Transaction model and energy management optimisation method of rural microgrid

被引:0
作者
Chen M. [1 ]
Fu B. [1 ]
Chen Z. [1 ]
Wu J. [1 ]
机构
[1] Department of Electronics and Information Engineering, Suzhou University of Science and Technology, Suzhou
基金
中国国家自然科学基金;
关键词
Game theory; optimal strategy; power consumption characteristics; rural microgrid;
D O I
10.1080/23335777.2021.2016982
中图分类号
学科分类号
摘要
Owing to the wide distribution of rural areas, the construction of power facilities is not perfect, which poses a great challenge to the power supply stability of the rural power grid. As an important supplement, the microgrid (MG) plays a complementary role in improving the power supply quality. However, the addition of the MG increases the complexity, and how to balance the interests of the participants has become a substaintial problem. Based on the analysis of the power consumption characteristics of rural residential, agricultural and industrial areas, a game relationship model between MG operators and power users is established, and the overall optimal strategy is obtained in this paper. For consumers, it can effectively achieve the effect of ‘peak shaving and valley filling’ and reduce the cost of electricity. For MG operators, it can improve the consumption rate of renewable energy and increase revenue. © 2021 Informa UK Limited, trading as Taylor & Francis Group.
引用
收藏
页码:122 / 143
页数:21
相关论文
共 27 条
  • [1] New rural construction in a socialist country[EB/OL, (2019)
  • [2] Wang T., Wang Q., Zhang C., Research on the optimal operation of a novel renewable multi-energy complementary system in rural areas[J], Sustainability, 13, 4, (2021)
  • [3] Lasseter R., Paigi P., Microgrid: a conceptual solution[C], 2004 IEEE 35th Annual Power Electronics Specialists Conference (IEEE Cat. No. 04CH37551), (2004)
  • [4] Yang X., Su J., Lv Z., Et al., Overview on micro-grid technology[J], Proc CSEE, 34, 1, pp. 57-70, (2014)
  • [5] Guo C., Wang X., Zheng Y., Et al., Optimal Energy management of multi-microgrids connected to distribution system based on deep reinforcement learning[J], Int J Electr Power Energy Syst, 131, (2021)
  • [6] Wei B., Shi Z., Zhu H., Et al., Configuration method of microgrid power supply mode in rural remote areas[J], Rural Electrificat, 1, pp. 5-7, (2016)
  • [7] Fu B., Chen M., Fei Z., Et al., Research on the Stackelberg game method of building micro-grid with electric vehicles[J], J Electric Eng Technol, 16, 3, pp. 1637-1649, (2021)
  • [8] Mokhtarnejad Z., Nazarzadeh J., Applying optimal nash‐Stackelberg game for load adjusting in DC microgrids[J], Int Trans Electr Energy Syst, 29, 4, (2019)
  • [9] Lu Q., Chen L., Mei S., Typical applications and prospects of game theory in power system[J], Proc Chin Soc Elect Eng, 34, 29, pp. 5009-5017, (2014)
  • [10] Mab A., Aab C., Multi-Stage optimal scheduling of multi-microgrids using deep-learning artificial neural network and cooperative game approach[J], Energy, 239, PartB, (2021)