Economic and reliability determination of sustainable renewable energy mix based on social spider prey optimization algorithm

Abstract Resolving the power crises requires combination of different individual renewable energy sources so that one source can compensate for another. Unfortunately, are not always available at certain times making their use problematic. To solve this uncertainty, it is important to combine independent and determine right set mix economical reliable. The data solar PV, wind, battery, biomass. Different scenarios or considered wind–biomass–battery, PV–wind–biomass, PV–biomass–battery, PV–wind–biomass–battery. Knowing economic reliable impact these combinations helps make best investment decision. nature-inspired optimization utilized as methodology feasible dimension, economic, reliability mix. Historical energy-related year were obtained from National Renewable Energy Laboratory was used evaluate hybrid systems. result shows SSP guaranteed optimal costs satisfied constraints wind–biomass–battery system, PV–wind–biomass outcomes suggests provide therefore calls researchers further explore potential integrating algorithm in approach PV–wind–biomass–battery system.