An expert discusses integrating renewables and storage into distribution networks using an Advanced Distribution Management System (ADMS). Key points covered include: 1) ADMS allows utilities to analyze, control, and optimize renewables and energy storage systems on the distribution network. 2) Integrating accurate weather forecasting with ADMS helps maximize the benefits from renewables. 3) Microgrids containing distributed energy resources and demand response can be managed and optimized by ADMS.

1. Advanced Distribution
Management System
Integration of Renewables
and Storage
Analyse, control, and optimise renewables and energy
storage systems within the distribution network
John Dirkman, PE
Sr. Product Manager, Schneider Electric
john.dirkman@schneider-electric.com
http://www.linkedin.com/in/dirkman
23 October 2013

2. Key Learning Objectives
● Learn how renewables and distributed energy resources can impact an
electric distribution system
● Discover ways to manage and optimise renewables and distributed
energy resources using ADMS
● Maximize benefits from renewables by leveraging integration of an
accurate weather forecasting system with ADMS
● Learn how microgrids, with distributed energy resource and demand
response components, are managed and optimized by ADMS

3. the global specialist
in energy management
Some of the world class brands that we have
built or acquired in our 175 year history
A global company
$31 billion sales in 2012
41% of sales in new economies
140,000+ people in 100+ countries
committed to innovation
4-5% of sales devoted to R&D
~$1.5 billion devoted to R&D
Delivering Solutions for End Users
Utilities & Infrastructure
25%
Industrial & machines
22%
Data Centers
15%
Non-residential buildings
Residential
29%
9%

4. ADMS/PCS Projects Worldwide
NIH, Washington DC, USA
EPCOR,
AB, Canada
BC Hydro,
BC, Canada
Austin Energy,
Texas
Burbank W&P,
California
Duke/Progress Enrgy,
North Carolina
CFE, Zona Puebla City,
Mexico
EMCALI, Cali,
Columbia
Petroproduccion,
Ecuador
MEER,
Ecuador
EDELNOR,
Lima, Peru
EPS,
Serbia
UofM, Michigan Elektro Celje,
Slovenia
Dong Energy,
Hydro One,
Denmark
ON, Canada
ENEL,
NS Power,
Italy
NS, Canada
PECO,
Philadelphia
Railway project,
Murcia, Spain
CNFL, San Jose,
Costa Rica
STEG,
Tunisia
ELECTRA, Panama City,
Panama
Energoprom, Novocheboksary
Russia
IDGC Center Russia, Moscow,
Russia
Irkutsk,
Russia
EMASZ / ELMU, Budapest,
Hungary
Guizhou Electric
Bihar,
Electrica, Cluj,
Corporation, China
India
Romania
Guangxi Power,
EVN,
China
Macedonia
UAE
Medina,
Saudi Arabia
Light Services de Electricitade,
Rio de Janeiro, Brazil
EPS
Serbia
EDEN, Buenos Aires province,
Argentina
PT-PLN, Bandung,
Indonesia
ACTEW, Canberra
Australia
Unison,
New Zealand
EPRS
EDENOR, Buenos Aires,
Argentina
ANDE, Asuncion,
Paraguay
Maharashtra,
India
PT-PLN, Banda Aceh,
Indonesia
Abu Dhabi,
B&H
EPCG
Montenegro
Over 180 control centers and 88M meters
ETSA, Adelaide
Australia

5. Utility Transformation
How do you expect utility business models to be in 2030 compared to
today in your market?

6. Utility Transformation
Which energy market transformation vision most closely matches your
expectations of your market?

