Bidding strategy of microgrid with consideration of uncertainty for participating in power market

• Published in: International journal of electrical power & energy systems 2014-07, Vol.59, p.1-13
• Main Authors: Shi, L., Luo, Y., Tu, G.Y.
• Format: Article
• Language: English
• Subjects: Applied sciences; Bidding strategy; Distributed generation; Electric power generation; Electric power plants; Electrical engineering. Electrical power engineering; Electrical power engineering; Energy market; Exact sciences and technology; Markets; Matlab; Microgrid; Miscellaneous; Operation. Load control. Reliability; Optimization; Power networks and lines; Reserves; Spinning; Spinning reserve market; Strategy; Uncertainty
• ISSN: 0142-0615; 1879-3517
• DOI: 10.1016/j.ijepes.2014.01.033

•A day-ahead bidding strategy of microgrid considering uncertainty is proposed.•Day-ahead microgrid uncertain power model is generated.•Backward scenario reduction method is employed to decrease the computation time.•Bi-level stochastic optimization model of bidding strategy of microgrid is given.•The effectiveness and excellence of proposed strategy is verified by case study. Microgrid is commonly regarded as an efficient way for integration of distributed generation (DG) in low voltage network. However, the integration method of microgrid in power system for maximum benefit needs to be further promoted. In this paper, a stochastic bidding strategy of microgrid in a joint day-ahead market of energy and spinning reserve service is proposed taking into account of uncertainty of renewable DG units’ output power and load. The stochastic bidding strategy is modeled as bi-level optimization problem and can be divided into two steps. First, Latin Hypercube Sampling (LHS) is utilized for generating microgrid uncertain net power scenarios according to day-ahead uncertain power scenario models, and then reduced by backward scenario reduction technique for less computation. Second, the upper level total bidding profit including bidding revenue, expected imbalance and operation cost is optimized by interior point algorithm in MATLAB for making optimal bids. The expected imbalance and operation cost is calculated by iteratively invoking lower level deterministic unit commitment under each microgrid uncertain net power scenario. The lower level deterministic unit commitment is coded and solved by mixed integer nonlinear programming (MINLP) solver DICOPT in GAMS. Finally, the optimal energy and spinning reserve bids are given by solving the bi-level bidding model. The model is applied to a modified typical low-voltage microgrid and the effectiveness and excellence of proposed strategy is proven by comparing simulation results with traditional deterministic bidding strategy.