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Effect of Real-Time Electricity Pricing on Ancillary Service Requirements

Published: 12 June 2018 Publication History

Abstract

The objective of this work is to analyze the effect of real time electricity price (RTP) on the amount of ancillary services required for load balancing in presence of responsive users, information asymmetry and forecast errors in demand and renewable energy sources (RES) generation. We consider a RTP that is determined by the forecasted generation and ramping cost. A community choice aggregator manages the load of all the consumers by setting the price. The consumer's objective is to minimize their overall cost of consumption. Ancillary services are called upon to balance the load in real time.
With zero RES in the power network and a high degree of load flexibility, the proposed RTP flattens and the volatility in demand vanishes. However, in presence of RES the volatility in price and demand is reduced up to an extent and ancillary services are required for load balancing. The amount of ancillary services required increases with forecast errors. We also propose a real time algorithm that approximates the optimal consumer behavior under the complete information setting. Extensive numerical simulations are provided using real data from Pecan Street and Elia Belgium.

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cover image ACM Conferences
e-Energy '18: Proceedings of the Ninth International Conference on Future Energy Systems
June 2018
657 pages
ISBN:9781450357678
DOI:10.1145/3208903
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 12 June 2018

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Author Tags

  1. Real time price design
  2. ancillary service
  3. information asymmetry

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Cited By

View all
  • (2020)Energy Storage Optimization for Grid ReliabilityProceedings of the Eleventh ACM International Conference on Future Energy Systems10.1145/3396851.3402123(516-522)Online publication date: 12-Jun-2020
  • (2020)Sizing and Profitability of Energy Storage for Prosumers in Madeira, Portugal2020 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)10.1109/ISGT45199.2020.9087772(1-5)Online publication date: Feb-2020
  • (2019)Optimal Storage Arbitrage under Net Metering using Linear Programming2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)10.1109/SmartGridComm.2019.8909753(1-7)Online publication date: Oct-2019
  • (2019)Energy storage in Madeira, Portugal: co-optimizing for arbitrage, self-sufficiency, peak shaving and energy backup2019 IEEE Milan PowerTech10.1109/PTC.2019.8810531(1-6)Online publication date: Jun-2019
  • (2019)Co-optimizing Energy Storage for Prosumers using Convex Relaxations2019 20th International Conference on Intelligent System Application to Power Systems (ISAP)10.1109/ISAP48318.2019.9065984(1-7)Online publication date: Dec-2019

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