7. Definitions
● Distributed Generation (DG)
● Dispersed generation, typically less than 10 MW, in the distribution network
● Controllable DG: Combined Heat and Power, Generators, ~Hydro
● Non-controllable DG: Wind and Solar
● Energy Storage Systems (ES)
● Battery Banks, Compressed Air Systems, Thermal Storage Systems
● Distributed Energy Resources (DERs)
● Combination of DG and ES, located throughout the distribution network
Power Resource
Generators
Wind
Solar
Interties
Battery Banks
Electric Vehicles
Compressed Air Systems
Thermal Storage Systems
Demand Response
Type*
Supply
Supply
Supply
Supply/Demand
Supply/Demand
Supply/Demand
Supply/Demand
Demand
Demand
Controllable?
Yes
No
No
Yes
Yes
Yes
Yes
Yes
Yes
* Supply-side provides power, Demand-side consumes power or affects consumption

8. Poll Question 1 – Preparedness
●How prepared is your utility for integration and optimization of
renewables and storage?
●Please select one:
1.
2.
3.
4.
5.
6.
Just getting started [38%]
Somewhat prepared [15%]
Fairly well prepared [15%]
Completely prepared but not yet fully integrated and optimized [1%]
We are already integrating and optimizing renewables and storage [7%]
Unknown [24%]

9. Energy Storage in the Network
● Storage provides benefits in the distribution network:
● Storing of active power
● Flattening of load profile: smaller nighttime valley and reduced daytime peak
● Storage can be considered as source of active power during peak hours
(energy storage as peak generation unit)
● In combination with intermittent operation of renewables (e.g. solar), ES can
provide continual power supply even during night hours
● Combination of renewables + ES can reduce fluctuation of power injection
caused from variation of solar/wind input. Stored energy can mitigate
sudden injections or drops of power from renewables.

10. Impact on Profile
● Impact on profile (left lower corner, gray area is stored energy, while
gray area in peak hours denote discharged energy):

11. Definitions Continued
● Demand Response (DR)
● Management of consumption, anywhere along a feeder, in response to
supply conditions
●Network Reconfiguration
●Voltage Reduction
●Volt/VAR Optimization
●DG/ES/DER Management
●Load Shedding/Curtailment
● Microgrid
● A local network of DERs and consumers that is a subset of the distribution
network
● Can operate in an isolated manner or be always connected
● May include multiple DR components
● Microgrid management targets local energy supply and demand

12. The Advanced DMS
Convergence of
DMS, OMS, and
SCADA
Monitoring,
analysis, control,
optimization,
planning, and
training
Management of
Demand and
Distributed
Energy
Resources
Network
automation with
closed-loop
control
Incident, fault,
and crew
management with
field mobility
Common User Experience, Data Model, Integration, Secure Infrastructure

13. ADMS Functionality












Real-time Simulation
Off-line Simulation
What-if Analysis
Historical Playback
Load Flow
State Estimation
Energy Losses
Fault Calculation
Reliability Analysis
Relay Protection
Device Capability
Contingency Analysis





Telemetry
Alarming
Tagging
Trending
Reporting
Train
Plan
ADMS Benefits
 Safety
 Reliability
 Efficiency
 Standardized Training
 Unified Interface
 Detailed Equipment Usage History
 Medium and Long-term
Load Forecasting
 Network Automation
 Network Reinforcement
 Optimal Device Placement
Optimize
 Volt/VAR Optimization
 Network Reconfiguration
 Near and Short-term Load
Operate
Forecasting
 Demand Response
 Distributed Energy Mgmt.
Analyze
Monitor






Fault Management
Switch Management
Crew Management
Under-load Switching
Large Area Restoration
Load Shedding

