关税
激励
电
需求价格弹性
经济
弹性(物理)
需求响应
可再生能源
电价
微观经济学
计量经济学
环境经济学
国际经济学
工程类
材料科学
电气工程
复合材料
作者
Wanlei Xue,Xin Zhao,Yan Li,Ying Mu,Haisheng Tan,Yixin Jia,Xuejie Wang,Huiru Zhao,Yihang Zhao
出处
期刊:Energies
[Multidisciplinary Digital Publishing Institute]
日期:2023-02-06
卷期号:16 (4): 1625-1625
被引量:15
摘要
Building a new power system with renewable energy as its main component is a key measure proposed by China to address the climate change problem. Strengthening demand-side management (DSM) is an important way to promote the development of a new power system. As an important economic incentive measure in DSM, the current TOU tariff is faced with the problem of a weak incentive effect due to the small tariff difference between the peak and valley periods. Against this background, a novel hybrid three-stage seasonal TOU tariff optimization model is proposed in this paper. First, the K-means++ algorithm is adopted to select the typical days of the four seasons through load curve clustering. Then, the price elasticity of the electricity demand model is constructed to calculate the self-elasticity and cross-elasticity in four seasons. Finally, the seasonal TOU tariff optimization model is constructed to determine the optimal TOU tariff. Through the proposed model, the tariff in the peak period has increased by 8.06–15.39%, and the tariff in the valley period has decreased by 18.48–27.95%. The result shows that the load in the peak period has decreased by 4.03–8.02% and the load in the valley period has increased by 6.41–9.75% through the proposed model.
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