Intelligent techno-economical optimization with demand side management in microgrid using improved sandpiper optimization algorithm
The energy management system is established in the microgrid system for optimally integrating the Distributed Energy Resources (DERs) and generating the power distribution grids. At last, diverse mechanisms have been highly concentrated on cost reduction and at the same time, both the technical indi...
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creator | Praveen, Mande Gadi, Venkata Siva Krishna Rao |
description | The energy management system is established in the microgrid system for optimally integrating the Distributed Energy Resources (DERs) and generating the power distribution grids. At last, diverse mechanisms have been highly concentrated on cost reduction and at the same time, both the technical indices and economic factors are considered. Thus, this research work suggests a new heuristic algorithm termed Modified Sandpiper optimization algorithm (M-SOA) for optimal integration of DER-like Photo Voltaic (PV), wind turbines, and Energy Storage Systems (ESS) into microgrids. Here, the techno-economical optimization with ISOA is designed for determining the optimal capacity of PV, Wind Turbine, and ESS via the multi-objective function concerning measures like network power losses, voltage fluctuations, Electricity Supply Costs, initial cost, operation cost, fuel cost, and demand side management. Finally, the optimal energy management is done on distributed energy resources, and this developed model experiments on the IEEE-33 bus network. Throughout the result analysis, the developed M-SOA obtains 3.84 %, 0.98 %, 5.72 %, and 4.63 % better performance with less latency than the AGTO, BOA, WOA, and SOA. Finally, the result evaluation is done for minimizing the Electricity Supply Costs, initial cost, operation cost, and fuel cost and maximize energy efficiency. |
doi_str_mv | 10.1515/ehs-2023-0036 |
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At last, diverse mechanisms have been highly concentrated on cost reduction and at the same time, both the technical indices and economic factors are considered. Thus, this research work suggests a new heuristic algorithm termed Modified Sandpiper optimization algorithm (M-SOA) for optimal integration of DER-like Photo Voltaic (PV), wind turbines, and Energy Storage Systems (ESS) into microgrids. Here, the techno-economical optimization with ISOA is designed for determining the optimal capacity of PV, Wind Turbine, and ESS via the multi-objective function concerning measures like network power losses, voltage fluctuations, Electricity Supply Costs, initial cost, operation cost, fuel cost, and demand side management. Finally, the optimal energy management is done on distributed energy resources, and this developed model experiments on the IEEE-33 bus network. Throughout the result analysis, the developed M-SOA obtains 3.84 %, 0.98 %, 5.72 %, and 4.63 % better performance with less latency than the AGTO, BOA, WOA, and SOA. Finally, the result evaluation is done for minimizing the Electricity Supply Costs, initial cost, operation cost, and fuel cost and maximize energy efficiency.</description><identifier>ISSN: 2329-8774</identifier><identifier>EISSN: 2329-8766</identifier><identifier>DOI: 10.1515/ehs-2023-0036</identifier><language>eng</language><publisher>Berlin: De Gruyter</publisher><subject>Algorithms ; Demand side management ; distributed energy resources ; Distributed generation ; Economic factors ; Electric power demand ; Electric power loss ; Electricity ; Energy costs ; Energy efficiency ; Energy management ; Energy resources ; Energy sources ; Energy storage ; Fuels ; Heuristic methods ; microgrid ; modified sandpiper optimization algorithm ; Objective function ; Optimization ; Optimization algorithms ; Storage systems ; techno-economical optimization ; Turbines ; Wind power ; Wind turbines</subject><ispartof>Energy harvesting and systems, 2024-01, Vol.11 (1)</ispartof><rights>2024. 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At last, diverse mechanisms have been highly concentrated on cost reduction and at the same time, both the technical indices and economic factors are considered. Thus, this research work suggests a new heuristic algorithm termed Modified Sandpiper optimization algorithm (M-SOA) for optimal integration of DER-like Photo Voltaic (PV), wind turbines, and Energy Storage Systems (ESS) into microgrids. Here, the techno-economical optimization with ISOA is designed for determining the optimal capacity of PV, Wind Turbine, and ESS via the multi-objective function concerning measures like network power losses, voltage fluctuations, Electricity Supply Costs, initial cost, operation cost, fuel cost, and demand side management. Finally, the optimal energy management is done on distributed energy resources, and this developed model experiments on the IEEE-33 bus network. Throughout the result analysis, the developed M-SOA obtains 3.84 %, 0.98 %, 5.72 %, and 4.63 % better performance with less latency than the AGTO, BOA, WOA, and SOA. Finally, the result evaluation is done for minimizing the Electricity Supply Costs, initial cost, operation cost, and fuel cost and maximize energy efficiency.