14. ADMS/PCS Projects Worldwide
NIH, Washington DC, USA
EPCOR,
AB, Canada
BC Hydro,
BC, Canada
Austin Energy,
Texas
Burbank W&P,
California
Duke/Progress Enrgy,
North Carolina
CFE, Zona Puebla City,
Mexico
EMCALI, Cali,
Columbia
Petroproduccion,
Ecuador
MEER,
Ecuador
EDELNOR,
Lima, Peru
EPS,
Serbia
UofM, Michigan Elektro Celje,
Slovenia
Dong Energy,
Hydro One,
Denmark
ON, Canada
ENEL,
NS Power,
Italy
NS, Canada
PECO,
Philadelphia
Railway project,
Murcia, Spain
CNFL, San Jose,
Costa Rica
STEG,
Tunisia
ELECTRA, Panama City,
Panama
Energoprom, Novocheboksary
Russia
IDGC Center Russia, Moscow,
Russia
Irkutsk,
Russia
EMASZ / ELMU, Budapest,
Hungary
Guizhou Electric
Bihar,
Electrica, Cluj,
Corporation, China
India
Romania
Guangxi Power,
EVN,
China
Macedonia
Maharashtra,
India
PT-PLN, Banda Aceh,
Indonesia
Abu Dhabi,
UAE
Medina,
Saudi Arabia
Light Services de Electricitade,
Rio de Janeiro, Brazil
EPS
Serbia
EDEN, Buenos Aires province,
Argentina
PT-PLN, Bandung,
Indonesia
ACTEW, Canberra
Australia
Unison,
New Zealand
EPRS
EDENOR, Buenos Aires,
Argentina
ANDE, Asuncion,
Paraguay
Over 180 control centers and 88M meters
B&H
EPCG
Montenegro
ETSA, Adelaide
Australia

15. Renewable Resource Commitment
● In June 2007, seeks to obtain
Burbank now the Burbank City
66% of adopted from
Council electricityBWP's
renewable resources 33% of
recommendation that by 2025
● electricity be will be a from
Renewables procured
renewable resources by wind,
combination of primarily 2020
● Burbank was the first city in the
solar, and compressed air
storage systems
United States to step up to this
ambitious goal

16. Renewable Resource Variability
185 MW
170 MW
10 MW
20 MW

17. Integrated ADS Business Objectives
● Integrate Demand and Supply resources into the realtime and
day-ahead operations at Burbank Water and Power
● Automate and Optimize dispatch of resources:
● Generation
● Renewable energy resources
(solar and wind)
● Energy purchases and sales
● Demand response and load
control (ADR)
● Energy storage and EV
● Distributed generation and PV
● Centralized Control Center

18. Integrated Automatic Dispatch System
(iADS)
Weather Service
(Schneider Elec)
Wholesale Markets
Balancing Authority
Trading Partners
Wholesale &
Market
Operations
(OATI)
GIS/OMS
(Schneider Elec)
CIS
(Oracle CC&B)
ADS/AGC
(OATI)
PCS/SCADA
(LF, RF, AGC)
(Schneider Elec)
AMI (Trilliant)
MDMS (eMeter)
Fiber/wireless networks/Internet
Customer
Portal
Distributed
Generation
Energy
Storage
Demand
Response
Ice Bear
TES units
Building
Mgmt
System
18

19. Poll Question 2 – Main Drivers
●At your utility, what are the main drivers for integration and
optimization of renewables and storage?
●Please select all applicable replies:
1. Required for reliability (create alternative sources of distributed energy
in the event of outages) [8%]
2. Required for reliability (reduce load on sections of feeders) [15%]
3. Required for efficiency (e.g. peak shifting, peak shaving, balance
supply and demand) [18%]
4. Required for environmental reasons (cleaner energy) [20%]
5. Required due to regulatory/governmental requirements [25%]
6. Other (please email John with your drivers) [1%]
7. Unknown [13%]

20. The DG/DER Challenge
● Integration of renewables and storage is a challenge for networks
designed to operate in the “classical” way
(one way: transmission –> distribution -> consumer)
● Renewables in the distribution system completely change the
philosophy of network operation:
● reverse power flow
● impact on voltage profile
● protection schemes
● Distribution network starts to look more like the transmission network

