Economic Optimization Operation of Virtual Power Plant Considering the Users' Satisfaction Based on Non-Cooperative Game Theory

LU Yao,LIU Jichun,XU Lixiong

Distributed Energy ›› 2017, Vol. 2 ›› Issue (1) : 23-29.

PDF(1514 KB)
PDF(1514 KB)
Distributed Energy ›› 2017, Vol. 2 ›› Issue (1) : 23-29. DOI: 10.16513/j.cnki.10-1427/tk.2017.01.004
Basic Research

Economic Optimization Operation of Virtual Power Plant Considering the Users' Satisfaction Based on Non-Cooperative Game Theory

Author information +
History +

Abstract

Nowadays the energy problems are gradually paid attention, the development of distributed generation(DG) and network communication technology relieves the strain on energy demand, improves the environment problems, and increases the permeability of renewable energy. But up to the present day, the optimization study of the common virtual power plant(VPP) focuses more on the energy scheduling of the internal DGs and the supply of the ancillary services such as market transactions for the external power grid etc. However, the common research fails to consider the load diversity and the electricity flexibility of the user demand, and the initiative and interactivity participating in internal energy scheduling as resources of demand side response. On this basis, the non-cooperative game theory is employed to build the interaction model of the power generation side and the demand side of users in this study. This model provides a theoretical basis to solve problems such as how to improve the interaction flexibility between the power generation side and the demand side of users, considering the satisfaction of users, gaming with their respective maximization of benefit as the goal. The simulation results verify the feasibility of the proposed theory, and compared with the traditional VPP optimization solution the method can realize the economic optimality of both the power generation side and the users' load side considering the users' satisfaction. Moreover, the proposed method improves the utilization rate of renewable energy and realizes the economic optimal operation of the VPP.

Key words

non-cooperative game / virtual power plant(VPP) / customer satisfaction / economic optimization

Cite this article

Download Citations
Yao LU , Jichun LIU , Lixiong XU. Economic Optimization Operation of Virtual Power Plant Considering the Users' Satisfaction Based on Non-Cooperative Game Theory[J]. Distributed Energy Resources. 2017, 2(1): 23-29 https://doi.org/10.16513/j.cnki.10-1427/tk.2017.01.004

References

[1]
廖秀英王婷程辉,等. 中国CO2能源排放量与 CO2 大气浓度时空分布研究[J]. 湖南科技大学学报(自然科学版), 2014, 29(3):103-107.
LIAO Xiuying, WANG Ting, CHENG Hui, et al. Research on spatial and temporal distribution of carbon dioxide energy emission and concentration[J]. Journal of Hunan University of Science & Technology (Natural Science Edition), 2014, 29(3):103-107.
[2]
SIMS R E H, ROGNER H H, GREGORY K. Carbon emission and mitigation cost comparisons between fossil fuel, nuclear and renewable energy resources for electricity generation[J]. Energy Policy, 2003, 31(13):1315-1326.
[3]
KASMAN A, DUMAN Y S. CO2 emissions, economic growth, energy consumption, trade and urbanization in new EU member and candidate countries: a panel data analysis[J]. Economic Modelling, 2015, 44(44):97-103.
[4]
BAYOD-RUJULA A A. Future development of the electricity systems with distributed generation[J]. Energy, 2009, 34(3):377-383.
[5]
KUMAGAI J. Virtual power plants, real power[J]. IEEE Spectrum, 2012, 49(3):13-14.
[6]
夏榆杭刘俊勇. 基于分布式发电的虚拟发电厂研究综述[J]. 电力自动化设备2016, 36(4):100-106, 115.
XIA Yuhang, LIU Junyong. Review of virtual power plant based on distributed generation[J]. Electric Power Automation Equipment, 2016, 36(4):100-106, 115.
[7]
XIA Y H, LIU J Y. Optimal scheduling of virtual power plant with risk management[J]. Journal of Power Technologies, 2016, 96(1):49-56.
[8]
GIUNTOLI M, POLI D. Optimized thermal and electrical scheduling of a large scale virtual power plant in the presence of energy storages[J]. IEEE Transactions on Smart Grid, 2013, 4(2):942-955.
[9]
RUIZ N, COBELO I, OYARZABAL J. A direct load control model for virtual power plant management[J].IEEE Transactions on Power Systems, 2009, 24(2):959-966.
[10]
余贻鑫刘艳丽. 智能电网的挑战性问题[J]. 电力系统自动化2015, 39(2):1-5.
YU Yixin, LIU Yanli. Challenging issues of smart grid[J]. Automation of Electric Power Systems, 2015, 39(2):1-5.
[11]
孙宇军李扬王蓓蓓,等. 计及不确定性需求响应的日前调度计划模型[J]. 电网技术2014, 38(10):2708-2714.
SUN Yujun, LI Yang, WANG Beibei, et al. A day-ahead scheduling model considering demand response and its uncertainty[J]. Power Systems Technology, 2014, 38(10):2708-2714.
[12]
董朝阳赵俊华文福栓,等. 从智能电网到能源互联网:基本概念与研究框架[J]. 电力系统自动化2014, 38(15):1-11.
DONG Zhaoyang, ZHAO Junhua, WEN Fushuan, et al. From smart grid to energy internet: Basic concepts and research framework[J]. Automation of Electric Power Systems, 2014, 38(15):1-11.
[13]
陈春武李娜钟朋园,等. 虚拟电厂发展的国际经验及启示[J]. 电网技术2013, 37(8):2258-2263.
CHEN Chunwu, LI Na, ZHONG Pengyuan, et al. Review of virtual power plant technology abroad and enlightenment to China[J]. Power Systems Technology, 2013, 37(8):2258-2263.
[14]
卢强陈来军梅生伟. 博弈论在电力系统中典型应用及若干展望[J]. 中国电机工程学报201434(29):5009-5017.
LU Qiang, CHEN Laijun, MEI Shengwei. Typical applications and prospects of game theory in power system[J]. Proceedings of the CSEE, 2014, 34(29):5009-5017.
PDF(1514 KB)

Accesses

Citation

Detail

Sections
Recommended

/