Energy management of microgrids: from a mixed-integer linear programming problem to a rule-based real-time algorithm

To ensure the economic viability and the reliability of microgrid operation, an adapted energy management system (EMS) has to be designed. Most of the studies have discussed optimization-based approaches, for example with a mixed-integer linear programming (MILP) problem, to get the best operating profiles for each microgrid device allowing economic, technical or environmental objectives to be met. However, this kind of EMS requires a forecasting ability of the power generation and of the demand, and the management of the uncertainties. In some microgrids, especially in industrial areas, the power generation and the load demand cannot be accurately forecasted. In such cases, only a rule-based algorithm can be considered for the real-time energy management. In this paper, a rule-based algorithm is proposed for the management of a seaport multi-energy microgrid, using electricity and hydrogen as energy vectors. The rules are designed on the basis of the results obtained with MILP problem solving with the aim being to maximize income and use the energy generated by the local energy sources as well as possible by taking dynamic pricing into account. Moreover, specific strategies are designed for the management of the electrolyzer and hydrogen tank to avoid premature ageing. The results show that the proposed real-time algorithm and rules enable the economic and energetic criteria to reach values close to those obtained with MILP problem solving, with an increase of the payback period less than 2%.