A novel hybrid MOL-TLBO optimized techno-economic-socio analysis of renewable energy mix in island mode
作者： Ranjeeta Khare , Yogendra Kumar
DOI: 10.1016/J.ASOC.2016.02.044
关键词: Diesel generator 、 Automotive engineering 、 Turbine 、 Mathematics 、 Sizing 、 Renewable energy 、 Reliability (computer networking) 、 Demand load 、 Wind speed 、 Hybrid system
摘要: In this paper, a novel hybrid many optimizing liaisons (MOL) and teaching-learning based optimization (TLBO) i.e. MOL-TLBO of integrated renewable energy sources (IHRES) is proposed for techno-economic-socio analysis. IHRES consists PV, wind turbine, battery storage banks diesel generator. The methodology was constructed by using meteorological data from Renewable Energy Laboratory electrical engineering department, MANIT, Bhopal situated in Madhya Pradesh, India. Optimal sizing done on the basis solar irradiation, speed, demand load, reliability index, loss load probability (LOLP) CO2 emission through Three different crystalline silicon PV modules are considered: ASE-300(mi-Si EFG), Kyocera-120(mc-Si wafer) Astro-Power AP-120(thin-film Si). Results show that AP-120 gives better result as compared with other two PV-wind-battery-DG combination. Annual cost system (ACS) evaluated MOL TLBO (MOL-TLBO) algorithm. Supremacy suggested method optimal proved comparing results techniques TLBO, ITLBO, PSO, SGA. Finally it seen analysis exhibit superior performance fast to SGA, ITLBO MOL.
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