Optimal load sharing of hydrogen-based microgrids with hybrid storage using model-predictive control

Abstract

Real operational scenario in renewable energy microgrids typically differs from the forecast computed by the economic dispatch, making difficult to achieve the contracted schedule agreed with the grid Market/System operator. Each energy storage system (ESS) has its own capabilities referred to the relationship between energy and power density. In addition, degradation issues or anomalous working conditions should be considered. Advanced control algorithms come up as a technological solution to these problems, taking advantage of each storage system and avoiding the degradation and/or limitations to provide optimal operation of a hybrid ESS. The high number of constraints and variables to be optimized increases the complexity of the control problem, being the rationale to deploy advanced control algorithms. In this paper, optimal load sharing of a real scenario in a renewable energy microgrid with hydrogen/batteries/ultracapacitor hybrid ESS is developed through an advanced control system based on model-predictive control techniques. The presence of logical states such as the start-up/shut-down of the fuel cell and electrolyzer or charge/discharge states in the batteries and ultracapacitor introduces logical variables. In order to model both continuous/discrete dynamics, the plant is modeled in the mixed logic dynamic framework.