21. Problems Created By DG and DER in
the Network
● Without ADMS, DG/DER’s in the network introduce several dilemmas
for engineering and operations:
● No visibility of network state with DG/DER’s
● Not clear if operating problems like high/low voltages are caused by
DG/DER’s or normal loading conditions
● Not clear how to select the optimal location for connecting large DG/DER
resources to the network
● No clear direction on how to maximize the operation and value of “green”
energy provided by renewables
● Result is operating problems such as high/low feeder voltage and
reverse power flows may go unseen until customers are affected

22. Current Situation
Wind
Generation
Buildings
???
Weather
Stations
Distribution utilities face new challenges
Solar
Panels
Smart
Devices
Smart Field
Devices
Houses + Electrical Vehicles
CHP Plants

23. DG/DER Visualization and Monitoring
● Visualization
● Geographic, schematic, substation views
● Filtering by and search by resource type, voltage level, size, affiliation, etc.
● Monitoring
● Real-time awareness of DG/DER activity
● Visualization and reports for active/reactive (over/under) generation
● Condition-based monitoring for maintenance

24. DG/DER Analysis and Forecasting
● Over generation
● Violation of upper limits for active/reactive power generation
● Predictive alarming, phase balancing
● Harmonic penetration
● Harmonic analysis in presence of DG/DERs
● DG/DER contribution to harmonic levels
● History of operations
● Historical trending and reporting
● Identify periods of operational violations
● Near-term and short-term forecasting
● Load and solar/wind generation forecasting
● Historical behavior with current and forecasted weather (wind
speed, solar irradiance, temperature, humidity)

25. WeatherSentry
● Weather imposes the largest external impact on your Smart Grid
● Demand, renewable energy supply, and outages are heavily influenced by weather
● Intelligent weather integration is the key factor in efficient Smart Grid management
Transmission
Load Forecasting
90% of demand variation
due to weather
Distribution
Temperature,
humidity and wind
impact line capacity
Weather is largest cause of
outages (lightning, high winds,
ice, transformer failures due to
high load, etc.)
Wind Power
Trading
Distributed Generation
Highly variable, difficult to predict.
Causes increases in spinning reserve
generation and risk of grid instability
Improved prediction of load
and renewable energy
contribution improves trading
decisions
Home solar contributions can cause
system instability due to rapid cloud
cover changes
WindPower Forecasts
Solar Power Forecasts

26. Schneider Electric – Dominant Weather
Provider to the Energy Industry in North
America
● 70% of generation in U.S.
● Largest energy weather provider
in U.S.
● A $30 billion global energy leader
● Rapid growth internationally
● Schneider Electric is an ADMS
leader
● #1 for transmission and distribution
crew management
● Weather integrated into OMS & DMS
SmartGrid systems
electric industry uses
Schneider Electric weather
forecasts for load modeling
● Renewable energy services:
● 73% of US wind farms use Schneider
Electric lightning safety alerting
● Advanced wind power and solar
forecasting

27. Forecasting Accuracy Results
Typical results for a single wind plant
Forecast Horizon
Hour-ahead to next 12 hours
Day-ahead (hour 30)
Days 3-7
MAPE = Mean Absolute Percentage Error
What accuracy are you
currently receiving?
MAPE* of Rated
Capacity
6-12%
12-18%
18-20%

28. Improved Accuracy Gives Large ROI
A Customer Perspective of Wind Power Forecast Value
● Day Ahead Forecasting Error Theory when using WindLogics forecasts
● Ideal Revenue = “generate exactly to the forecast”
● Deviation to Ideal = “Forecast Error”
● Forecast Error is comprised of
• Availability error
• Curtailments
1/3 of Forecast Error
• Wind forecast error: Timing & magnitude
● Customer view:
• Assuming 15% MAPE, each 1% equates to $65K, or nearly
$1M annually (400MW wind portfolio)
● Ongoing WindLogics forecast training yields between 3-5%
improvement in accuracy, or $195K-$325K annually

