Main content area

Day-ahead optimal bidding strategy of microgrid with demand response program considering uncertainties and outages of renewable energy resources

Das, Saborni, Basu, Mousumi
Energy 2020 v.190 pp. 116441
confidence interval, electrical equipment, electricity, energy, markets, models, profits and margins, renewable energy sources, risk, uncertainty
In restructured electricity markets, microgrids are becoming smarter, more reliable and more economic electricity providers with respect to the incorporation of advanced smart grid technologies, distributed energy resources, efficient energy storage systems, and demand response programs (DRPs). Moreover, better bidding strategies, prepared by MG operators, boost the profits of MG market players. But, highly intermittent nature of renewable energy resources and their higher rate of outages make bidding strategies inefficient. To solve these issues, this study suggests an optimal bidding strategy considering uncertainty of renewable energy resources and DRP based on their outage probabilities. Tent chaos mapping is used to generate load scenarios and all possible renewable power output scenarios within the confidence intervals in non-repetitive and adaptive manner. Reserve and penalty costs for incorrect estimation of renewable energies are invoked to design more robust bidding. Moreover, the risk of participation in the competitive energy market is assessed using CVaR criteria. The proposed bidding model is optimized using mixed integer nonlinear programming. ‘Value of stochastic solution’ is used to investigate the efficiency of the stochastic programming in uncertainty integration into the bidding problem.