Capacity Valuation of Demand Response in the Presence of Variable Generation through Monte Carlo Analysis

Gordon Stephen, Andrew Klem

Research output: Contribution to conferencePaperpeer-review

1 Scopus Citations

Abstract

While smart demand-side management technologies have significant potential to support the integration of variable renewable generation sources in the electricity system, rigorously quantifying the contribution of demand response to meeting peak demand remains a challenge due to the nontrivial intertemporal considerations involved in demand response operations. This paper contributes to the field of capacity value by studying the effect of customer participation in DR programs, investigating the contribution that shiftable loads can provide for capacity value in a smart, standalone system. This paper uses a Monte Carlo simulation to investigate the effect of DR on the loss of load probability in a sequential simulation framework. Also presented here is a load-shifting model for customer loads where time of use is based on need, priority, and the availability of generation. Results of this work present a quantitative value for the equivalent firm capacity of demand response programs for a specific test case that depends on the participation rate among consumers.

Original languageAmerican English
Number of pages5
DOIs
StatePublished - Feb 2019
Event2019 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2019 - Washington, United States
Duration: 18 Feb 201921 Feb 2019

Conference

Conference2019 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2019
Country/TerritoryUnited States
CityWashington
Period18/02/1921/02/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

NREL Publication Number

  • NREL/CP-6A20-72871

Keywords

  • Capacity value
  • demand response
  • equivalent firm capacity
  • loss of load expectation
  • Monte Carlo

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