load group refers to one or more controllable
water heating ripple channels, and is part of the total “ controllable load”
contributing to the peak demand. The energy and capacity drawn from the grid at
different times by these controllable loads can be varied to accommodate network
peak demand constraints. Having a number of controllable load groups enables
Orion to manage / minimise the peak demand. The PPD consists of chargeable
half-hours when one or more load groups has been shed for more than 15 minutes.
This information is used in billing calculations for general customers. Some load
groups (primarily residential water heating) are controlled directly by the Orion
load management system, and other load groups are controlled by individual
customers, in response to pricing signals.
42. The current pricing regime for network-embedded generators, wanting to sell
capacity to the Orion distribution network is shown in table 8 below5:
Table 8: Capacity Pricing Schedule for Network-Embedded Generators in the Orion Network
Pricing Definition Line Transmission Delivery
Fixed (Connection): GC - $0.00 ----- - $0.00/year
Fixed (Connection): MC - $500.05 ----- - $500.05/year
Peak Period Demand $66.70 $33.30 $100.00/kVA/year
Real power pricing schedule for generators larger than 30kW – go to http://www.oriongroup.co.nz/ for full details
GC = General Customers. MC = Major Customers. (A “+” sign indicates payment to the customer).
Under this proposal, Orion will pay an Independent Power Producer (IPP)
connected to the appropriate network area for either summer or winter peak period
generation based on the average capacity provided over the season at a rate of
$100/kVA/year5. (The charge for connecting a Major Customer’ s generator to the
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23.
Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
network is $500.05/year). In this study, the actual PPD schedules for the last three
summers were used to determine when the diesel generator had to operate to receive
PPD payments. The IDES tools3 developed for this purpose, used 10-minute
intervals to match the diesel generator’ s operating schedule and the wind energy
available with the PPD schedule for the season investigated. (The PPD schedule for
summer 2002-03 is given in table 9 below for reference). The average wind
capacity available over the PPD schedule for the season was used to calculate the
PPD payments from the wind generation. The diesel component of the DG-WTG
Hybrid system was used to cover only the capacity shortfall, when the wind turbine
could not provide 550kW of capacity during any time period in the PPD schedule.
Operating efficiency of the diesel genset was adjusted depending on its operating
level (kW output delivered).
Table 9: Duration of Chargeable Peak Half-hours for Summer 2002-03 PPD Season (108.5 hours in Total)
Date Half Hour Ending Duration Cumulative
Thu, 27-3-2003 19:30, 20:00, 20:30, 21:00, 21:30, 22:00 3.0 108.5
Wed, 26-03-2003 19:30, 20:00, 20:30, 21:00, 21:30, 22:00, 22:30 3.5 105.5
Tue, 25-03-2003 19:00, 19:30, 20:00, 20:30, 21:00, 21:30, 22:00, 22:30, 23:00 4.5 102.0
Mon, 24-03-2003 19:30, 20:00, 20:30, 21:00, 21:30, 22:00, 22:30, 23:00, 24:00 4.5 97.5
Fri, 21-03-2003 20:00, 20:30, 21:00, 21:30 2.0 93.0
Thu, 20-03-2003 19:30, 20:00, 20:30, 21:00, 21:30, 22:00, 22:30 3.5 91.0
Wed, 19-03-2003 20:00, 20:30, 21:00, 21:30, 22:00, 22:30 3.0 87.5
Tue, 18-03-2003 20:00, 20:30, 21:00, 21:30, 22:00, 22:30, 23:00 3.5 84.5
Mon, 17-03-2003 18:30, 19:00, 19:30, 20:00, 20:30, 21:00, 21:30, 22:00, 22:30, 23:00 5.0 81.0
Fri, 14-03-2003 01:00 0.5 76.0
Thu, 13-03-2003 21:30, 22:00, 22:30, 23:00 2.0 75.5
Wed, 12-03-2003 01:00, 01:30 1.0 73.5
Tue, 11-03-2003 01:00, 20:00, 20:30, 21:00, 21:30, 22:00, 22:30, 23:00, 24:00 4.5 72.5
Mon, 10-03-2003 18:00, 18:30, 19:00, 19:30, 21:00, 21:30, 22:00, 22:30, 23:00, 24:00 5.0 68.0
Fri, 7-03-2003 01:00 0.5 63.0
Thu, 6-03-2003 17:00, 17:30, 18:00, 18:30, 19:00, 21:30, 22:00, 22:30 4.0 62.5
Thu, 13-02-2003 22:30 0.5 58.5
Mon, 10-02-2003 17:30, 18:00, 18:30, 22:30 2.0 58.0
