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Regular Paper | Open Access

Stochastic Economic Dispatch based Optimal Market Clearing Strategy Considering Flexible Ramping Products Under Wind Power Uncertainties

Haoyong Chen1Jianping Huang1Zhenjia Lin1,2( )Fanqi Huang1Mengshi Li1
School of Electric Power, South China University of Technology, Guangzhou, 510641, China
Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
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Abstract

High penetration level of renewable energy has brought great challenges to operation of power systems, and use of flexible resources (FRs) is becoming increasingly important. Flexibility of power systems can be improved by changing generation arrangements, but the interests of some market participants may be harmed in the process. This study proposes a stochastic economic dispatch model with trading of flexible ramping products (FRPs). To calculate changes in revenue and reasonably compensate units that provide FRs, multisegmented marginal bidding for energy is simulated by linearizing generation cost, and an optimal market clearing strategy for FRPs is developed according to changes in clearing energy and marginal clearing price. Then, the correlation between prediction errors of wind speeds among different wind farms is determined based on a joint distribution function modeled by the copula function, and quasi-Monte Carlo simulation (QMC) is used to generate wind power scenarios. Finally, numerical simulations of modified IEEE-30 and IEEE-118 bus systems is performed with minimum comprehensive cost as the objective function. This verifies the proposed model could effectively deal with wind variability and uncertainty, stabilize the marginal clearing price of the electricity market, and ensure fairness in the market.

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CSEE Journal of Power and Energy Systems
Pages 1525-1535
Cite this article:
Chen H, Huang J, Lin Z, et al. Stochastic Economic Dispatch based Optimal Market Clearing Strategy Considering Flexible Ramping Products Under Wind Power Uncertainties. CSEE Journal of Power and Energy Systems, 2024, 10(4): 1525-1535. https://doi.org/10.17775/CSEEJPES.2021.06340

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Received: 25 August 2021
Revised: 15 March 2022
Accepted: 14 April 2022
Published: 03 March 2023
© 2021 CSEE.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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