Post on 06-May-2015
description
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
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
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
Residential 9%
Utilities & Infrastructure 25%
Industrial & machines 22%
Data Centers 15%
Non-residential buildings 29%
Delivering Solutions for End Users
the global specialist
in energy management
Some of the world class brands that we have built or acquired in our 175 year history
EPS,
Serbia
ACTEW, Canberra
Australia
Energoprom, Novocheboksary
Russia
ENEL,
Italy
Light Services de Electricitade,
Rio de Janeiro, Brazil
Abu Dhabi,
UAE Tunisia PT-PLN, Banda Aceh,
Indonesia
ANDE, Asuncion,
Paraguay
Murcia, Spain
EDENOR, Buenos Aires,
Argentina
NIH, Washington DC, USA
EDELNOR,
Lima, Peru
CNFL, San Jose,
Costa Rica
Petroproduccion,
Ecuador
EMCALI, Cali,
Columbia
ELECTRA, Panama City,
Panama
Duke/Progress Enrgy,
North Carolina
UofM, Michigan
EMASZ / ELMU, Budapest,
Hungary Guizhou Electric
Corporation, China
IDGC Center Russia, Moscow,
Russia
Maharashtra,
India
Electrica, Cluj,
Romania
Elektro Celje,
Slovenia
Hydro One,
ON, Canada
Railway project,
STEG,
EVN,
Macedonia
PECO,
Philadelphia
EDEN, Buenos Aires province,
Argentina
PT-PLN, Bandung,
Indonesia
Austin Energy,
Texas
EPS
Serbia
EPRS
B&H
EPCG
Montenegro
CFE, Zona Puebla City,
Mexico
Burbank W&P,
California
BC Hydro,
BC, Canada
Medina,
Saudi Arabia
Irkutsk,
Russia
Dong Energy,
Denmark
ETSA, Adelaide
Australia
Unison,
New Zealand
Guangxi Power,
China
Bihar,
India
MEER,
Ecuador
NS Power,
NS, Canada
EPCOR,
AB, Canada
ADMS/PCS Projects Worldwide
Over 180 control centers and 88M meters
Utility Transformation
How do you expect utility business models to be in 2030 compared to
today in your market?
Utility Transformation
Which energy market transformation vision most closely matches your
expectations of your market?
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 Type* Controllable?
Generators Supply Yes
Wind Supply No
Solar Supply No
Interties Supply/Demand Yes
Battery Banks Supply/Demand Yes
Electric Vehicles Supply/Demand Yes
Compressed Air Systems Supply/Demand Yes
Thermal Storage Systems Demand Yes
Demand Response Demand Yes
* Supply-side provides power, Demand-side consumes power or affects consumption
Poll Question 1 – Preparedness
●How prepared is your utility for integration and optimization of
renewables and storage?
●Please select one:
1. Just getting started [38%]
2. Somewhat prepared [15%]
3. Fairly well prepared [15%]
4. Completely prepared but not yet fully integrated and optimized [1%]
5. We are already integrating and optimizing renewables and storage [7%]
6. Unknown [24%]
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.
Impact on Profile ● Impact on profile (left lower corner, gray area is stored energy, while
gray area in peak hours denote discharged energy):
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
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
ADMS Functionality
Train
Plan
Optimize
Operate
Analyze
Monitor
Load Flow
State Estimation
Energy Losses
Fault Calculation
Reliability Analysis
Relay Protection
Device Capability
Contingency Analysis
Fault Management
Switch Management
Crew Management
Under-load Switching
Large Area Restoration
Load Shedding
Telemetry
Alarming
Tagging
Trending
Reporting
Volt/VAR Optimization
Network Reconfiguration
Near and Short-term Load
Forecasting
Demand Response
Distributed Energy Mgmt.
Medium and Long-term
Load Forecasting
Network Automation
Network Reinforcement
Optimal Device Placement
Real-time Simulation
Off-line Simulation
What-if Analysis
Historical Playback
ADMS Benefits
Safety
Reliability
Efficiency
Standardized Training
Unified Interface
Detailed Equipment Usage History
EPS,
Serbia
ACTEW, Canberra
Australia
Energoprom, Novocheboksary
Russia
ENEL,
Italy
Light Services de Electricitade,
Rio de Janeiro, Brazil
Abu Dhabi,
UAE Tunisia PT-PLN, Banda Aceh,
Indonesia
ANDE, Asuncion,
Paraguay
Murcia, Spain
EDENOR, Buenos Aires,
Argentina
NIH, Washington DC, USA
EDELNOR,
Lima, Peru
CNFL, San Jose,
Costa Rica
Petroproduccion,
Ecuador
EMCALI, Cali,
Columbia
ELECTRA, Panama City,
Panama
Duke/Progress Enrgy,
North Carolina
UofM, Michigan
EMASZ / ELMU, Budapest,
Hungary Guizhou Electric
Corporation, China
IDGC Center Russia, Moscow,
Russia
Maharashtra,
India
Electrica, Cluj,
Romania
Elektro Celje,
Slovenia
Hydro One,
ON, Canada
Railway project,
STEG,
EVN,
Macedonia
PECO,
Philadelphia
EDEN, Buenos Aires province,
Argentina
PT-PLN, Bandung,
Indonesia
Austin Energy,
Texas
EPS
Serbia
EPRS
B&H
EPCG
Montenegro
CFE, Zona Puebla City,
Mexico
Burbank W&P,
California
BC Hydro,
BC, Canada
Medina,
Saudi Arabia
Irkutsk,
Russia
Dong Energy,
Denmark
ETSA, Adelaide
Australia
Unison,
New Zealand
Guangxi Power,
China
Bihar,
India
MEER,
Ecuador
NS Power,
NS, Canada
EPCOR,
AB, Canada
ADMS/PCS Projects Worldwide
Over 180 control centers and 88M meters
Renewable Resource Commitment
● In June 2007, the Burbank City
Council adopted BWP's
recommendation that 33% of
electricity be procured from
renewable resources by 2020
●Burbank was the first city in the
United States to step up to this
ambitious goal
●Burbank now seeks to obtain
66% of electricity from
renewable resources by 2025
●Renewables will be a
combination of primarily wind,
solar, and compressed air
storage systems
Renewable Resource Variability
185 MW
20 MW
170 MW
10 MW
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
Integrated Automatic Dispatch System
(iADS)
18
PCS/SCADA
(LF, RF, AGC)
(Schneider Elec)
GIS/OMS
(Schneider Elec) ADS/AGC
(OATI)
Wholesale &
Market
Operations
(OATI)
AMI (Trilliant)
MDMS (eMeter)
CIS
(Oracle CC&B)
Balancing Authority Trading Partners
Wholesale Markets
Fiber/wireless networks/Internet
Customer
Portal
Distributed
Generation Energy
Storage
Demand
Response
Ice Bear
TES units
Building
Mgmt
System
Weather Service
(Schneider Elec)
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%]
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
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
Current Situation
Smart Field
Devices
???
