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Distributed polygeneration using local resources for an Indian village: multiobjective optimization using metaheuristic algorithm

机译:印度村庄使用本地资源的分布式多代发电:使用元启发式算法的多目标优化

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Introduction of renewable energy systems is an imperative need at present. Hybridization of locally available different renewable resources is required due to intermittency of these resources. A multicriteria optimization using cuckoo search algorithm for simultaneous best combination of economy, land use and GHG emission has been carried out for polygeneration with three utility outputs. These are electricity, heat and high calorific value gas. The levelized cost of electricity at 100% reliability of power supply has come out to be 0.1 USD/kWh. For better economy, a minimum plant life of 20 years is desired. This study is with data for a small hilly village of India with mostly poor people. Methodology and results of this study represent optimization of such sustainable energy systems using local resources in specific sites.
机译:目前,引入可再生能源系统是当务之急。由于这些资源的间歇性,因此需要对本地可用的不同可再生资源进行混合。利用杜鹃搜索算法对经济,土地利用和温室气体排放同时进行最佳组合的多准则优化,已经实现了三项效用输出的多联产发电。这些是电,热和高热值气体。在100%的供电可靠性下,平均电费成本为0.1美元/千瓦时。为了获得更好的经济性,要求至少20年的植物寿命。这项研究的数据来自印度一个小山丘小村庄,大多数人都是穷人。这项研究的方法论和结果代表了在特定地点使用当地资源对此类可持续能源系统的优化。

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