Bi-level optimal dispatch and control strategy for air-conditioning load based on direct load control

被引：0

作者：

Gao, Ciwei ^{[1
]}

Li, Qianyu ^{[1
]}

Li, Yang ^{[1
]}

机构：

[1] Jiangsu Provincial Key Laboratory of Smart Grid Technology and Equipment, Southeast University, Nanjing 210096, Jiangsu Province

来源：

Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering | 2014年 / 34卷 / 10期

关键词：

Air-conditioning load; Bi-level optimization; Demand response; Direct load control; Load aggregator; Load dispatch;

D O I：

10.13334/j.0258-8013.pcsee.2014.10.005

中图分类号：

学科分类号：

摘要：

The proportion of air-conditioning load in electric terminal devices is growing year by year. Air-conditioning load is the most important part of the power peak-load, deepening the contradiction between supply and demand in China during peak periods and further widening the peak-valley difference. But the air-conditioning load has thermal storage ability, which has the huge potential of load regulation and can be connected into power system dispatch through demand response. The bi-level optimal dispatch and control model for air-conditioning load based on direct load control was proposed to deal with the problem in this paper. The macro-layer model was devoted to minimizing the cost of load dispatch through optimizing dispatching scheme based on air-conditioning load outputs and biddings of load aggregators, and the micro one was aimed at minimizing the difference between air-conditioning outputs and dispatching scheme through optimizing the control strategy of load aggregators. The case study shows the application of the proposed model. © 2014 Chin. Soc. for Elec. Eng.

引用

页码：1546 / 1555

页数：9

共 24 条

[11] Xu D., Xie S., Direct residential load control based on fuzzy linear programming, Power DSM, 9, 1, (2007)
[12] Mohagheghi S., Yang F., Falahati B., Impact of demand response on distribution system reliability, 2011 IEEE Power and Energy Society General Meeting, pp. 1-7, (2011)
[13] Ikaheimo J., Evens C., Karkkainen S., DER aggregator business: the finish case
[14] He C., Correlation analysis on system peak load and temperature, Hebei Electric Power, 30, 5, pp. 15-17, (2011)
[15] Luan W., Advanced metering infrastructure, Southern Power System Technology, 3, 2, pp. 8-10, (2009)
[16] Zhang J., Chen Z., The impact of AMI on the future power system, Automation of Electric Power Systems, 34, 2, pp. 20-23, (2010)
[17] Li T., Technical implications and development trends of flexible and interactive utilization of intelligent power, Automation of Electric Power Systems, 36, 2, pp. 11-17, (2012)
[18] A methodology for estimating large-customer demand response market potential
[19] Zhang Q., Wang X., Wang J., Et al., Survey of demand response research in deregulated electricity markets, Automation of Electric Power Systems, 32, 3, pp. 97-106, (2008)
[20] Lu N., David P.C., A state-queueing model of thermostatically controlled appliances, IEEE Transactions on Power Systems, 19, 3, pp. 1666-1673, (2004)

← 1 2 3 →