A joint approach for strategic bidding of a microgrid in energy and spinning reserve markets

In the electricity market, short-term operation is organized in day-ahead and real-time stages. The two stages that are performed in different time intervals have reciprocal effects on each other. The paper shows the strategy of a microgrid that participates to both day-ahead energy and spinning reserve market. It is supposed that microgrid is managed by a prosumer, a decision maker who manages distributed energy sources, storage units, Information and Communication Technologies (ICT) elements, and loads involved in the grid. The strategy is formulated considering that all decisions about the amount of power to sell in both markets and the price links to the offer, must be taken contextually and at the same time, that is through a joint approach. In order to develop an optimal bidding strategy for energy markets, prosumer implements a nonlinear mixed integer optimization model: in this way, by aggregating and coordinating various distributed energy sources, including renewable energy sources, micro-turbines–electricity power plants, combined heat and power plants, heat production plants (boilers), and energy storage systems, prosumer is able to optimally allocate the capacities for energy and spinning reserve market and maximize its revenues from different markets. Moreover, it is considered that both generators and loads can take part in the reserve market. The demand participation happens through both shiftable and curtailable loads. Case studies based on microgrid with various distributed energy sources demonstrate the market behavior of the prosumer using the proposed bidding model.

[1]  Yuan Wu,et al.  Energy management of cooperative microgrids: A distributed optimization approach , 2018 .

[2]  D. Kirschen,et al.  A Survey of Frequency and Voltage Control Ancillary Services—Part II: Economic Features , 2007, IEEE Transactions on Power Systems.

[3]  Feng Liu,et al.  Robust Energy and Reserve Dispatch Under Variable Renewable Generation , 2015, IEEE Transactions on Smart Grid.

[4]  Fushuan Wen,et al.  Coordination of bidding strategies in day-ahead energy and spinning reserve markets , 2002 .

[5]  D. Swider Efficient Scoring-Rule in Multipart Procurement Auctions for Power Systems Reserve , 2007, IEEE Transactions on Power Systems.

[6]  Reza Hemmati,et al.  Energy management in microgrid based on the multi objective stochastic programming incorporating portable renewable energy resource as demand response option , 2017 .

[7]  E. Lobato,et al.  Optimization of the Spanish market sequence by a price-taker generating firm , 2003, 2003 IEEE Bologna Power Tech Conference Proceedings,.

[8]  Ning Zhang,et al.  Integrated Power Management of Conventional Units and Industrial Loads in China's Ancillary Services Scheduling , 2015 .

[9]  S. M. Moghaddas-Tafreshi,et al.  Bidding Strategy of Virtual Power Plant for Participating in Energy and Spinning Reserve Markets—Part I: Problem Formulation , 2011, IEEE Transactions on Power Systems.

[10]  Federico Rossi,et al.  Determination of the Prosumer’s Optimal Bids , 2015 .

[11]  Luis Rouco,et al.  Strategic bidding in sequential electricity markets , 2006 .

[12]  Alireza Zakariazadeh,et al.  Day-ahead resource scheduling of a renewable energy based virtual power plant , 2016 .

[13]  R. Raineri,et al.  Technical and economic aspects of ancillary services markets in the electric power industry: an international comparison , 2006 .

[14]  Federico Rossi,et al.  Optimal Operation of a Residential Microgrid: The Role of Demand Side Management , 2015 .

[15]  L. Shi,et al.  Bidding strategy of microgrid with consideration of uncertainty for participating in power market , 2014 .

[16]  Chang Ye,et al.  Optimal Dispatch Strategy of a Virtual Power Plant Containing Battery Switch Stations in a Unified Electricity Market , 2015 .

[17]  H. Morais,et al.  Distribution network short term scheduling in Smart Grid context , 2011, 2011 IEEE Power and Energy Society General Meeting.

[18]  Jianhui Wang,et al.  Review of real-time electricity markets for integrating Distributed Energy Resources and Demand Response , 2015 .

[19]  E. Allen,et al.  Reserve markets for power systems reliability , 2000 .

[20]  A. Papalexopoulos,et al.  Competitive procurement of ancillary services by an independent system operator , 1999 .

[21]  F. A. Campos,et al.  Joint energy and reserve markets: Current implementations and modeling trends , 2014 .

[22]  Enrico Zio,et al.  An integrated framework of agent-based modelling and robust optimization for microgrid energy management , 2014 .

[23]  Kankar Bhattacharya,et al.  Oligopolistic Competition of Gencos in Reactive Power Ancillary Service Provisions , 2009, IEEE Transactions on Power Systems.

[24]  Jun Hasegawa,et al.  A new profit-based unit commitment considering power and reserve generating , 2002, 2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309).

[25]  Hossein Nezamabadi,et al.  Arbitrage strategy of virtual power plants in energy, spinning reserve and reactive power markets , 2016 .

[26]  Saeed Rahmani Dabbagh,et al.  Risk Assessment of Virtual Power Plants Offering in Energy and Reserve Markets , 2016, IEEE Transactions on Power Systems.

[27]  D. Kirschen,et al.  A Survey of Frequency and Voltage Control Ancillary Services—Part I: Technical Features , 2007, IEEE Transactions on Power Systems.

[28]  Ram Avtar Gupta,et al.  A robust optimization based approach for microgrid operation in deregulated environment , 2015 .

[29]  Xifan Wang,et al.  Operating reserve model in the power market , 2005, IEEE Transactions on Power Systems.

[30]  Iman Narimani,et al.  Participating of micro-grids in energy and spinning reserve markets — Intra-day market , 2015, 2015 30th International Power System Conference (PSC).

[31]  E. F. Sánchez-Úbeda,et al.  Strategic Bidding in Secondary Reserve Markets , 2016, IEEE Transactions on Power Systems.

[32]  Hassan Ghasemi,et al.  Optimal operation of a virtual power plant with risk management , 2012, 2012 IEEE PES Innovative Smart Grid Technologies (ISGT).

[33]  Study on Conjectural Variation Based Bidding Strategy in Spinning Reserve Markets , 2006, 2006 International Conference on Power System Technology.

[34]  Pierluigi Siano,et al.  Designing and testing decision support and energy management systems for smart homes , 2013, J. Ambient Intell. Humaniz. Comput..

[35]  Rajabi Mashhadi Habib,et al.  PRICE-TAKERS’ BIDDING STRATEGIES IN JOINT ENERGY AND SPINNING RESERVE PAY-AS-BID MARKETS , 2013 .

[36]  A.L. Dimeas,et al.  Operation of a multiagent system for microgrid control , 2005, IEEE Transactions on Power Systems.

[37]  A. David,et al.  Optimally co-ordinated bidding strategies in energy and ancillary service markets , 2002 .

[38]  H. Yamin,et al.  Spinning reserve uncertainty in day-ahead competitive electricity markets for GENCOs , 2005, IEEE Transactions on Power Systems.

[39]  Eiichi Tanaka,et al.  New bidding strategy formulation for day-ahead energy and reserve markets based on evolutionary programming , 2005 .