Vi t l P Pl t b SiVirtual Power Plants by Siemens
DEMS® – Decentralized Energy Management System
© Siemens AG 2013. All rights reserved.
Key Challenges Drive Implementation of Demand Response & Virtual Power Plants
Trends Customer challenges
Generation & network bottlenecks Generation & network capacity bottlenecks:E.g. California, US
Increasing peak load prices
Increasing peak load prices:E.g. Germany 6% in 2009Dispatch load as most economic power supply: A id f ti & t k b ttl k d
Increasing distributed &
Avoidance of generation & network bottlenecks and high peak load pricesIncreased grid stability through emergency load shed & selective load dispatchIncreasing distributed &
renewable generationshed & selective load dispatchNew market opportunities for distributed energy resources
Rising consumption
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Demand Response & Virtual Power Plant –Current Portfolio of Siemens Smart Grid
Virtual Power Plant Integrated Solutions
Grid-specificEnterprise IT
Business consulting for identification & analysis of customer business modelsEnergy management system for monitoring planning
Business analytics, IT integration
Operational ITEnergy management system for monitoring, planning and optimized operation of DER, loads & storageFully automated demand response management system: DRMS platform for load aggregation and
Demand response management system (DRMS) , decentralized energy management system (DEMS)
Information &Communication
y p gg genablementForecasting system for consumption and renewable generation
f
Support of standard communication protocols like IEC 104 and OPC, etc. over public/private TCP/IP networks
Automation
Field
Linking together a number of individual plants to be combined to form a large-scale virtual power plant
Optimized operation of decentralized Optimized operation of decentralized
Distributed energy resources (DER) controller
DER controller load controllerEquipmentp penergy resources, load & storage,
enabling trading of energy flexibility at minimized risk.
p penergy resources, load & storage,
enabling trading of energy flexibility at minimized risk.
Smart GridServices
DER controller, load controller
Consulting, system installation & maintenancesite enrollment & enablement
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Services site enrollment & enablement
Virtual Power Plants
A Virtual Power Plant (VPP) is a cluster of distributed energy resources (generationA Virtual Power Plant (VPP) is a cluster of distributed energy resources (generation, controllable loads and storages such as microCHP, wind-turbines, small hydro, back-up
gensets, flexible loads, batteries etc.) which are collectively run by a central control entity.
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Virtual Power Plants:Technical Structure and Use Cases
Network ControlSystem
EnergyExchange Billing
SchedulingLoad Forecast
Biomass Power Plant
MeteorologicalService
g
Load Balancing Block type
Flexible Loads
®Aggregation of DER1
Block-typeHeating Power Plant DEMS®
PV PowerPlants
Wind FarmsDistributed Small
Fuel Cell
Fuel CellsDistributed Loads
Storage
Automatic Generation Control
Renewable Generation Forecast
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1 DER = Distributed Energy Resource Communication Unit
Three Main Target Groups for Customers for Virtual Power Plants
Use Case Target CustomersFacilitate participation in energy
trading/participate in markets for reserve capacity Aggregators and utilitiescapacity
(day ahead and reserve markets)
Operators with larger generation units with
To optimize of fleet management and ensure compliance with fleet schedule
p g g- More than one generation source¹/converter² and/or
- Different modalities of energy (e.g. electricity heat)electricity, heat)
Industries and municipalities with their own- Generation source and/orEconomic optimization of energy costs - Generation source and/or
- Load control- Storage³
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¹Including Boilers, turbines, CHP, fuel cells, renewables ²Including compressors, chillers, electrolysis ³Including heat/cold storage, accumulators, e-cars
DEMS® for Load Balancing
Energy Data- Acquisition
Archiving- Archiving- Reporting- MonitoringEnergy contracts
Production plan
®
Supply Monitoring- Natural Gas- Electricity
energy$optimize
Production plan
Operator inputs
®
Load Forecast- Electricity
Steam
energycost
savings$short-term
purchasingon the market
Process control
Quality information- Steam
- Natural Gas
Optimization
Field information
Energy counterOptimization - Unit Commitment
- Fuels- Contracts
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DEMS® – Decentralized Energy Management System
DEMS® – Decentralized Energy Management System
Load ForecastForecast of Renewable G ti
User InterfaceSCADA ArchiveGeneration SCADA
(Supervisory Control andData Acquisition)
SchedulingAutomatic Generation Reports Market Interfacesg
Controlp
Communication
®DEMS®
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Virtual Power Plant Application for Electric Utilities
ISO (Day Ahead and Real Time Market)ISO (Day Ahead and Real Time Market)
Energy MarketEnergy Market Operating ReservesMarket
Operating ReservesMarket
Optimization of Generation and Demand Portfolio
Offer the delta generation (Gen – Load) to the Energy and Operating Reserves market (when load < PPA + DG). Aggregate and optimize the Energy Market Energy Market Energy Market Energy Market ) gg g pschedules of available generation during the bidding phase.