Wed, 8-01-2003 00:30, 01:00, 01:30, 02:00, 02:30 2.5 56.0
Tue, 7-01-2003 00:30, 01:00, 01:30, 18:30, 19:00, 19:30, 20:00, 20:30, 21:00, 7.5 53.5
21:30, 22:00, 22:30, 23:00, 23:30, 24:00
Mon, 6-01-2003 18:00, 18:30, 19:00, 19:30, 20:00, 20:30, 21:00, 21:30, 22:00, 6.5 46.0
22:30, 23:00, 23:30, 24:00
Sat, 4-01-2003 00:30 0.5 39.5
Fri, 3-01-2003 01:00, 01:30, 17:30, 18:00, 18:30, 19:00, 19:30, 20:00, 20:30, 6.5 39.0
22:30, 23:00, 23:30, 24:00
Thu, 2-01-2003 22:30, 23:00, 24:00 1.5 32.5
Wed, 1-01-2003 00:30, 01:00, 01:30 1.5 31.0
Tue, 31-12-2002 00:30, 01:00, 17:00, 17:30, 18:30, 19:00, 24:00 3.5 29.5
Mon, 30-12-2002 19:00, 22:30, 23:00, 24:00 2.0 26.0
Fri, 27-12-2002 24:00 0.5 24.0
Tue, 24-12-2002 01:00, 24:00 1.0 23.5
Mon, 11-11-2002 18:30, 19:00, 19:30, 20:00, 20:30 2.5 22.5
Thu, 7-11-2002 00:30, 01:00, 01:30, 02:00, 18:00, 18:30, 19:00, 19:30, 20:00, 6.5 20.0
20:30, 21:00, 21:30, 22:00
Wed, 6-11-2002 15:30, 16:00, 16:30, 18:30, 19:00, 19:30, 20:00, 20:30, 21:00, 7.5 13.5
21:30, 22:00, 22:30, 23:00, 23:30, 24:00
Tue, 5-11-2002 17:30, 22:00 1.0 6.0
Mon, 4-11-2002 22:00, 22:30 1.0 5.0
Wed, 23-10-2002 16:30, 17:00 1.0 4.0
Tue, 22-10-2002 17:30, 18:00, 18:30, 19:00, 19:30, 20:00 3.0 3.0
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Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
Other Potential Benefits Available from these Technology
Combinations Scenarios
Cogeneration Heat
43. Depending on the duration of the capacity delivery periods, substantial heat output
is available from the diesel engine described in the scenarios (see figures 1 and 2).
In some circumstances it may be worthwhile making use of this heat for water or
space heating applications. The specialised tools and methodologies used in this
study3 can be used to calculate the additional value to the operation of using this
heat. This value was not considered in these scenarios.
Standby Plant
43. In some customer applications the loss of service can be very costly. If the
appropriate controls and switching arrangements are in place, this technology can
be used to provide continuous capacity in the event of a grid supply failure. If the
cost of downtime is higher than the average cost of running for example: a diesel
generator operating continuously at the required capacity – additional risk reduction
returns are available. This value was not considered in these scenarios.
High GXP Prices
44. The diesel genset can be used to generate additional revenues (which may be
considerable) whenever the wholesale price-linked contract price rises above the
cost of operating the generator (for example, when national energy transmission
constraints or energy generation shortfalls occur). This value was not considered in
these scenarios.
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25.
Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
Resource Inputs
45. Wind: A wind energy data set of 10-minute values over a complete year was used
with 5, 7, 9 m/s average wind speeds.
Diesel: The diesel price used was 70.3c/litre delivered.
For other model inputs and assumptions see Appendix One.
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Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
Main Results of the Scenarios
MCLM Operating Scenario
46. For the DG-Only option, the simulation models were set to calculate the financial
return based on a full 550kW of capacity being delivered from the diesel generator
during the CPD schedule and for the four highest AC peaks (see paragraph 35). For
the DG-WTG Hybrid option, 550 kW combined generation capacity from wind and
diesel was delivered during the CPD schedule and for the four highest AC peaks
(with diesel generation meeting the capacity shortfall when less than 550kW of
wind turbine capacity was available). A summary of the results for the MCLM
operating scenario is given under two different financing arrangements: (a) 10%
interest on borrowing all required funds from the bank (see table 10) and 0%
interest (see table 11) for example as a result of channelling corporate funds directly
into the project.