29. Forecasting of Ramp Events
● Uses an ensemble approach to ramp probability
● The WindLogics forecasting system outputs predictive intervals
(P20/P50/P80), which provide a valuable assessment of the
possible impact of a ramp event (timing & magnitude)
Ramp events
were wellforecasted
days in
advance
Actual Power
P20 Forecast Power
P50 Forecast Power
P80 Forecast Power

30. DTN Solar Forecasting Experience
Providing solar irradiance
forecasts to many utilities
for load forecasting
Utility-scale solar irradiance forecasting
● PV (Photovoltaic) and
● CSP (Concentrated Solar Power),
including Abengoa Solar
Distributed solar projects,
for utilities

31. Schneider Electric’s Solar Capabilities
● Schneider Electric provides a leading inverter solution, and is a solar
integrator
● Schneider Electric has SCADA systems for solar plants (monitoring &
control), used by Abengoa Solar and others
● Schneider Electric’s ADMS (Advanced Distribution Management
System) manages distributed solar generation challenges for utilities
● Schneider Electric is participating in a major US Department of Energy
3-year research project with the US National Center for Atmospheric
Research (NCAR) to improve solar forecasting, as part of the US
Department of Energy’s “SunShot” Initiative)

32. Benefits of Solar Forecasting System
●Integrate solar successfully
●Schedule power and maintain system reliability
●Utilize more of the generated solar power
●Minimize reserve costs
●Reliably make unit commitments, reduce risk
●Improve power marketing

33. DTN Solar Benefits
●Provides outstanding irradiance accuracy
●Reliable delivery
●Energy weather experts, with the resources of
Schneider Electric, committed to solar energy
●Also, we will be introducing solar power forecasting in
Q4 2013
● Irradiance forecasting now
● Adding generated power forecasting

34. ADMS Operation & Optimization of DER
● Dispatch (reliability, economic)
● Dispatch entire network or localized areas
● Increase or decrease generation (automatically/manually)
● Operation Validation
● What-if analysis in simulation mode
● Prevent operation on adjacent feeders
● Volt/VAR Optimization
● Manage VVO in the presence of DG/DERs
● Utilize DG/DERs as VVO resource
● Relay Protection Coordination
● Adaptive relay protection and transfer trip settings
● Microgrid Islanding
● Maintaining reliable service with islanded networks

35. Steps to Solving the DG/DER Problems
1. Provide full visibility of network state with DG/DER; to increase
network awareness
2. Evaluate the impacts of new DG/DER;
● What will happen if we add a new unit,
● Simulate and study impacts before unit goes on line (planning)
3. Optimize DG/DER operation (including microgrids)

36. 1. Full visibility of network state
● A comprehensive task which requires modeling of DG/DER with
appropriate models:
● Load flow model
● Short circuit model
● Models which can be used for forecasting purposes
● ADMS software package provides modeling
● For real-time visualization and operations
● For off-line simulation and study
● Following are some illustrations of the main effects of DG/DER in the
distribution network

37. Full Network State Visibility

38. Voltage Profiles – no DG (open)

39. Voltage Profiles – with DG (closed)

40. Short Circuit Current

41. Near Term Operation Planning
supported by Weather Forecast Inputs

42. 2. DG/DER Planning
● What will happen if we add a new unit
● Run analysis before adding unit in the network
● One possibility is to add DG/DER in the selected network configuration and
state (e.g. the worst case)
● Better possibility is to check several typical cases, e.g.:
● Maximum DG production/minimum Load (voltage problems?)
● Minimum DG production/maximum Load (overloading?)
● Etc.

