Modeling Tools for Energy Systems Analysis (MOTESA): Impacts of - - PowerPoint PPT Presentation

Modeling Tools for Energy Systems Analysis (MOTESA): Impacts of Energy Efficiency, Energy Storage, Rooftop PV

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Dalia Patiño Echeverri Duke University Energy Research Conference May 10, 2016

The goal of this presentation

 To present a method/model we have

available to assess the effects of introducing different energy generation and non- generation resources in an electric power system

 In case this method can be used to explore a

questions some of you may have and we can collaborate

 Previous presentation of this resource led to a

collaboration with Angel Peterchev to assess the impacts of deploying the AC battery at the system level

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MOTESA: Production Cost-Based model to simulate operations of a power system

 Two versions representative of

 MISO  DEP/DEC

 Resolution:

 Plant level representation  Day ahead commitment of unit and  Real time dispatch – every 5-10 minutes during a full

year

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Main Goal of Power System Simulation Model

 To explore the effects of different low-carbon

strategies on the performance of Power Systems:

 Economics



Costs of generating electricity



Electricity Prices in the day-ahead and real time



Payments to generators

 Environmental Performance



CO2 and other air emissions from power plant operation



Accounting for the increased emissions from starting-up units and operating at minimum loading levels

 Reliability



Instances of energy imbalance (when demand <> supply)



Instances of reserves shortages (when available reserves are lower than target)

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Motesa’s PCB model

Generator Costs

Energy Cost Spinning Reserve Cost Startup Cost No Load Cost

Day Ahead Unit Commitment

Int Length: 1 hr # Intervals: 24

Real Time Economic Dispatch

Int Length: 5 Mins # Intervals: 1

Repeat Every 5 Minutes

Day Ahead System Reqs

Forecasted Net Load Reserve Requirements Regulation Requirements

Day Ahead Output/ Real Time Input

Commitment (on/off) Schedule

Real-Time Output

Generator Dispatch Market Clearing Price Spin Reserve Dispatch and Price

Generator Parameters

Max Ramp Rates Min/Max Generation Min Uptime Min Downtime

Real-Time System Requirements

Actual Net Load Reserve Requirements

Day Ahead Market Real Time Market

Models Final Outputs Intermediate Outputs Inputs Key

LP or MILP models: Minimize costs (or maximize welfare) subject to constraints Big effort on characterizing the uncertainty on net load Big effort characterizing costs and emissions 3 different types: conv, stochastic, Flexiramp

What are the impacts on costs, reliability and air emissions of

 Roof-top PV  Investments in end-use

energy efficiency

 Deployment of modular

“AC Battery” for central dispatch

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Seed research funding with A Peterchev What are the benefits from this Battery?

impacts on costs, reliability and air emissions AC batteries

 Deployment of modular

“AC Battery” for central dispatch

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Round Trip Efficiency Annual Reduction in Total System Monetized Reliability Benefits Monetized Emission Benefits Total System Benefits % $ $ $ $ 80 2,970,893 90 2,790,746 95 2,959,986 80 200,000 90 300,000 95 300,000 80

• 293,051

90

• 363,868

95

• 244,262

80 2,877,842 90 2,726,878 95 3,015,724

Thank you! Dalia.patino@duke.edu

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