Bidding Strategy of Micro-Grids in Day-Ahead Energy and Reserve Markets under Generation and Load Uncertainties

Micro-grids are integrated electrical systems, which can include dispatchable and non-dispatchable resources, consumption and battery storages. However, optimal management of these integrated systems requires stochastic programming approaches to consider the random nature of renewable generation and consumption. In this paper, a comprehensive bidding strategy model has been provided for renewable micro-grids to participate in the day-ahead energy and reserve markets. The uncertainties in renewable generation and load consumption have been integrated to the problem by the use of stochastic programming approach. Furthermore, the Latin Hypercube Sampling and Fast Backward/forward scenario reduction approaches have been utilized to generate and reduce the scenarios. A large size mixed integer non-liner problem with a lot of binary variables is the outcome of the optimization problem, which is maximized via combination of AlphaECP and Lindoglobal solvers in GAMS to guarantee the global solutions. The “value of the stochastic solution” shows the efficiency of the stochastic programming approach.