Distributed generation planning in an active distribution network considering multi-agent interests and demand response

被引：0
|
作者：
Hu J. [1 ]
Chen H. [1 ]
Chen L. [1 ]
Shi J. [1 ]
Ding T. [1 ]
机构：
[1] School of Electrical Engineering and Automation, Wuhan University, Wuhan
来源：
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | 2021年 / 49卷 / 15期
基金：
中国国家自然科学基金;
关键词：
Active distribution network; Demand response; Environmental cost; Multi-agent benefits; Time-series;
D O I：
10.19783/j.cnki.pspc.201363
中图分类号：
学科分类号：
摘要：
For traditional distributed energy planning, it is common to only consider a single interest subject. Demand side response is not effectively considered, and especially the interests of various market entities and load regulation ability are absent. To take these issues into account, a novel planning model considering multiple interests and demand response is proposed. First, in terms of the environmental cost on the power supply side and the demand response on the user side, optimal configuration models are established to maximize the net incomes of distributed generation enterprises, distribution companies and power users. Then, a comprehensive optimization objective is designed to combine entire net incomes, and the second-order cone planning method is adopted to solve the problem. Finally, the IEEE33 node distribution network combined with the actual data of a regional power grid is used to test the effectiveness of the proposed model. The results show that the proposed model can effectively improve the overall economic benefits and balance the interests among different interests, and thus the vitality of the power market is well enhanced. © 2021 Power System Protection and Control Press.
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页码：38 / 46
页数：8
相关论文
共 25 条
  • [1] XIAO Bai, GUO Bei, Review and prospect of distribution network planning, Electric Power Automation Equipment, 38, 12, pp. 200-211, (2018)
  • [2] LONG Chuan, ZHANG Wentao, YE Shengyong, Et al., Optimal planning for siting and sizing of distributed generator including electric vehicles considering correlations of source and load, Thermal Power Generation, 49, 6, pp. 97-104, (2020)
  • [3] HAO Chaochao, LI Xiaoming, LIU Sheng, Et al., Day-ahead optimal dispatch for multi-agent balanced micro grid based on MILP model, Power System Protection and Control, 47, 6, pp. 32-39, (2019)
  • [4] EHSAN A, YANG Q., Optimal integration and planning of renewable distributed generation in the power distribution networks: a review of analytical techniques, Applied Energy, 210, pp. 44-59, (2018)
  • [5] HUANG Q., Insights for global energy interconnection from China renewable energy development, Global Energy Interconnection, 3, 1, pp. 2-12, (2020)
  • [6] KANG Chongqing, YAO Liangzhong, Key scientific issues and theoretical research framework for power system with high proportion of renewable energy, Automation of Electric Power Systems, 41, 9, pp. 2-11, (2017)
  • [7] SONG Miao, WANG Kewen, Planning of distributed PV grid-access considering the space and time correlation in active distribution network, Power System Protection and Control, 47, 5, pp. 106-114, (2019)
  • [8] WANG Y N, ZHENG T., Site selection and capacity determination of multi-types of DG in distribution network planning, 2019 4th Asia Conference on Power and Electrical Engineering, pp. 613-618, (2019)
  • [9] KAZMI S A A, SHIN D R., DG placement in loop distribution network with new voltage stability index and loss minimization condition based planning approach under load growth, Energies, 10, 8, pp. 1-28, (2017)
  • [10] DING H, ZHANG W, CHEN M, Et al., Multi-objective optimal configuration of distributed wind-solar generation considering energy storage, 2018 2nd IEEE Conference on Energy Internet and Energy System Integration, pp. 1-6, (2018)
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