Coordinate between participation in energy market$ MWh $ MWh
gyPurchase
gyPurchase
gySellinggy
Selling
Base Load Generation Resources
IntermittentGeneration Resources
Coordinate between participation in energy market and/or operating reserve market
Maximize the benefit (Revenue – Cost): Cost of
Electric Utility
Generation Resources(PPA and/or own)
Peak LoadG ti R
Generation Resources(PV/Wind: PPA or own)
Load Following
operating own generation (vs.) purchasing from energy market
Curtailment of interruptible load as per theGeneration Resources(Distributed Generation)
gGeneration Resources
Retail Consumers(Load)
Curtailment of interruptible load as per the available load reduction programs
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(Load)
DEMS® – Data Model
ConsumerElectricity
ContractsDelivery
ConsumerGas
ConsumerHeat
ConsumerHeat
EmissionCO2
BalanceElectricity
BalanceHeat
ConnectionHeat
BalanceHeat
BalanceCOElectricity Heat Heat Heat CO2
CHP FuelcellWind PhotovoltaicCHP
BalanceGas
BalanceBiomass Gas
AcquisitionGas
Biomass
AcquisitionBiomass
AcquisitionElectricity
DEMS®
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GasBiomass Electricity
DEMS® – Data Model
Energy / Media Purchase / Sales Contracts Primary energy consumption Bilateral electricity purchase / sales Energy markets (day ahead and reserve markets)
Energy / Media Demands Non-flexible loads Switchable loadsSwitchable loads Time controllable loads
RenewablesRenewables Wind power Photovoltaic Small hydro power Solar thermal Geothermal
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DEMS® – Data Model
Energy / Media Converters Boilers, Turbines, CHP, Fuel Cells Compressors, Chillers, Electrolysis
Energy / Media Storages Heat / Cold Storage Accumulators, E-Cars Media StorageMedia Storage
Emissions CO SOX NOX CO2, SOX, NOX, …
Electric system reserve considerationF t t i ti Forecast uncertainties
Own reserve capacity Sellable reserve or imbalance risk
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DEMS® – Forecast Function
Import from meteorological service
Multi Area Weather Forecast
Refine imported forecasts with local online measurements
Forecast model: Day types, calendar, weather data, production schedules trends
Load ForecastTime Grid:
15/30/60 Minschedules, trends Continuous self adapting model coefficient training Kalman filter allows dynamic, partly static or fully static forecast models
15/30/60 Min.
Horizon: Up to 7 days ahead
Forecast uncertainty (bandwidth) calculation
Renewable Generation
7 days ahead
Plant characteristic (power as function of weather) is analyzed in offline stepF t t i t (b d idth) l l ti
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Forecast uncertainty (bandwidth) calculation
DEMS® – Scheduling Functions
Scheduling Cost / revenue optimized scheduling of all flexible resources
C id ti f / di fl t l Consideration of energy / media flow topology Consideration of:
Reserve / risk strategygy Technical constraints of all modeled elements Environmental constraint of all modeled elements Time Grid:
15/30/60 Min.Time Grid:
15/30/60 Min. Contractual constraints of all modeled elements Fuel prices, contract prices and market options Actual process status and operating point
15/30/60 Min.
Horizon: Up to 7 days ahead
15/30/60 Min.