Table 10: Summary of Annual MCLM Operating Scenario Results for 10% Interest on Finance over 20 years at an
average annual wind speed of 7m/s
MCLM Scenario Results
System Used CPD Season CPD Length Finance IRR Payback
550kW WTG-Only Summer 2001-02 1.6 Hrs 10% int. 11.93% 7.73 yrs
550kW WTG-Only Summer 2002-03 31.4 Hrs 10% int. 10.90% 8.25 yrs
550kW WTG-Only Summer 2000-01 81.1 Hrs 10% int. 9.43% 9.11 yrs
550kW DG-WTG Hybrid Summer 2001-02 1.6 Hrs 10% int. 9.56% 9.03 yrs
550kW DG-WTG Hybrid Summer 2002-03 31.4 Hrs 10% int. 9.45% 9.09 yrs
550kW DG-WTG Hybrid Summer 2000-01 81.1 Hrs 10% int. 9.20% 9.23 yrs
550kW DG-Only Summer 2001-02 1.6 Hrs 10% int. 24.99% 4.05 yrs
550kW DG-Only Summer 2002-03 31.4 Hrs 10% int. 24.38% 4.14 yrs
550kW DG-Only Summer 2000-01 81.1 Hrs 10% int. 23.25% 4.31 yrs
Table 11: Summary of Annual MCLM Operating Scenario Results for 0% Interest on Finance over 20 years at an
average annual wind speed of 7m/s
MCLM Scenario Results
System Used CPD Season CPD Length Finance IRR Payback
550kW WTG-Only Summer 2001-02 1.6 Hrs 0% int. 20.47% 4.85 yrs
550kW WTG-Only Summer 2002-03 31.4 Hrs 0% int. 19.55% 5.06 yrs
550kW WTG-Only Summer 2000-01 81.1 Hrs 0% int. 18.29% 5.37 yrs
550kW DG-WTG Hybrid Summer 2001-02 1.6 Hrs 0% int. 18.39% 5.34 yrs
550kW DG-WTG Hybrid Summer 2002-03 31.4 Hrs 0% int. 18.31% 5.36 yrs
550kW DG-WTG Hybrid Summer 2000-01 81.1 Hrs 0% int. 18.11% 5.41 yrs
550kW DG-Only Summer 2001-02 1.6 Hrs 0% int. 32.84% 3.08 yrs
550kW DG-Only Summer 2002-03 31.4 Hrs 0% int. 32.27% 3.13 yrs
550kW DG-Only Summer 2000-01 81.1 Hrs 0% int. 31.21% 3.23 yrs
The above tables summarise the median wind speed case. At first glance it appears
that the diesel generator only option provides the best return. But this is a high-risk
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27.
Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
option dependent on CPD payments alone and low CPD hours for income. The
wind-diesel hybrid provides lower risk by spreading income between capacity and
energy and is more attractive at higher wind speed.
47. For the three summer CPD seasons evaluated (see table 2) the WTG energy
contributions as a percentage of the total kWh of energy supplied from the hybrid
combination, will vary significantly with wind speed when the total CPD hours per
season is high. In other words, when the wind speed is low and the CPD hours are
high, the wind energy percentage drops because more diesel generation is necessary
to maintain the capacity during the control demand periods. The effect of this is to
reduce the IRR on all options. (A more detailed list of assumptions is given in
appendix one). Table 12 shows how much energy would be supplied from the wind
at different average wind speeds. Even at 5m/s, 88.45% of the annual energy
supplied still comes from the wind, for the longest CPD season (81.1 hours),
although in this case the WTG-Only IRR is reduced from 18.29% (0% financing –
see table 11) at a 7m/s annual wind speed, to 6.18% (0% financing) at a 5m/s
annual wind speed.
Table 12: MCLM Scenario Results for Energy Contributions (% kWh) from Wind Energy
CPD Hours MCLM Wind @ 5m/s MCLM Wind @ 7m/s MCLM Wind @ 9m/s
/ Season
1.6 Hrs 99.52% (876 kWh) 99.80% (878 kWh) 99.82% (878 kWh)
31.4 hrs 95.56% (16,503 kWh) 98.11% (16,944 kWh) 98.89% (17,078 kWh)
81.1 Hrs 88.45% (39,453 kWh) 94.54% (42,170 kWh) 96.41% (43,004 kWh)
48. The contribution of CPD capacity and AC support towards the MCLM scenario’ s
total annual earnings can be essential to the economic viability of the distributed
generation system. Table 13 provides a summary of the energy and capacity
contributions towards the annual earnings under different annual wind speeds for
the technology options investigated in this study. (These results are presented
graphically in figure 4). The values in parentheses represent what the payback
periods would have been without any earnings contributions from the CPD and AC.
