Optimal Bidding Strategy of Energy Storage in Power Market with Performance-Based Regulation Mechanism

doi:10.3969/j.issn.1000-7229.2016.03.011

Abstract

Abstract:

Auxiliary services are essential to the reliable operation of power systems. As the penetration of intermittent and variable renewable energy increases, the requirements of reserve and regulation in power grid rise correspondingly. Energy storage is a high-quality regulation resourcs, because of its fast ramping and responding capability. Performance-based regulation mechanism can provide economic incentive for energy storage and reasonable compensation for its cost, which can arouse the enthusiasm of energy storage. This paper constructs the optimal bidding strategy model for energy storage in current power market with considering performance-based regulation mechanism, which can guide the optimal resource allocation of energy storage, and help make a trade-off for energy storage between revenues from energy markets and auxiliary service markets to achieve the maximization of profits. The proposed model can also help estimate the profit potential of energy storage, and in turn help its investment decision. The validity of the proposed model is verified by example analysis.

Key words: energy storage, power market, performance-based regulation, auxiliary service, optimal bidding strategy

CLC Number:

TM 91

SU Feng, ZHANG Ben, SHI Peiran, HE Guannan, CHEN Qixin. Optimal Bidding Strategy of Energy Storage in Power Market with Performance-Based Regulation Mechanism[J]. Electric Power Construction, 2016, 37(3): 71-75.

References

［1］胡泽春, 谢旭, 张放, 等. 含储能资源参与的自动发电控制策略研究［J］. 中国电机工程学报,2014,(29): 5080-5087.
HU Zechun, XIE Xu, Zhang Fang, et al. Research on automatic generation control strategy incorporating energy storage resources［J］. Proceedings of the CSEE, 2014, 34(29): 5080-5087.
［2］CHENG Y, TABRIZI M, SAHNI M, et al. Dynamic available AGC based approach for enhancing utility scale energy storage performance［J］. IEEE Transactions on Smart Grid, 2014, 5(2):1070-1078.
［3］雷博. 电池储能参与电力系统调频研究［D］. 长沙：湖南大学, 2014.
LEI Bo. Research on application of battery energy storage system in power system frequency regulation［D］. Changsha: Hunan University, 2014.
［4］陈大宇, 张粒子, 王澍, 等. 储能在美国调频市场中的发展及启示［J］. 电力系统自动化,2013,37(1): 9-13.
CHEN Dayu, ZHANG Lizi, WANG Shu, et al. Development of energy storage in frequency regulation market of United States and its enlightenment［J］.Automation of Electric Power Systems,2013,37(1): 9-13.
［5］MASIELLO R D, ROBERTS B, SLOAN T. Business models for deploying and operating energy storage and risk mitigation aspects［J］. Proceedings of the IEEE, 2014, 102(7):1052-1064.
［6］KINTNER-MEYER M. Regulatory policy and markets for energy storage in north America［J］. Proceedings of the IEEE, 2014, 102(7):1065-1072.
［7］WASHINGTON D U F E. Frequency regulation compensation in the organized wholesale power markets［R］. Washington DC: Federal Energy Regulatory Commission, 2011.
［8］PJM. Performance based regulation: year one analysis［R］. Valley Forge, PA: 2013.
［9］KAZEMPOUR S J, HOSSEINPOUR M, MOGHADDAM M P. Self-scheduling of a joint hydro and pumped-storage plants in energy, spinning reserve and regulation markets［C］//Power & Energy Society General Meeting, 2009.
［10］AKHAVAN-HEJAZI H, MOHSENIAN-RAD H. Optimal operation of independent storage systems in energy and reserve markets with high wind penetration［J］. IEEE Transactions on Smart Grid, 2014, 5(2):1088-1097.
［11］MOGHADDAM I G, SAEIDIAN A. Self scheduling program for a VRB energy storage in a competitive electricity market［C］//2010 International Conference on Power System Technology (POWERCON), 2010:1-6.
［12］VARKANI A K, DARAEEPOUR A, MONSEF H. A new self-scheduling strategy for integrated operation of wind and pumped-storage power plants in power markets［J］. Applied Energy, 2011, 88(12):5002-5012.

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