Abstract
The purpose of this study is to conduct the techno-economic-environmental feasibility analysis of a grid-connected hybrid energy systems, making use of locally renewable resources such as solar, wind, and biomass (pine needles). In the absence of a storage unit, five different configurations are investigated. With the use of a newly invented gaining-sharing knowledge optimization method, a mathematical model for optimum size is developed. The Gaining-sharing knowledge algorithm is based on how individuals learn and distribute information throughout their lives. The results of gaining-sharing knowledge-based model is also compared with the standard software tool, Hybrid optimization of multiple energy resources, and the commonly used optimization techniques Genetic algorithm and Biogeography-based optimization to confirm the effectiveness of the proposed approach. The Gaining-sharing knowledge (GSK) based model performance is found best among all. The grid-integrated biomass gasifier/PV amalgam system is determined to be the most economical with an energy production cost of 5.2 ₹/kWh and it saves 87.9% CO2 per annum when compared to a diesel-only system.
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