Optimal economical schedule of hydrogen-based microgrids with hybrid storage using model predictive control

Abstract

The electricity market rules determine the energy prices in the day-ahead market, matching offers from generators to bids from consumers. The unpredictability of renewable energy combined with the penalty deviations used in the regulation market makes it difficult for clean energy to play an important role in the electricity market. The high density of hydrogen as an energy storage system (ESS) appears to be one solution to the problems outlined. There is still not a perfect ESS, everyone has different limitations from the point of view of time autonomy, time response, degradation issues, or acquisition cost. The design of a hybrid energy storage management system emerges as a technological solution to the problems commented. The development of an optimal control for renewable energy microgrids with hybrid ESS is carried out using model predictive control (MPC). The MPC techniques allow maximizing the economical benefit of the microgrid, minimizing the degradation causes of each storage system, and fulfilling the different system constraints. 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. The MPC problem is solved within mixed-integer quadratic programming.