Repair-based constraint handling techniques for sizing and energy management optimisation in microgrids

Microgrid sizing and energy management system (EMS) optimisation problems have conflicting objectives while subjected to complex constraints. These problems are usually solved with meta–heuristic algorithms, which are originally developed to solve unconstrained problems. Therefore, appropriate constraint handling technique (CHT) must be employed to solve constrained problems. This study proposes using three types of repair–based penalty approaches to solve a microgrid sizing and EMS problem. Parasitism predation algorithm is employed to solve the multi–objective optimisation problem, which minimises the levelized cost of electricity (LCOE) and dump load, while maximising the reliability of power supply. A case study based on the Westray Island standalone microgrid in Scotland is conducted to compare the effects of the repair approaches, in terms of the objective function values, battery dynamics and computational efficiency. The results of this study show the importance of using CHTs in an algorithm. Even though the results do not explicitly identify one as the best, each of the repair schemes have contributed to different dynamics of the battery and unique optimum results for the same system analysis.