Interdependent multi-objective sizing and control optimisation of a renewable energy hydrogen system

Abstract

This paper presents a sizing and control optimisation architecture for the design and evaluation of a small-scale stand-alone hybrid PV-wind-battery system for the production of hydrogen (H2) using proton exchange membrane (PEM) technology. Three objectives are considered simultaneously namely cost, efficiency and reliability. For this task an optimisation approach is developed combining a single objective genetic algorithm (GA) with a multiobjective GA (MOGA) to optimise nine system sizing variables and six power management system control set-point variables. The nine sizing and six control variables are combined to form a solution vector. The optimisation algorithm searches the search space, with user defined boundaries, for non-dominated solution vectors. The result is a set of solution vectors which are useful in the selection of components for the design and evaluation of these systems. The optimisation approach developed sufficiently searches the bounded search space and provides results in the form of a set of non-dominated solution vectors. These results are useful in understanding how the different components of such a non-linear complex system affect each other as well as the three objectives considered in this study