A Day-ahead Optimization Scheduling Method for Prosumer Based on Iterative Distribution Locational Marginal Price

被引：0
|
作者：
Hu J. [1 ]
Li Y. [1 ]
Wu J. [1 ]
Ai X. [1 ]
机构：
[1] State Key Laboratory of Alternate Electrical Power System With Renewable Energy Sources, North China Electric Power University, Changping District, Beijing
来源：
Dianwang Jishu/Power System Technology | 2019年 / 43卷 / 08期
基金：
中国国家自然科学基金;
关键词：
Congestion management; DLMP; Lagrange dual decomposition; Prosumer; Sub-gradient method;
D O I：
10.13335/j.1000-3673.pst.2019.0619
中图分类号：
学科分类号：
摘要：
With increasing penetration of prosumers in distribution network, the flexible dispatching ability of the prosumers becomes an important factor affecting positive and negative load peaks. The distribution locational marginal price (DLMP) method is extended to solve the problem of bidirectional congestion caused by prosumers in distribution network, and a distributed day-ahead scheduling strategy is proposed for prosumers based on iterative DLMP. Based on Lagrange duality decomposition principle, distribution system operator (DSO) adopts sub-gradient method to determine the purchase and sale congestion prices respectively, thus guiding the controllable photovoltaic and adjustable household load under aggregator (Agg), to adjust the power to achieve synergistic effect of alleviating distribution network congestion. DSO and Agg realize power consensus through interaction of "power-price" information, so as to protect the privacy information of Agg users. Finally, a modified IEEE 33-bus system is used to illustrate rationality and effectiveness of the proposed method. © 2019, Power System Technology Press. All right reserved.
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收藏
页码：2770 / 2780
页数：10
相关论文
共 24 条
  • [1] Parag Y., Sovacool B.K., Electricity market design for the prosumer era, Nature Energy, 1, 4, (2016)
  • [2] Valero S., Ortiz M., Senabre C., Et al., Methods for customer and demand response policies selection in new electricity markets, IET Generation Transmission & Distribution, 1, 1, pp. 104-110, (2007)
  • [3] Zhang X., Lu L., Jin Y., Et al., Congestion mitigation model and algorithm for urban power grids considering configurability of high-voltage distribution transformer unit groups, Proceedings of the CSEE, 36, 20, (2016)
  • [4] Daroj K., Limpananwadi W., Reactive Power Dispatch scheme evaluation for synchronous based distributed generators to reduce real power loss in distribution systems, IEEE International Conference on Sustainable Energy Technologies, pp. 1178-1183, (2009)
  • [5] You Y., Liu D., Zhong Q., Et al., Research on optimal schedule strategy for active distribution network, Automation of Electric Power Systems, 38, 9, pp. 177-183, (2014)
  • [6] Sun H., Shen Z., Zhou W., Et al., Congestion dispatch research of active distribution network with electric vehicle group response, Proceedings of the CSEE, 37, 19, pp. 5549-5559, (2017)
  • [7] Liu Y., Tan C.S., Lo K.L., The effects of locational marginal price on electricity market with distributed generation, Proceedings of the CSEE, 27, 31, pp. 89-97, (2007)
  • [8] Cao J., Ma H., Liu Y., Et al., Research on demand response strategy based on nodal price, Power System Technology, 40, 5, pp. 1536-1542, (2016)
  • [9] Liu W., Wu Q., Wen F., Et al., A market for participation of electric vehicles and dispatchable loads in distribution system congestion management, Automation of Electric Power Systems, 38, 24, pp. 26-33, (2014)
  • [10] Ruoyang L., Qiuwei W., Shmuel S.O., Distribution locational marginal pricing for optimal electric vehicle charging management, IEEE Transactions on Power Systems, 29, 1, pp. 203-211, (2013)
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