Multi-Timescale Optimal Operation Strategy for Renewable Energy Power Systems Based on Inertia Evaluation

Author:

Wang Yang1ORCID,Wang Yifan1,Zhao Zhenghui1ORCID,Zhou Zhiquan1,Hou Zhihao2

Affiliation:

1. School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China

2. Department of Electronic and Electrical Engineering, University of Sheffield, Sheffield S102TN, UK

Abstract

To enhance the operational dependability of renewable energy power systems with high proportions, this study proposes a multi-timescale optimization strategy based on the inertia evaluation model. Firstly, the inertia evaluation model is established based on the factors influencing the inertia demand of the power system, and the concept of the inertia margin coefficient is introduced. Secondly, to address the uncertainties associated with sustainable energy output and the cost of carbon emissions, a multi-timescale optimization operation model is formulated for day-ahead, intraday, and real-time operations, aimed at economic optimization. The output status of each unit is obtained and adjusted in a timely manner in the next stage, while meeting the system’s inertia demand, to derive the final scheduling strategy. Lastly, a sensitivity analysis of the inertia margin coefficient is conducted through simulations to validate the effectiveness and cost-efficiency of the proposed scheduling strategy.

Funder

Scientific Research Start-up Fund for Senior Talents of Jiangsu University

Jiangsu innovation and Entrepreneurship Program

Publisher

MDPI AG

Subject

Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction

Reference28 articles.

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3. National Energy Administration (2022, January 20). Available online: http://www.nea.gov.cn/2022-01/20/c_1310432517.htm.

4. Analysis of “9.28” power outage in Australia and enlightenment to China;Zeng;Autom. Electr. Power Syst.,2017

5. Analysis of "8·9" power outage in Britain and enlightenment to China Power Grid;Sun;Proc. CSEE,2019

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