Table 13: MCLM Scenario Results for 0% Interest on Finance (For a Typical CPD Season: Summer 2002-03)
Option kWh / year CPD kW Earnings AC&CPD Earnings: Payback -
capacity from kWh earnings total per without kW
Support energy / yr per year year earnings in ( )
WTG-Only @ 5m/s 926,202 119 $50,663 $21,334 $71,997 10.69 (> 20)
WTG-Only @ 7m/s 1,683,957 245 $92,112 $37,803 $129,915 5.06 (8.64)
WTG-Only @ 9m/s 2,144,492 334 $117,304 $47,005 $164,309 3.85 (6.33)
DG-WTG @ 5m/s 969,222 550 $53,016 $58,747 $111,763 8.27 (> 20)
DG-WTG @ 7m/s 1,716,421 550 $93,888 $64,882 $158,770 5.36 (13.64)
DG-WTG @ 9m/s 2,168,484 550 $118,616 $66,802 $185,418 4.48 (9.29)
DG-Only 52,941 550 $2,896 $48,394 $51,290 3.13 (> 20)
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Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
49. The table 13 results indicate that economic viability without capacity support is
not simply dependent on the energy to capacity earnings ratio, as shown by:
WTG-Only @ 5m/s (70% energy to 30% capacity earnings ratio); DG-WTG
Hybrid @ 5m/s (47% energy to 53% capacity earnings ratio); and, DG-Only (6%
energy to 94% capacity earnings ratio). Note that a relatively high WTG-Only
capacity support ranging from 119kW to 334kW was obtained. This contribution
was achieved because the Orion payment model allows average capacity to be
rewarded. If only the minimum capacity at anytime during the CPD was
rewarded, then the option would provide much lower financial returns. The
equivalent value (in cents / kWh) of the capacity earnings are given in table 14
below. This table shows how much energy has to be delivered in order to avail of
the potentially high earnings possible from delivering capacity.
Figure 4 shows the above results in graphical form, which demonstrates the
highest revenues (savings) come from the wind-diesel combinations but this does
not necessarily give the best ROI.
Comparison of MCLM Energy and Capacity Savings for the Summer 2002-03 CPD
Season
$200,000
$180,000
$160,000
Annual Savings
$140,000
AC & CPD Savings from Capacity / yr
$120,000
$100,000
$80,000 Savings from Energy / yr
$60,000
$40,000
$20,000
$0
WTG- WTG- WTG- DG-WTG DG-WTG DG-WTG DG-Only
Only @ Only @ Only @ Hybrid @ Hybrid @ Hybrid @
5m/s 7m/s 9m/s 5m/s 7m/s 9m/s
Distributed Generation Option
Figure 4: Graphical Comparison of the Earnings Contributions from Energy and Capacity for the MCLM Scenario
50. Table 14 shows that the equivalent value in cents / kWh of capacity supplied by
distributed generation systems can be quite substantial, over fairly small periods of
time. (Table 14 results are presented graphically in figure 5).
It is interesting to note that there is some correlation between high wholesale
electricity pricing periods and capacity demand periods. As a result, the overall
averaged c/kWh equivalent earnings is more than likely to be significantly higher
than figures quoted in table 14.
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29.
Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
Table 14: Equivalent Earnings in c/kWh Energy for the MCLM Scenario Results in Table 13
Option % Earnings from % Earnings from capacity Averaged c/kWh
energy supplied supplied (see note* below): equivalent earnings
@ 5.47cents/kWh
% Earnings @ Equivalent c/kWh Capacity Total
WTG-Only @ 5m/s 70% 30% 536.76 2.30 7.77
WTG-Only @ 7m/s 71% 29% 461.97 2.24 7.71
WTG-Only @ 9m/s 71% 29% 421.36 2.19 7.66
DG-WTG @ 5m/s 47% 53% 319.80 6.06 11.53
DG-WTG @ 7m/s 59% 41% 353.20 3.78 9.25
DG-WTG @ 9m/s 64% 36% 363.65 3.08 8.55
DG-Only 6% 94% 263.44 91.41 96.88
* Note: % earnings from capacity supplied in equivalent c/kWh has been calculated from the actual kWh used in
order to provide capacity support, in this case: 31.4 hours CPD (Summer 2002-03) + 4 hours AC
Equivalent Earnings in c/kWh for the MCLM Scenario Results
Extended to approx.
