Multi-objective optimization and multi-criteria decision making aided by numerical method: Framework and a case study of Malaysia and South Africa.

• GCAOA is applied for parameter extraction of the TD PV model to predict the output current of the PV model. • Non-dominated multi-objective principle is proposed for constructing sets of Pareto optimal solutions using three conflicting objectives. • A new integration based on MOO and MCDM aided by numerical methods are considered to choose the most desirable configuration. • MODA based on AHP-VICKOR-GDM method is used for validation of the proposed method. • Performance of optimum designs are evaluated using hourly meteorological data for one year. This paper presents a new optimum design for an off-grid hybrid solar photovoltaic (PV), wind turbine (WT), and battery storage system for power isolated dwellings in Malaysia and South Africa. Selecting a desirable design of the WT/PV/Battery system among a wide variety of configurations, particularly at a favorable level of reliability, lowering the total cost, and reducing the surplus energy, remains a challenging task. The procedure of this work is summarized as follows: First, the parameter of the three diode PV model is optimally extracted from datasheet information to forecast the output power of the Yingli PV module. Then, the upper and lower variables bounds of the WT/PV/Battery system are intuitively determined. Afterward, the numerical method is employed to identify every possible configurations inside the design space. The non-dominated multi-objective principle is then established to generate optimal sets of Pareto front solutions. Finally, an integration of the best worst method, technique for order of preference by similarity to ideal solution, and group decision making technique are employed to weight the objectives with complete consistency ratios and rank the optimal designs based on practical judgments. The performance results showed that the optimal designs are comprised of 1 WTs, 105 PV modules (21 in series and 5 in parallel), and 69 storage batteries with zero loss of load probability (LLP), 60185.47 ($) of life cycle cost (LCC), and 13548017.77 KWh of excess energy for Malaysian scenario. While the optimum configuration of the South African case study consists of 16 WTs, 80 PV modules (20 in series and 4 in parallel), and 69 storage batteries with a favorable LLP values of 0.00068, 59180.15 ($) of LCC, and 19174160.54 ($) of excess energy, respectively. It can be concluded that the proposed methodology for finding appropriate size of the WT/PV/Battery system is capable of operating with extremely confident dependability while minimizing the overall cost of the system and minimizing the surplus energy. [ABSTRACT FROM AUTHOR]