Renewable energy time series regulation strategy considering grid flexible load and N-1 faults

Yongkang Xiong, Zhenfeng Zeng, Jianbo Xin, Guanhong Song, Yonghong Xia and Zaide Xu

Energy, 2023, vol. 284, issue C

Abstract: As the proportion of renewable energy in electricity generation continues to increase, the uncertainty of renewable energy has brought significant challenges to power system security. Traditional renewable energy dispatching methods have less research on power system failure risk analysis due to economic considerations. In this paper, a renewable energy time series regulation strategy considering N-1 faults is proposed to improve the power system economy and security. In this strategy, by researching flexible load aggregation models, the time-series regulation model of aggregation loads is determined. Then the network N-1 security analysis divided into generator detection and branch detection is conducted. Determining possible N-1 faults of the system, the scheme minimizes the operating cost and grid risk. Adopting the methods above, the most desired renewable energy time-series regulation results are obtained. The results have shown that after adopting the proposed strategy in the improved system, the solar and wind curtailment volume is reduced by 38.10%, and the operating cost is reduced by 24.60%. In a daily cycle, the maximum power of all branch power overruns at the most risky moment is reduced by 20.36%, and the sum of the total power of all branch power overruns is reduced by 40.30%.

Keywords: Load modeling; Power system faults; Renewable energy sources; Security; Uncertainty (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:284:y:2023:i:c:s0360544223025343

DOI: 10.1016/j.energy.2023.129140

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