负荷聚合商多类型需求侧资源激励价格制定一般模型及应用

doi:10.12204/j.issn.1000-7229.2021.01.001

摘要/Abstract

摘要：

负荷聚合商通过整合需求侧可调资源参与系统运行交易获利,是开展电力需求响应的专业机构。实现多类型需求响应资源的个性化激励定制对进一步灵活管理需求侧资源和增加需求响应效益至关重要,是负荷聚合商核心业务。基于主从博弈原理建立了负荷聚合商激励价格定制通用模型,选取了电动汽车用户及楼宇空调用户,考虑舒适度价格随削减负荷变化情况,在主从博弈架构下构建了含不同舒适度价格需求的楼宇空调用户优化模型和电动汽车充放电行为优化模型。结合Karush-Kuhn-Tucker条件、对偶定理和线性松弛等方法,在负荷聚合商经济损失最小基础上推导出含楼宇空调和电动汽车需求响应激励价格制定的单层混合整数线性规划优化模型。算例表明,所提出的模型可用于负荷聚合商定制楼宇空调用户和电动汽车用户动态激励价格,为负荷聚合商开展需求响应提供参考。

关键词: 负荷聚合商, 楼宇空调, 电动汽车, 激励, 利润

Abstract:

A load aggregator is a professional organization to develop power demand response, which integrates demand-side adjustable resources to participate in system operation and market transactions to gain profits. It is very important for further flexible management of demand-side resources and increasing demand-response benefit to realize personalized incentive customization of multiple types of demand-response resources. It is also the core business of load aggregators. In this paper, a general model of incentive price customization for load aggregators is established according to the principle of stackelberg game. Electric-vehicle users and building air-conditioning users are selected as the research object. Considering the impact of comfort price changing with load shedding, an optimization model of building air-conditioning users with different comfort prices and a model for optimizing the charge and discharge behavior of electric vehicles are constructed under the framework of stackelberg game model. Karush-Kuhn-Tucker condition, dual theorem and linear relaxation are used to derive a two-level mixed integer linear programming model with the minimum economic loss of load aggregator. The results show that the proposed model can be effectively used to customize dynamic incentive price of building air-conditioning users and electric-vehicle users for load aggregators, and provide new ideas for demand response.

Key words: load aggregator, building air conditioning, electric vehicle, incentive, profit

中图分类号:

TM73

吴宛潞, 韩帅, 孙乐平, 郭小璇. 负荷聚合商多类型需求侧资源激励价格制定一般模型及应用[J]. 电力建设, 2021, 42(1): 1-9.

WU Wanlu, HAN Shuai, SUN Leping, GUO Xiaoxuan. A General Incentive Pricing Model and Its Application for Multi-type Demand-Side Resources of Load Aggregators[J]. ELECTRIC POWER CONSTRUCTION, 2021, 42(1): 1-9.

