基于优惠券激励的需求响应双层优化机制
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(电力系统广域测量与控制四川省重点实验室,电子科技大学机械与电气工程学院,四川 成都 611731)

作者简介:

王 均(1988—),男,博士研究生,从事配电网优化、需求侧管理工作;E-mail:jwuestc@gmail.com
黄 琦(1976—),男,博士,教授,博导,从事电力系统分析、智能电网工作。

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四川青年科技基金项目资助(2017TD0009)


Coupon incentives based customers voluntary demand response program via bilevel optimization mechanism
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(Sichuan Provincial Key Lab of Power System Wide Area Measurement and Control, School of Mechanical and Electrical Engineering (University of Electronic Science and Technology of China), Chengdu 611731, China)

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    摘要:

    提出了一种用户自主参与的需求响应(Customer Voluntary Demand Response, CVDR)计划,电力企业为用户提供优惠券激励,鼓励用户在尖峰电价时减少用电需求。电力企业通过实施CVDR计划降低自身尖峰电价的购电经济损失,同时用户在优惠券激励作用下提升收益。因此提出了电力企业和用户之间合作博弈的双层优化模型,结合Karush-Kuhn-Tucker条件和Big-M法将双层优化转化为一个单层混合整数线性问题进行求解。算例仿真采用居民和小商业配电网,通过数值分析验证CVDR计划增强了用户的收益,减少了电力企业经济损失,实现了调峰需求。

    Abstract:

    This paper proposes a Customer Voluntary Demand Response (CVDR) program, in which the Load Serving Entity (LSE) caters coupon rebates to customers for demand reduction during peak pricing. With the implementation of CVDR program, LSE reduces economic losses during peak pricing and customers improve profits with coupon incentives simultaneously. Therefore, a bilevel programming for LSE and customers cooperative game is formulated in CVDR program. Karush-Kuhn-Tucker optimality condition and Big-M method are used to transfer the bilevel programming to a single level mixed integer linear programming problem. Numerical studies are examined with a residential and small commercial radial network. Simulation results unveil that the proposed CVDR program enhances customers’ profits, reduces LSE economic losses and realizes the demand for peak shaving. This work is supported by Youth Science and Technology Innovation Fund of Sichuan Province (No. 2017TD0009).

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王均,黄琦.基于优惠券激励的需求响应双层优化机制[J].电力系统保护与控制,2019,47(1):108-114.[WANG Jun, HUANG Qi. Coupon incentives based customers voluntary demand response program via bilevel optimization mechanism[J]. Power System Protection and Control,2019,V47(1):108-114]

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  • 收稿日期:2017-12-16
  • 最后修改日期:2018-01-27
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  • 在线发布日期: 2019-01-06
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