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Microgrid energy management system (EMS)/power management system (PMS) optimisation problems often have conflicting objectives subjected to nonlinear constraints. They are challenging to solve due to sources of discontinuity and non-convexity. However, the optimisation algorithms used to solve these problems are originally developed to solve unconstrained problems. Therefore, constraint handling techniques (CHTs) are integrated into these algorithms to solve constrained optimisation problems. The strategy of handling constraints contributes immensely toward the quality and accuracy of the solutions. Nonetheless, CHTs in solving microgrid EMS/PMS optimisation problems have received scant attention in the research. This study reviews the state-of-the-art CHTs through a four-step systematic framework. It identifies and screens the related research work, conducts an in-depth analysis on CHTs, scrutinises the nature of recurring constraints in EMS/PMS optimisation problems and critically analyses the findings. Based on the results of this review, three crucial factors in selecting an appropriate CHT were identified: (i) domain knowledge, which includes the nature of the problem (unimodality or multi-modality), the nature of the equality/inequality constraints (linearity or non-linearity), relationships among objective functions and constraints, number of constraints and their interdependencies, (ii) the area of feasible space defined by the constraints and (iii) the exploration and exploitation stages of the search algorithm. In addition, the need for more accurate and advanced CHTs to handle the constraints in microgrid EMS/PMS problems is emphasised. Moreover, conducting performance comparisons of CHTs in these problems would assure favourable upgrades in microgrid EMS/PMS.

Item Type:	Refereed Article
Keywords:	constraint handling techniques, energy management system, microgrids, optimisation, power management system, renewable energy
Research Division:	Engineering
Research Group:	Electrical engineering
Research Field:	Electrical energy generation (incl. renewables, excl. photovoltaics)
Objective Division:	Expanding Knowledge
Objective Group:	Expanding knowledge
Objective Field:	Expanding knowledge in engineering
UTAS Author:	Amarawardhana, KN (Mrs Kumudu Amarawardhana)
UTAS Author:	Enshaei, H (Dr Hossein Enshaei)
UTAS Author:	Jayasinghe, SDG (Dr Shantha Jayasinghe Arachchillage)
ID Code:	155289
Year Published:	2022
Web of Science® Times Cited:	1
Deposited By:	Seafaring and Maritime Operations
Deposited On:	2023-02-08
Last Modified:	2023-02-09
Downloads:	0