97c/kWh (Total)
25
Averaged c/kWh Equivalent Earnings
20
15
Averaged capacity earnings
Averaged energy earnings
10
5
0
WTG-Only WTG-Only WTG-Only DG-WTG DG-WTG DG-WTG DG-Only
@ 5m/s @ 7m/s @ 9m/s Hybrid @ Hybrid @ Hybrid @
5m/s 7m/s 9m/s
Distributed Generation Option
Figure 5: Equivalent Total Earnings in c/kWh for the Energy and Capacity Components for MCLM
IPP Operating Scenario
51. For the DG-Only option, the simulation models were set to calculate the financial
return based on a full 550kW of capacity being delivered from the diesel generator
during the PPD schedule. For the DG-WTG Hybrid option, 550 kW combined
generation capacity from wind and diesel was delivered during the PPD schedule
(with diesel generation meeting the capacity shortfall when less than 550kW of
wind turbine capacity was available). Tables 15 and 16 provide a summary of the
IPP operating scenario results under two different financing arrangements: (a) 10%
interest on borrowing all required funds from the bank (see table 15) and 0%
interest (see table 16) for example as a result of channelling corporate funds directly
into the project.
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30.
Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
Table 15: Summary of Annual IPP Operating Scenario Results for 10% Interest on Finance over 20 years at an
average annual wind speed of 7m/s
IPP Scenario Results
System Used PPD Season PPD Length Finance IRR Payback
550kW WTG-Only Summer 2001-02 53 Hrs 10% int. 4.45% 13.32 yrs
550kW WTG-Only Summer 2002-03 108.5 Hrs 10% int. 5.70% 12.03 yrs
550kW WTG-Only Summer 2000-01 307.5 Hrs 10% int. 5.76% 11.97 yrs
550kW DG-WTG Hybrid Summer 2001-02 53 Hrs 10% int. 4.59% 13.15 yrs
550kW DG-WTG Hybrid Summer 2002-03 108.5 Hrs 10% int. 4.35% 13.40 yrs
550kW DG-WTG Hybrid Summer 2000-01 307.5 Hrs 10% int. 3.36% 14.51 yrs
550kW DG-Only Summer 2001-02 53 Hrs 10% int. 28.98% 3.50 yrs
550kW DG-Only Summer 2002-03 108.5 Hrs 10% int. 27.53% 3.66 yrs
550kW DG-Only Summer 2000-01 307.5 Hrs 10% int. 22.10% 4.42 yrs
It is interesting to note that the Wind only generation option performs better at higher
PPD durations. This is purely coincidental with longer PPD durations representing PPD
schedules corresponding to higher wind capacity factors for the wind profiles used.
Table 16: Summary of Annual IPP Operating Scenario Results for 0% Interest on Finance over 20 years at an
average annual wind speed of 7m/s
IPP Scenario Results
System Used PPD Season PPD Length Finance IRR Payback
550kW WTG-Only Summer 2001-02 53 Hrs 0% int. 14.26% 6.63 yrs
550kW WTG-Only Summer 2002-03 108.5 Hrs 0% int. 15.22% 6.29 yrs
550kW WTG-Only Summer 2000-01 307.5 Hrs 0% int. 15.26% 6.27 yrs
550kW DG-WTG Hybrid Summer 2001-02 53 Hrs 0% int. 14.38% 6.58 yrs
550kW DG-WTG Hybrid Summer 2002-03 108.5 Hrs 0% int. 14.21% 6.63 yrs
550kW DG-WTG Hybrid Summer 2000-01 307.5 Hrs 0% int. 13.54% 6.86 yrs
550kW DG-Only Summer 2001-02 53 Hrs 0% int. 36.80% 2.75 yrs
550kW DG-Only Summer 2002-03 108.5 Hrs 0% int. 35.41% 2.85 yrs
550kW DG-Only Summer 2000-01 307.5 Hrs 0% int. 30.29% 3.28 yrs
52. Based on the PPD hours experienced, table 17 gives an indication of how much
energy would have been supplied from the wind resource at different average wind
speeds. Even at 5m/s, 73.57% of the annual energy supplied still comes from the
wind, for the longest PPD season (307.5 hours), although in this case the WTG-
Only IRR is reduced from 15.26% (0% financing – see table 17) at a 7m/s annual
wind speed, to 4.15% (0% financing) at a 5m/s annual wind speed.