43. Planning Variants
S1.0 - DGmaxLoadmax
No problem
S2.0 - DGminLoadmin
No problem
S3.0 - DGmaxLoadmin
S3.1 Volt/VAR Optimization (VVO)
Voltage problem
Load
S0.0
DG
S0.1
S4.1 Cable Reinforcement
S4.0 - DGminLoadmax
S4.2 Load Management + Reconfiguration
Overload problem
S4.3 Demand Response
S4.4 Energy Storage

44. DG Influence on Network Design
State with DGmax, Lmin – Voltage Problem

45. DG Influence on Network Design
State with DGmax, Lmin – VVO Solution

46. DG Influence on Network Design
State with DGmin, Lmax – Overload Problem

47. DG Influence on Network Design
State with DGmin, Lmax – NR Solution

48. DG Influence on Network Design
State with DGmin, Lmax – Energy Storage Solution

49. 3. Microgrid Optimization
HV BUSBAR
SUPPLY TRANSFORMER
OR
TIE LINE
Weather
Information + Forecast
MV BUSBAR
LOAD CONSUMPTION
CONVENTIONAL
GENERATION
(Hydro, gas, CHP)
SOLAR UNITS
WIND UNITS
STORAGE UNITS

50. Microgrid Management with ADMS
●
●
●
●
●
Provide monitoring of microgrid level resources
Identify capabilities of generators; especially renewables
Determine historical behavior of renewables (vs. weather input)
Provide monitoring of interchange through supply transformer or tie line
Provide forecast of load and renewable production (weather monitoring
plus weather forecast)
● Calculate costs/benefits of microgrid operation, including forecasting
● Optimize operation of utility resources (“regional islanding”)
MV BUSBAR
LOAD CONSUMPTION
CONVENTIONAL
GENERATION
(Hydro, gas, CHP)
SOLAR UNITS
WIND UNITS
STORAGE UNITS

51. Island Operation?
● Real islanding (no connection with main grid) is typically forbidden
● Possible, but not primary goal
● Islanding requires much more investment and tuning
● Load shedding to balance island production and consumption at the
moment of islanding
● Is stable frequency required? If yes, effective and efficient under frequency
protection is required to align imbalance at any moment
● Regulating unit capable of keeping stable frequency
● e.g. CHP of 10 MW has ramp up about 50 kW/sec; economic threshold
for e.g. CHP is above 4000h/year
● hydro unit can have even greater ramp up, but ramp down can be a
problem

52. Application Support for Microgrids
● Applications:
● Automatic Generation Control – AGC
● Economic Dispatching – ED
● Unit Commitment – UC
● Load Forecasts – LF
● Renewable Production Forecast – RPF
● Load Shedding – LS
● Interchange Transaction Scheduler – ITS
● Additionally, ADMS applications can be
added for monitoring/control when the full
network model is used
● Product Focus
● ADMS for Distribution
● EMS for Transmission
● PCS for Generation
● Convergence of Systems

53. Managing and Optimizing DG with ADMS
● Complete, real-time and off-line model of the distribution grid
● Insight into grid state in the presence of DGs and DERs
● Conditions during reverse power flow
● Support operations and planning
ADMS provides insight
● Capacity planning
● Load growth
● New DG/DER connections (what-if analysis)
● Load and power forecasting
● Near-term (hours) and short-term (days) forecasting
● DER operations and optimization
● Network simulations
● Relay protection coordination
● DER to shape the daily load curve
● Advanced DMS operations
● Volt/VAR Optimization
● Fault Location, Isolation, Supply Restoration
into all areas of grid
operations

54. Summary
●Schneider Electric has a long history of applying technology
to solve complex problems for utilities
●Advanced systems like those provided by Schneider Electric
can balance and optimize supply and demand and provide
reliable, safe, and affordable power in the presence of highly
variable renewable resources
●Integrations between applications are an integral part of
these advanced systems
●Sophisticated Load Forecast and Renewable Forecast
algorithms based on input from Weather Systems are a
critical component of renewable optimization

55. Thank You!
John Dirkman, PE
Sr. Product Manager
Schneider Electric
john.dirkman@schneider-electric.com
http://www.linkedin.com/in/dirkman
23 October 2013