Buildings
Houses + Electrical Vehicles
Weather
Stations
Wind
Generation
Smart
Devices
Solar
Panels Distribution utilities face new challenges
CHP Plants
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
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)
Load Forecasting 90% of demand variation
due to weather
Wind Power Highly variable, difficult to predict.
Causes increases in spinning reserve
generation and risk of grid instability
● 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 Temperature,
humidity and wind
impact line capacity
Distribution Weather is largest cause of
outages (lightning, high winds,
ice, transformer failures due to
high load, etc.)
Distributed Generation Home solar contributions can cause
system instability due to rapid cloud
cover changes
Trading Improved prediction of load
and renewable energy
contribution improves trading
decisions
WeatherSentry
WindPower Forecasts Solar Power Forecasts
Schneider Electric – Dominant Weather
Provider to the Energy Industry in North
America
● #1 for transmission and distribution
crew management
● Weather integrated into OMS & DMS
SmartGrid systems
● Renewable energy services:
● 73% of US wind farms use Schneider
Electric lightning safety alerting
● Advanced wind power and solar
forecasting
● 70% of generation in U.S.
electric industry uses
Schneider Electric weather
forecasts for load modeling
● Largest energy weather provider
in U.S.
● A $30 billion global energy leader
● Rapid growth internationally
● Schneider Electric is an ADMS
leader
Forecasting Accuracy Results
Typical results for a single wind plant
Forecast Horizon MAPE* of Rated
Capacity
Hour-ahead to next 12 hours 6-12%
Day-ahead (hour 30) 12-18%
Days 3-7 18-20%
What accuracy are you
currently receiving?
MAPE = Mean Absolute Percentage Error
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
• 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
1/3 of Forecast Error
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 well-
forecasted
days in
advance
P20 Forecast Power
Actual Power
P50 Forecast Power
P80 Forecast Power
DTN Solar Forecasting Experience
Utility-scale solar irradiance forecasting
● PV (Photovoltaic) and
● CSP (Concentrated Solar Power),
including Abengoa Solar
Distributed solar projects,
for utilities
Providing solar irradiance
forecasts to many utilities
for load forecasting
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)
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
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
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
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)
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
Full Network State Visibility
Voltage Profiles – no DG (open)
Voltage Profiles – with DG (closed)
Short Circuit Current
Near Term Operation Planning
supported by Weather Forecast Inputs
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.
Overload problem
S4.2 Load Management + Reconfiguration
S4.4 Energy Storage
No problem
Load
DG
S1.0 - DGmaxLoadmax
No problem
S3.0 - DGmaxLoadmin
S4.0 - DGminLoadmax
S2.0 - DGminLoadmin
S3.1 Volt/VAR Optimization (VVO)
Voltage problem
S4.3 Demand Response
S4.1 Cable Reinforcement S0.0 S0.1
Planning Variants
DG Influence on Network Design State with DGmax, Lmin – Voltage Problem
State with DGmax, Lmin – VVO Solution
DG Influence on Network Design
DG Influence on Network Design State with DGmin, Lmax – Overload Problem
DG Influence on Network Design State with DGmin, Lmax – NR Solution
DG Influence on Network Design State with DGmin, Lmax – Energy Storage Solution
3. Microgrid Optimization
WIND UNITS
CONVENTIONAL
GENERATION
(Hydro, gas, CHP)
MV BUSBAR
HV BUSBAR
LOAD CONSUMPTION STORAGE UNITS
SUPPLY TRANSFORMER
OR
TIE LINE
Weather
Information + Forecast
SOLAR UNITS
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
WIND UNITS
CONVENTIONAL
GENERATION
(Hydro, gas, CHP)
LOAD CONSUMPTION STORAGE UNITS SOLAR UNITS
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
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
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
●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
ADMS provides insight
into all areas of grid
operations
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
Thank You!
John Dirkman, PE
Sr. Product Manager
Schneider Electric
john.dirkman@schneider-electric.com
http://www.linkedin.com/in/dirkman
23 October 2013