Table 17: IPP Scenario Results for Energy Contributions (% kWh) from Wind Energy
PPD Hours IPP Wind @ 5m/s IPP Wind @ 7m/s IPP Wind @ 9m/s
53 Hrs 93.80% (27,343 kWh) 97.39% (28,389 kWh) 98.22% (28,631 kWh)
108.5 Hrs 89.01% (53,117 kWh) 95.30% (56,870 kWh) 96.69% (57,700 kWh)
307.5 Hrs 73.57% (124,425 kWh) 87.93% (148,712 kWh) 91.70% (155,088 kWh)
53. The contribution of PPD capacity support towards the IPP scenario’ s total annual
earnings can be essential to the economic viability of the distributed generation
system selected. Table 18 provides a summary of the energy and capacity
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31.
Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
contributions towards the annual earnings under different annual wind speeds for
the technology options investigated in this study. (These results are presented
graphically in figure 6). The values in parentheses represent what the payback
periods would have been without any earnings contributions from the PPD.
Table 18: IPP Scenario Results for 0% Interest on Finance (For a Typical PPD Season: Summer 2002-03)
Option kWh / year PPD kW Earnings PPD Earnings: Payback -
capacity from kWh earnings total per without kW
Support energy / yr per year year earnings in ( )
WTG-Only @ 5m/s 926,202 187 $45,597 $18,208 $63,805 13.19 (> 20)
WTG-Only @ 7m/s 1,683,957 296 $82,901 $29,138 $112,039 6.29 (10.47)
WTG-Only @ 9m/s 2,144,492 327 $105,573 $32,179 $137,752 4.95 (7.56)
DG-WTG @ 5m/s 1,040,551 550 $51,226 $54,500 $105,726 > 20 (> 20)
DG-WTG @ 7m/s 1,767,078 550 $86,993 $54,500 $141,493 6.63 (18.76)
DG-WTG @ 9m/s 2,217,994 550 $109,192 $54,500 $163,692 5.59 (11.83)
DG-Only 161,805 550 $7,966 $54,500 $62,466 2.85 (> 20)
54. The table 19 results indicate (once again – see paragraph 49) that economic viability
without capacity support is not simply dependent on the energy to capacity savings
ratio, as shown by: WTG-Only @ 5m/s (71% energy to 29% capacity savings
ratio); DG-WTG Hybrid @ 5m/s (48% energy to 52% capacity savings ratio); and,
DG-Only (13% energy to 87% capacity savings ratio). Note again (see paragraph
48) that a relatively high WTG-Only capacity support ranging from 187kW to
327kW was obtained. This contribution was achieved because the Orion payment
model allows average capacity to be rewarded. If only the minimum capacity at
anytime during the PPD was rewarded, then the option would provide much lower
financial returns. The equivalent value (in cents / kWh) of the capacity earnings are
given in table 19 below. This table shows how much energy has to be delivered in
order to avail of the potentially high earnings possible from delivering capacity.
Comparison of IPP Energy and Capacity Revenues for the Summer 2002-03 PPD
Season
$180,000
$160,000
$140,000
Annual Savings
$120,000
$100,000 PPD Revenue from Capacity / yr
$80,000 Revenue from Energy / yr
$60,000
$40,000
$20,000
$0
WTG- WTG- WTG- DG-WTG DG-WTG DG-WTG DG-Only
Only @ Only @ Only @ Hybrid @ Hybrid @ Hybrid @
5m/s 7m/s 9m/s 5m/s 7m/s 9m/s
Distributed Generation Option
Figure 6: Graphical Comparison of the Earnings Contributions from Energy and Capacity for the IPP Scenario
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32.
Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
55. Table 19 shows that the equivalent value in cents / kWh of capacity supplied by
distributed generation systems can be quite substantial, over fairly small periods of
Table 19: Equivalent Earnings in c/kWh Energy for the IPP Scenario Results in Table 18
Option % Earnings from % Earnings from capacity Averaged c/kWh
energy supplied supplied (see note** below): equivalent earnings
@ 4.92cents/kWh
% Earnings @ Equivalent c/kWh Capacity Total
WTG-Only @ 5m/s 71% 29% 89.74 1.97 6.89
WTG-Only @ 7m/s 74% 26% 90.73 1.73 6.65
WTG-Only @ 9m/s 77% 23% 90.70 1.50 6.42
DG-WTG @ 5m/s 48% 52% 91.33 5.24 10.16
DG-WTG @ 7m/s 61% 39% 91.33 3.08 8.01
DG-WTG @ 9m/s 67% 33% 91.33 2.46 7.38
DG-Only 13% 87% 91.33 33.68 38.61
** Note: % earnings from capacity supplied in equivalent c/kWh has been calculated from the actual kWh used in
order to provide capacity support, in this case: 108.5 hours PPD (Summer 2002-03)
time. (Table 19 results are presented graphically in figure 7). Once again (see
paragraph 50), it is interesting to note that there is some correlation between high
wholesale electricity pricing periods and capacity demand periods. As a result,
therefore, overall averaged c/kWh equivalent earnings is more than likely to be
significantly higher than figures quoted in table 19.
Equivalent Earnings in c/kWh for the IPP Scenario Results
Extended to approx.
45c/kWh (Total)
25
Averaged c/kWh Equivalent Earnings
20
15
Averaged capacity earnings
Averaged energy earnings
10
5
0
WTG-Only WTG-Only WTG-Only DG-WTG DG-WTG DG-WTG DG-Only
@ 5m/s @ 7m/s @ 9m/s Hybrid @ Hybrid @ Hybrid @
5m/s 7m/s 9m/s
Distributed Generation Option
Figure 7: Equivalent Total Earnings in c/kWh for the Energy and Capacity Components for IPP
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33.
Decentralised Capacity-Support for Distribution Networks from Distributed Energy Resources
Comparing the MCLM and IPP Operating Scenarios
56. The results from tables 10 and 15 have been summarised in figure 8 below. Figure
8 shows the Internal Rate of Return (IRR) trends against the different annual total
CPD or PPD hours for an average wind speed of 7 m/s, for the IPP and MCLM
operating scenarios.
IRR Based on Seasonal Control (MCLM / Load Mgt) or Peak (IPP / Generator) Period Duration,
with 10% Interest on Finance with WTG Priced at $2,725/kW over Life
30%
DG-Only (Generator)
25%
DG-Only (Load Mgt)
Internal Rate of Return (IRR)
20% DG & WTG @ 7m/s
(Generator)
DG & WTG @ 7m/s
(Load Mgt)
15%
WTG-Only @ 7m/s
(Generator)
10% WTG-Only @ 7m/s
(Load Mgt)
Poly. (DG-Only
(Generator))
5%
Linear (DG-Only
(Load Mgt))
Linear (WTG-Only @
0%
7m/s (Load Mgt))
-5%
0 100 200 300 400 500 600 700 800 900 1000
Seasonal Peak / Control Demand Period Duration
Figure 8: Comparison of the IRR for the different IPP and MCLM Scenarios
57. Figure 8 shows that, because of the higher fuel content and its cost relative to wind,
the longer the seasonal CPD or PPD period, the lower the Internal Rate of Return
(IRR). There is no direct relationship between speed and the length of the seasonal
CPD or PPD period. In the examples used in this study, the increase in CPD
duration corresponded with a decrease in the seasonal average availability of wind;
while, the increase in PPD duration corresponded with an increase in the seasonal
average availability of wind. Further investigation of average wind speed variations
over extended periods of time can be conducted using Monte Carlo simulation
methods. (See tables 5 and 9 to compare the CPD and PPD for Summer 2002-03).
58. It is interesting to note that the diesel generator option (DG-Only), operating to
provide capacity support to the network under the IPP operating scenario, provides
the best financial returns overall. For the DG-WTG Hybrid combination, a modest
financial return is provided at a 7m/s average wind speed for the MCLM operating
scenario but the IPP operating scenario provided a poor result due to the reduced
income gained from capacity savings in the MCLM mode. . For the WTG-Only
option, the IPP operating scenario financial returns are poor due to limited capacity
support, but the MCLM operating scenario provides better – even attractive
financial returns because of the higher value of the energy delivered. From these
results, it appears that predictable dispatchable distributed generation is best suited
Industrial Research Page 33 Dr. Iain Sanders