工业大用户分时电价优化方法

doi:10.19595/j.cnki.1000-6753.tces.170105

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摘要

分时电价是需求侧管理的有效手段。综合考虑售电公司和工业大用户双方利益,提出了一种分时电价制定的双层优化模型。该模型的上层模型以售电公司销售收益最大为目标函数,下层模型以工业大用户用电成本最小为目标函数,并考虑了大用户自备电厂生产调度、可调度负荷以及售电公司的购售电特性等因素。针对该模型的复杂性,提出遗传算法和混合整数规划法相结合的混合优化算法,在采用遗传算法解决上层优化模型的同时,利用代数技术将下层模型中非线性部分等价线性化后,使用商用混合整数线性规划求解器求解,并嵌入到遗传算法中,高效地实现了工业大用户分时电价的上、下层协调优化。算例表明,该方法有利于提高售电公司收益及大用户用电方式的调整。

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	舒隽
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关键词 ：分时电价, 工业大用户, 双层优化模型, 遗传算法, 混合整数线性规划法

Abstract：

Time-of-use (TOU) price is an effective method for demand side management. In light of the profit of utility companies and large industrial customers, a bi-level optimization model for setting the optimal TOU price is proposed in this paper. Subjected to the dispatch of the self-provided power plant of the large industrial customers, the shifting loads and the characteristics of the electricity purchasing and sales of the utility company, the objective function of the upper model is to maximize the sales profit of the utility company, while the lower model is devoted to minimize the power consumption cost of the large industrial customers. A hybrid optimization algorithm integrated by genetic algorithm (GA) and mixed integer programing (MIP) is proposed to address the computational complexity. GA is used to figure out the upper model, in which the lower model solved by a commercial MIP optimizer after using algebraic techniques to equivalent linearize the nonlinear part is embedded. Consequently, the coordinated optimization of the upper and lower model is achieved efficiently. The results of the cases show that the proposed method increases the profit of the utility company and improves the electricity consumption pattern of the large industrial customers.

Key words： Time-of-use price large industrial customers bi-level optimization model genetic algorithm mixed integer programing

收稿日期: 2017-01-23 出版日期: 2018-04-12

PACS:

TM9

通讯作者: 关睿女,1993年生,硕士研究生,研究方向为电力市场等。E-mail：guanrui_93@qq.com

作者简介: 舒隽男,1974年生,博士,副教授,研究方向为电力市场、电力系统运行优化、电力系统规划等。E-mail：junshu2000@sohu.com

引用本文:

舒隽, 关睿, 韩冰. 工业大用户分时电价优化方法[J]. 电工技术学报, 2018, 33(7): 1552-1559. Shu Jun, Guan Rui, Han Bing. Method of Optimal Time-of-Use Price for Large Industrial Customers. Transactions of China Electrotechnical Society, 2018, 33(7): 1552-1559.

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https://dgjsxb.ces-transaction.com/CN/10.19595/j.cnki.1000-6753.tces.170105 https://dgjsxb.ces-transaction.com/CN/Y2018/V33/I7/1552

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