Constraint multi-objective optimal design of hybrid renewable energy system considering load characteristics

Abstract Finding the optimal size of a hybrid renewable energy system is certainly important. The problem often modelled as an multi-objective optimization (MOP) in which objectives such annualized cost, loss power supply probability etc. are minimized. However, MOP model rarely takes load characteristics into account. We argue that ignoring may be inappropriate when designing HRES for place with intermittent high demand. For example, training base demand there tasks while decreases to low level no task. This results interesting issue, is, determined at specific value, say 15%, then it very likely most would occur right period unexpected. Therefore, this study proposes constraint deal issue—in addition general model, over critical set constraint. Correspondingly, non-dominated sorting genetic algorithm II relaxed $$\epsilon $$ ϵ handling strategy proposed address MOP. Experimental on real world application demonstrate and both effective efficient.