Horizon: Up to 7 days ahead Actual process status and operating point
Includes DSM concepts already in the operations planning phase Problem solution algorithm MILP is used
yy
Calculation of Power and commitment schedules
R l ti t d th h d l d b i t
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Regulation costs around the scheduled power base points
DEMS® – Online Functions
General Cycle Time: typically 1 Minute or lower
Multi Area Exchange Monitoring Supervision of electrical “interchange” of areap g Comparison with scheduled commitment for area Energy (15/30/60 Minutes interval) or flat power area regulation mode Minute reserve monitoring Minute reserve monitoring Reaction on market reserve call Calculation of required area power correction term
Online Optimization Distribution of required area power correction term to all objects in regulating modeDistribution of required area power correction term to all objects in regulating mode Usage of storage, flexible demands and flexible generating units Preference for elements with lowest regulation costs calculated by the scheduling
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Generation Management
DEMS® – Online Functions
Generation Management Unit operation modes: Independent, Manual, Scheduled, Regulating Considering technical constraints of units Considering actual unit states (disturbed, on/off, local/remote control) Start / Stop command and set point control Supervision of unit command and set point following behaviorSupervision of unit command and set point following behavior Applicable to storages and generating units Including active and reactive power set points
Load Management Load operation modes: Independent, Scheduled, Regulating Prioritization of load classes via their regulating costs Prioritization of load classes via their regulating costs One load class (continuous model) has several load groups (discrete model) Rotational load switching of load groups of one load class for continuous regulation Consideration of
Actual load state (on/off, local remote, dead time) Actual power when switching off
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p g Nominal power & switching risk factor when switching on
Virtual Power Plant – RWE ProVippAggregation of Generation + Minute Reserve Market
Integration of multiple renewable energy resources
Challenge
Defining of various operation strategies Implementation of an optimal operation strategy for distributed generation
Build up a virtual power plant integrating small hydro power plants combined heat and power units
Solution Build up a virtual power plant integrating small hydro power plants, combined heat and power units,
and emergency generators based on DEMS®
DER*-Controller for innovative communication with DEMS®
Benefits
P j t t RWE
Allows market access for distributed energy resources Increases the economical benefit of distributed energy resources Provides regulating energy to reserve markets
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Project partner: RWECountry: Germany *DER = Distributed Energy Resource
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Case Study ProViPP – Virtual Power Plant for RWE
DEMS Decentralized Energy
in Operation Since 31-Oct-2008
DEMS – Decentralized Energy Management System
9 Small hydro units (8,6 MVA). Additional units will be connected in the next weeks
Hamburg
Schleswig-Holstein
Mecklenburg-Vorpommern
Project Focus: Development of a marketable Virtual Power Plant
Niedersachsen
BremenBrandenburg
Berlin
Sachsen-Anhalt
Definition of business models in different energy markets
Definition and implementation of optimalNordrhein-Westfalen
Sachen
Anhalt
ThüringenHessen
Definition and implementation of optimal operation strategies for distributed generation
Implementation of innovative communication Rheinland-
Pfalz
Saarland
pconcepts between distributed generation and DEMS
Baden-Württemberg
Bayern
P j t t RWE
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Project partner: RWECountry: Germany
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Stadtwerke München (SWM) –Start up Virtual Power Plant
Stadtwerke München (SWM)Key Features
Integration of 6 unit-type cogeneration modules, 5 hydropower plants and 1 wind farm to form a virtual power plantplants and 1 wind farm to form a virtual power plant
Scope is the distributed energy management system DEMS
A t t d d l t d t di h d l b d t Automated deployment and trading schedule based on exact usage and generation forecasts
C fCustomer Benefits
Opens up further marketing alternatives for distributed energy sourcessources
Minimization of generation and operational costs
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Our Technology – Your Future
Already today, Siemens DEMS® and Siemens DER-Controller offer the technical basis for managing distributed energy systems.
Your Benefits:Your Benefits:
Use of synergies by aggregating distributed generation
Achievement of remarkable economical and ecological benefits
Obtaining new market opportunities for distributed generation Obtaining new market opportunities for distributed generation
Support of new operation concepts like virtual power plants
Create your future energy system with DEMS® !
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Comprehensive Modeling of power system elementsComprehensive Modeling of power system elements1
10 Good Reasons for DEMS®
Comprehensive Modeling of power system elementsComprehensive Modeling of power system elements1
Intelligent forecasting and planning using advanced mathematical techniquesIntelligent forecasting and planning using advanced mathematical techniques2
Integral consideration of all resourcesIntegral consideration of all resources3
Open interfaces for a seamless integration into the IT environmentOpen interfaces for a seamless integration into the IT environment4 Open interfaces for a seamless integration into the IT-environmentOpen interfaces for a seamless integration into the IT-environment4
Workflow support to reduce operators’ workloadWorkflow support to reduce operators’ workload5
Preparation of a solid background for energy trading decisions Preparation of a solid background for energy trading decisions 6
Simple real time operationSimple real time operation6
Clear, straightforward operationClear, straightforward operation8
Simple real-time operationSimple real-time operation6
Scalable systemScalable system9
Decentralized power generation with the character of a power plantDecentralized power generation with the character of a power plant10
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Decentralized power generation with the character of a power plantDecentralized power generation with the character of a power plant10
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