• CSCD核心库收录期刊
  • 中文核心期刊
  • 中国科技核心期刊

Electric Power Construction ›› 2017, Vol. 38 ›› Issue (7): 88-.doi: 10.3969/j.issn.1000-7229.2017.07.011

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  Bidding Strategies for Virtual Power Plants Including Wind Power Generation Units and Power-to-Gas Facilities 
 

 ZHENG Yu1,LI Yang2,JIAO Fengshun3,WEN Fushuan2,ZHAO Junhua4,DONG Zhaoyang1 

 
  

  1.   (1. Electric Power Research Institute, China Southern Power Grid, Guangzhou 510080, China; 2. College of   Electrical Engineering, Zhejiang University, Hangzhou 310027, China; 3. Shenzhen Power Supply Co., Ltd.,   Shenzhen 518100, Guangdong Province, China; 4. School of Science and Engineering, The Chinese   University of Hong Kong (Shenzhen),  Shenzhen 518100, Guangdong Province, China)   
     
  • Online:2017-07-01
  • Supported by:
    Project supported by National Natural Science Foundation of China(51477151);the National Basic Research Program of China (973 Program) (2013CB228202)  

Abstract:  ABSTRACT:  With the continuous development and commercialization of power-to-gas (P2G) technology, the coordinated operation between wind power generation units (WPGUs) and P2G facilities has attracted more and more attentions. The operational flexibility of P2G facilities can be employed to mitigate power output fluctuations of WPGUs, while both P2G facilities and WPGUs can form a virtual power plant (VPP) to participate in electricity market operation. Given this background, this paper studies the optimal bidding strategies for the VPP including WPGUs and P2G facilities. First, we present a modeling framework for a VPP with WPGUs and P2G facilities to participate in the operation of an electricity market. Then we construct the bidding strategy model for a VPP in a day-ahead electricity market with the objective of maximizing the overall profit, and determine the self-scheduling strategy of VPP. Considering uncertain forecasting error of the fluctuant outputs from wind power units, we develop both robust and opportunity bidding strategy models based on the information gap decision theory (IGDT), so as to reflect the risk preferences of various VPPs. And then, we adopt the well-developed commercial solver AMPL/IPOPT to solve the proposed nonlinear optimization model, and determine the robust and opportunity bidding strategy models for expected cost. Finally, case studies based on data from the Nord pool electricity market are carried out to demonstrate the characteristics of the developed optimization models and the employed solving method. 

 

Key words: virtual power plant (VPP), wind power generation unit (WPGU), power-to-gas (P2G) facility, electricity market, bidding strategy, information gap decision theory (IGDT) 

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