Regulation service for the short-term management of renewable energy microgrids with hybrid storage using Model Predictive Control

The electricity market rules determine the energy price in the day-ahead market, matching offers from generators to bids from consumers to develop a classic supply and demand equilibrium price, usually on an hourly interval. The unpredictability of renewable energy joined to the penalty deviations used in the regulation market make it difficult for clean energy to play an important role in the system. The use of Energy Storage Systems (ESS) integrated in a microgrid (μG) structure with renewable energy systems using two level scheduling, long-term (40 hours) and short-term (1 hour) appears as a solution to minimize the penalty deviations. In this paper, the short-term regulation service optimization linked to the long-term economical dispatch of a grid-connected renewable energy μG is addressed. The μG includes hybrid energy storage composed of hydrogen storage (HESS), battery storage (BESS) and ultracapacitor storage (UESS). It is managed with Model Predictive Control (MPC) in order to maximize the economical benefit minimizing the degradation causes of each storage system. In order to capture both continuous/discrete dynamics and switching between different operating conditions, the plant is modeled with the framework of mixed logic dynamic (MLD). Taking into account the presence of integer variables, the MPC problem is solved using MIQP (Mixed Integer Quadratic Programming).