基于用户电器分类的智能电网实时定价研究

doi:10.16381/j.cnki.issn1003-207x.2019.04.020

中国管理科学 ›› 2019, Vol. 27 ›› Issue (4): 210-216.doi: 10.16381/j.cnki.issn1003-207x.2019.04.020

• 论文 • 上一篇

基于用户电器分类的智能电网实时定价研究

李军祥, 张文财, 高岩

上海理工大学管理学院, 上海 200093

收稿日期:2017-01-22 修回日期:2017-07-08 出版日期:2019-04-20 发布日期:2019-06-12
通讯作者: 李军祥(1971-),男(汉族),山东人,上海理工大学管理学院副教授,博士/博士后,博导,研究方向:系统工程、管理科学与工程,E-mail:lijx@usst.edu.cn. E-mail:lijx@usst.edu.cn
基金资助:
国家自然科学基金资助项目（71572113，71432007，71202065）；上海市高峰高原学科项目（XTKX2012，S1201YLXK）；国家自然科学基金匹配项目（1P1630 3003，2017KJFZ024）；上海市大学生创新项目（SH2016 064，SH2017062，XJ2017090，XJ2017 091，XJ20171105）

Research on Real-time Pricing Based on the Classification of the User's Electrical Appliances in Smart Grid

LI Jun-xiang, ZHANG Wen-cai, GAO Yan

Business School, University of Shanghai for Science and Technology, Shanghai 200093, China

Received:2017-01-22 Revised:2017-07-08 Online:2019-04-20 Published:2019-06-12

摘要/Abstract

摘要： 目前，电力运行环境日趋复杂，电力体制改革也在不断进行。针对电力行业逐渐向信息化转变、能源利用率较低以及用户与电力公司交互性不高的现状，提出了一种电器分类实时定价模型。该模型根据不同类型用户的用电器进行分类，电力公司根据不同类型电器的用电情况实时制定出不同种类电器的用电价格，以便引导用户在不同时段根据不同类型电器的电价来使用电器，控制居民的用电行为。智能电表的使用，可使用户了解到不同电器的实时电价，并以此调整使用电器，电力公司也随时得到用户的用电量来调整电价和供电量，达到削峰填谷的作用。此模型既有时效性也能使供需双方用电效用最大化。最后通过数值实验对比分析，结果验证了所提出的模型的有效性。

关键词: 智能电网, 实时定价, 削峰填谷, 电器识别

Abstract: The current electric power operation environment is increasingly becoming complex and the reform of the electric power system is on the way. For the situation that the power industry is gradually depending on information, energy efficiency is low and the current interactivity between the user and the electric power company is not frequent. A real-time pricing model basing on classification of electrical appliances is developed, in which the electrical appliances can be divided into categories according to their use for different kinds of users, and then be real-timely made into different electric prices of using the appliances by the electric power company in order that the users can decide to use these electrical appliances according to the prices. By using smart meters, the subscribers can get the information of the electric prices at any time and adjust the time of using the electric equipment in time. Meanwhile, the electric power company can also know the whole power consumption to adjust the price and supply, by which the electric power can be kept to run smoothly. Thus the peak load is reduced and the electricity in the volley can also be fully utilized.This model is both time-effective and can make the utility of the supply and demand of electricity maximization. Finally, by comparison and analysis of numerical results,the residents can use the same or less electric power to get high degree of satisfaction. The effectiveness of the constructed model and the corresponding method are verified. The proposed model has important theoretical and practical significance to optimize the real time electric pricing system.

Key words: smart grid, real time pricing, load shifting, classification of electrical appliances

中图分类号:

TP391.9

李军祥, 张文财, 高岩. 基于用户电器分类的智能电网实时定价研究[J]. 中国管理科学, 2019, 27(4): 210-216.

LI Jun-xiang, ZHANG Wen-cai, GAO Yan. Research on Real-time Pricing Based on the Classification of the User's Electrical Appliances in Smart Grid[J]. Chinese Journal of Management Science, 2019, 27(4): 210-216.

参考文献

[1] 张东霞,姚良忠,马文媛.中外智能电网发展战略[J].中国电机工程学报,2013,31(1):188-193.

[2] 田世明.智能电网条件下的需求响应关键技术[J].中国电机工程学报,2014,22(2):14-19.

[3] Botterud A, Ilic M D,Wangensteen I. Optimal investments in power generation under centralized and decentralized decision making[J]. IEEE Transactions on Power Systems. 2005, 35(2):254-263.

[4] Gonzalez M, Debusschere V, Bacha S. A load identificationmethod for residential building applications[J]. IEEE International Conference on Industrial Technology. 2012,55(12):84-88.

[5] Li Jing, Yang Honggeng. The investigation of residential load identification technologies[J].Power Systems.2012,20(4):27-29.

[6] 李静,杨洪耕.一种用于家用智能电表的负荷识别方法[J].现代电力.2013,05(12):56-65.

[7] Liao Bin, Ma Rui. Power system load dynamic characteristics identification based on Elman neural network[C]//Intrnational Conference on Electrical and Control Engineering,Yichang, China, September 16-18, 2011.

[8] 刘博, 李军祥,高岩.智能电网分类用户实时电价算法研究[J].计算机应用研究,2017, 34(9):2605-2609.

[9] Kazempour S J,Conejo A J.Strategic bidding for large consumer[J].IEEE Transactionsons Power Systems,2016,30(2):848-856.

[10] 代业明, 高岩, 高红伟, 等.基于需求响应的智能电网实时电价谈判模型[J].中国管理科学,2017, 3(25):130-136.

[11] Wang Qingsi, Liu Mingyan, Jain R.Dynamic pricing of power in Smart-Grid networks[J]. Power Energy. 2012,5(4):121-124.

[12] Bu Shengrong, Yu F R, Liu P X. Dynamic pricing for demand-sid emanagement in the smart grid[J]. Electricity Pricing in Transition,2011,13(7):223-228.

[13] Samadi P, Mohsenian-Rad A H. Optimal real-time pricing algorithm based on utility maximization for smart grid[J]. Journal ofthe Operational Research Society, 2010,21(6):415-420.

[14] Dahleh M, Mitter S. Dynamic pricingand stabilization of supply and demand in modern electric power grids[J]. Science and Engineering,2014,5(12):1130-1143.

[15] Roozbehani M. On the stability of wholesale electricity markets under real-time pricing[J].Optimization and Engineering,2014,4(2):543-548.

[16] Rinehart M. Analysis of competitive electricity markets under a new model of real-time retail pricing[J]. Power Systems,2013,50(1):1911-1918.

基于用户电器分类的智能电网实时定价研究

Research on Real-time Pricing Based on the Classification of the User's Electrical Appliances in Smart Grid

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