Scalable and Robust Demand Response With Mixed-Integer Constraints

被引:92
作者
Kim, Seung-Jun [1 ]
Giannakis, Georgios B. [1 ]
机构
[1] Univ Minnesota, Dept Elect & Comp Engn, Minneapolis, MN 55455 USA
关键词
Lagrange relaxation; mixed-integer programs; parallel and distributed algorithms; real-time demand response; robust optimization; RESIDENTIAL LOAD CONTROL; OPTIMIZATION APPROACH; PRICE; MANAGEMENT; DUALITY;
D O I
10.1109/TSG.2013.2257893
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
080906 [电磁信息功能材料与结构]; 082806 [农业信息与电气工程];
摘要
A demand response (DR) problem is considered entailing a set of devices/subscribers, whose operating conditions are modeled using mixed-integer constraints. Device operational periods and power consumption levels are optimized in response to dynamic pricing information to balance user satisfaction and energy cost. Renewable energy resources and energy storage systems are also incorporated. Since DR becomes more effective as the number of participants grows, scalability is ensured through a parallel distributed algorithm, in which a DR coordinator and DR subscribers solve individual subproblems, guided by certain coordination signals. As the problem scales, the recovered solution becomes near-optimal. Robustness to random variations in electricity price and renewable generation is effected through robust optimization techniques. Real-time extension is also discussed. Numerical tests validate the proposed approach.
引用
收藏
页码:2089 / 2099
页数:11
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