图/表 11

图1 双层问题结构

Fig.1 Architecture of a two-level problem

图2 负荷聚合商与用户的主从博弈架构

Fig.2 Framework of stackelberg game model between LA and users

图3 舒适度成本随着削减负荷变化曲线

Fig.3 Curve of comfort cost versus reduced load

图4 舒适度价格随着削减负荷变化曲线

Fig.4 Curve of comfort price versus reduced load

表1 楼宇空调参数

Table 1 Parameters of BAC

图5 负荷及室外环境温度预测值

Fig.5 Forecast value of load and outdoor air temperature

表2 用户舒适度价格

Table 2 Comfort price of user

图6 电力批发价格和零售电价

Fig.6 Wholesale price of power and retail rate

表3 不同场景下负荷聚合商利润

Table 3 Profit of the load aggregator in different scenarios

表4 用户参与需求响应效益比较

Table 4 Benefit of users participating in demand response

图7 场景4下的仿真结果

Fig.7 Simulation results under scenario 4

参考文献 16

[1]	张钦, 王锡凡, 王建学 , 等. 电力市场下需求响应研究综述[J]. 电力系统自动化, 2008,32(3):97-106.
	ZHANG Qin, WANG Xifan, WANG Jianxue , et al. Survey of demand response research in deregulated electricity markets[J]. Automation of Electric Power Systems, 2008,32(3):97-106.
[2]	曾鸣, 韩旭, 孙静惠 , 等. 能源互联网背景下自动需求响应关键问题及展望[J]. 电力建设, 2017,38(2):21-27.
	ZENG Ming, HAN Xu, SUN Jinghui , et al. Key issues and prospects of automated demand response under energy Internet background[J]. Electric Power Construction, 2017,38(2):21-27.
[3]	高赐威, 李倩玉, 李慧星 , 等. 基于负荷聚合商业务的需求响应资源整合方法与运营机制[J]. 电力系统自动化, 2013,37(17):78-86. doi: 10.7500/AEPS201211091 URL
	GAO Ciwei, LI Qianyu, LI Huixing , et al. Methodology and operation mechanism of demand response resources integration based on load aggregator[J]. Automation of Electric Power Systems, 2013,37(17):78-86. doi: 10.7500/AEPS201211091 URL
[4]	陈璐, 杨永标, 姚建国 , 等. 基于电力积分的需求响应激励机制设计[J]. 电力系统自动化, 2013,37(18):82-87. doi: 10.7500/AEPS201208245 URL
	CHEN Lu, YANG Yongbiao, YAO Jianguo , et al. Incentive mechanism design for demand response based on power score[J]. Automation of Electric Power Systems, 2013,37(18):82-87. doi: 10.7500/AEPS201208245 URL
[5]	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, 2019,47(1):108-114.
[6]	李媛, 冯昌森, 文福拴 , 等. 含电动汽车和电转气的园区能源互联网能源定价与管理[J]. 电力系统自动化, 2018,42(16):1-10.
	LI Yuan, FENG Changsen, WEN Fushuan , et al. Energy pricing and management for park-level energy internets with electric vehicles and power-to-gas devices[J]. Automation of Electric Power Systems, 2018,42(16):1-10.
[7]	董军, 张晓虎, 李春雪 , 等. 自动需求响应背景下考虑用户满意度的分时电价最优制定策略[J]. 电力自动化设备, 2016,36(7):67-73.
	DONG Jun, ZHANG Xiaohu, LI Chunxue , et al. Optimal TOU pricing strategy considering user satisfaction in automated demand response background[J]. Electric Power Automation Equipment, 2016,36(7):67-73.
[8]	张高, 王旭, 蒋传文 . 基于主从博弈的含电动汽车虚拟电厂协调调度[J]. 电力系统自动化, 2018,42(11):48-55.
	ZHANG Gao, WANG Xu, JIANG Chuanwen . Stackelberg game based coordinated dispatch of virtual power plant considering electric vehicle management[J]. Automation of Electric Power Systems, 2018,42(11):48-55.
[9]	宋梦, 高赐威, 苏卫华 . 面向需求响应应用的空调负荷建模及控制[J]. 电力系统自动化, 2016,40(14):158-167.
	SONG Meng, GAO Ciwei, SU Weihua . Modeling and controlling of air-conditioning load for demand response applications[J]. Automation of Electric Power Systems, 2016,40(14):158-167.
[10]	黄海涛, 王岱锋, 朱丰泽 , 等. 考虑热舒适度的变频空调响应调控策略[J]. 电力建设, 2018,39(9):9-17.
	HUANG Haitao, WANG Daifeng, ZHU Fengze , et al. Study on the control strategy of frequency conversion air conditioning considering thermal comfort[J]. Electric Power Construction, 2018,39(9):9-17.
[11]	辛洁晴, 吴亮 . 商务楼中央空调周期性暂停分档控制策略[J]. 电力系统自动化, 2013,37(5):49-54. doi: 10.7500/AEPS201204161 URL
	XIN Jieqing, WU Liang . Hierarchical strategies for duty cycling control of air conditioners in business buildings[J]. Automation of Electric Power Systems, 2013,37(5):49-54. doi: 10.7500/AEPS201204161 URL
[12]	ZENG B, ZHAO L . Solving two-stage robust optimization problems using a column-and-constraint generation method[J]. Operations Research Letters, 2013,41(5):457-461. doi: 10.1016/j.orl.2013.05.003 URL
[13]	Residential module user’s guide [EB/OL]. [ 2020- 03- 22]. http://gridlab-d.shoutwiki.com/wiki/Residential_module_user%27s_guide, 2017-06-06.
[14]	RUIZ C, CONEJO A J . Pool strategy of a producer with endogenous formation of locational marginal prices[J]. IEEE Transactions on Power Systems, 2009,24(4):1855-1866. doi: 10.1109/TPWRS.2009.2030378 URL
[15]	YAO W F, ZHAO J H, WEN F S , et al. A hierarchical decomposition approach for coordinated dispatch of plug-in electric vehicles[J]. IEEE Transactions on Power Systems, 2013,28(3):2768-2778. doi: 10.1109/TPWRS.2013.2256937 URL
[16]	Climate guide [EB/OL]. [ 2020- 03- 22]. http://gridlab-d.shoutwiki.com/wiki/Climate_Guide2016-07-2.