Risk Prediction and Optimization of Electricity Retail Market Based on Risk Factors of Electricity Retail Companies

Yongbo Li, Chuan He, Yahai Zhang, Hanhan Qian
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Abstract

With deregulation of electrical market in the China, the electricity retail companies (ERCs) and the electricity retail market (ERM) experiences fast development in the recent years. Different from the generation and transmission market, the retail market is more open to the participators, and has more competition and higher risk. Considering the risk factors e.g. the business scale, the capital, the employee, and the complaints, an optimization model to reduce the risk of the ERCs and ERM with higher predicted risk is newly proposed in this paper, where the risk factors are normalized by the threshold value and the time before quantifying the risk. The risk optimization problem with constraints to adjustable risk factors is nonlinear and solved by the interior point method. The numerical results validate the optimization effect on the risk of the ERCs and the ERM.
基于电力零售企业风险因素的电力零售市场风险预测与优化
近年来,随着中国电力市场的放开,电力零售企业和电力零售市场得到了快速发展。与发电和输电市场不同,零售市场对参与者更开放,竞争更激烈,风险更高。考虑到企业规模、资金、员工、投诉等风险因素,本文提出了一种降低预测风险较高的erc和ERM风险的优化模型,该模型将风险因素通过阈值和时间归一化后再量化风险。具有可调风险因子约束的风险优化问题是非线性的,采用内点法求解。数值结果验证了优化对erc和ERM风险的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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