{"corpus_id":155643415,"paper_sha":"ef76e83e6aad1a9ecce2f966a6b03b37382bfd7d","doi":"10.1016/J.REF.2019.03.004","arxiv_id":null,"pmid":null,"pmcid":null,"mag_id":2942982252,"dblp_id":null,"acl_id":null,"title":"Thermal energy demand fulfillment of Kolhapur through modeling and optimization of integrated renewable energy systems","year":2019,"publication_date":"2019-06-01","venue":"Renewable Energy Focus","journal":{"name":"Renewable Energy Focus","pages":null,"volume":null},"journal_issn":null,"journal_title":null,"publication_types":[],"pubmed_pub_types":null,"s2_fields_of_study":["Engineering","Environmental Science"],"reference_count":27,"citation_count":10,"influential_citation_count":0,"is_open_access":false,"arxiv_categories":null,"arxiv_license":null,"arxiv_journal_ref":null,"mesh_headings":null,"chemicals":null,"comments_corrections":null,"source_flags":1,"s2_open_access_pdf_url":null,"s2_open_access_landing_url":null,"s2_open_access_license":null,"s2_open_access_status":null,"pmc_open_access_pdf_url":null,"pmc_open_access_landing_url":null,"pmc_open_access_license":null,"pmc_open_access_status":null,"unpaywall_open_access_pdf_url":null,"unpaywall_open_access_landing_url":null,"unpaywall_open_access_license":null,"unpaywall_open_access_status":null,"abstract":"To reduce the dependency on fossil fuels, the renewable energy systems must be utilized in an interactive manner and need to be optimized. Currently, the thermal energy demand of any city is mostly satisfied by the conventional resources. It produces considerable strain on fossile fuel reserves and lead to increase green house gas emissions also. The thermal demand of city can be satisfied by integrative use of renewable energy resources. This integrative use needs modelling and optimization. In this paper, optimised combinations of three renewable energy systems, such as solar water heating systems, biomass gasifiers and biogas energy systems are presented to satisfy the thermal demand of a region. A Microsoft excel optimizer software is used to solve the multiobjective optimization problem to find the optimum combinations. Minimization of lifecycle cost and CO2 emission are considered as main two multiobjectives. Particle Swarm Optimization (PSO) algorithm is utilized to solve the constraint optimization problem. The thermal energy demand satisfaction of Kolhapur city, a midtown city, in western Maharashtra, India, is taken for case study. The daily average thermal energy demand of one day for each month is satisfied in this case study for the whole year.","claims":[{"public_id":"cl_c040078ae6ae4201acf8f05f251c3105","status":"active","text":"Minimization of lifecycle cost and CO2 emission are the two main objectives in the multiobjective optimization problem.","confidence":0.95,"contributors":[{"id":32,"public_id":"7c402c1b98","public_label":"뀨 (7c402c1b98)","roles":["extraction"],"url":"https://sah.borca.ai/u/7c402c1b98"},{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["review"],"url":"https://sah.borca.ai/u/12632b8b5f"}],"url":"https://sah.borca.ai/claims/cl_c040078ae6ae4201acf8f05f251c3105"},{"public_id":"cl_9ca76b09b5f99f45faf1f98bdb71e5d3","status":"active","text":"Optimized combinations of solar water heating systems, biomass gasifiers, and biogas energy systems are presented to satisfy the thermal demand of Kolhapur 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