</description><subject>Algorithms</subject><subject>Demand side management</subject><subject>distributed energy resources</subject><subject>Distributed generation</subject><subject>Economic factors</subject><subject>Electric power demand</subject><subject>Electric power loss</subject><subject>Electricity</subject><subject>Energy costs</subject><subject>Energy efficiency</subject><subject>Energy management</subject><subject>Energy resources</subject><subject>Energy sources</subject><subject>Energy storage</subject><subject>Fuels</subject><subject>Heuristic methods</subject><subject>microgrid</subject><subject>modified sandpiper optimization algorithm</subject><subject>Objective function</subject><subject>Optimization</subject><subject>Optimization algorithms</subject><subject>Storage systems</subject><subject>techno-economical optimization</subject><subject>Turbines</subject><subject>Wind power</subject><subject>Wind turbines</subject><issn>2329-8774</issn><issn>2329-8766</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNptkM1LwzAYxoMoOHRH7wHP1Xw0TXuU4cdg4EXPIUvfdhltUpPOMa_-46ZMFMHAS57D73mS90HoipIbKqi4hU3MGGE8I4QXJ2jGOKuyUhbF6Y-W-Tmax7glhFAmhKTlDH0u3QhdZ1twIx7BbJzPwHjne2t0h_0w2t5-6NF6h_d23OAaeu1qHG0NOCndQj9ZrcPJEXwbbI130boW234I_h0SmwyDHSD8jdNd60OK7C_RWaO7CPPv-wK9Pty_LJ6y1fPjcnG3ygwtBc0oWa-hkQCSi4o3RZVzWpIGgBbMkCYNE82amVzkUJeSJNCkQw2XQhuo-QW6Puamf73tII5q63fBpScVq1hJixQsE5UdqbRNjAEaNQTb63BQlKipapWqVlPVaqo68eWR3-tuhFBDG3aHJH7D__VRSvkXJJGIrw</recordid><startdate>20240101</startdate><enddate>20240101</enddate><creator>Praveen, Mande</creator><creator>Gadi, Venkata Siva Krishna Rao</creator><general>De Gruyter</general><general>Walter de Gruyter GmbH</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>KB.</scope><scope>L6V</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PDBOC</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope></search><sort><creationdate>20240101</creationdate><title>Intelligent techno-economical optimization with demand side management in microgrid using improved sandpiper optimization algorithm</title><author>Praveen, Mande ; Gadi, Venkata Siva Krishna Rao</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c1851-10bbef7ee73593f6943180fee162c0f2c025fb2c454ed870ee7cccc1c375aced3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Algorithms</topic><topic>Demand side management</topic><topic>distributed energy resources</topic><topic>Distributed generation</topic><topic>Economic factors</topic><topic>Electric power demand</topic><topic>Electric power loss</topic><topic>Electricity</topic><topic>Energy costs</topic><topic>Energy efficiency</topic><topic>Energy management</topic><topic>Energy resources</topic><topic>Energy sources</topic><topic>Energy storage</topic><topic>Fuels</topic><topic>Heuristic methods</topic><topic>microgrid</topic><topic>modified sandpiper optimization algorithm</topic><topic>Objective function</topic><topic>Optimization</topic><topic>Optimization algorithms</topic><topic>Storage systems</topic><topic>techno-economical optimization</topic><topic>Turbines</topic><topic>Wind power</topic><topic>Wind turbines</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Praveen, Mande</creatorcontrib><creatorcontrib>Gadi, Venkata Siva Krishna Rao</creatorcontrib><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>Materials Science Database</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Materials Science Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><jtitle>Energy harvesting and systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Praveen, Mande</au><au>Gadi, Venkata Siva Krishna Rao</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Intelligent techno-economical optimization with demand side management in microgrid using improved sandpiper optimization algorithm</atitle><jtitle>Energy harvesting and systems</jtitle><date>2024-01-01</date><risdate>2024</risdate><volume>11</volume><issue>1</issue><issn>2329-8774</issn><eissn>2329-8766</eissn><abstract>The energy management system is established in the microgrid system for optimally integrating the Distributed Energy Resources (DERs) and generating the power distribution grids. At last, diverse mechanisms have been highly concentrated on cost reduction and at the same time, both the technical indices and economic factors are considered. Thus, this research work suggests a new heuristic algorithm termed Modified Sandpiper optimization algorithm (M-SOA) for optimal integration of DER-like Photo Voltaic (PV), wind turbines, and Energy Storage Systems (ESS) into microgrids. Here, the techno-economical optimization with ISOA is designed for determining the optimal capacity of PV, Wind Turbine, and ESS via the multi-objective function concerning measures like network power losses, voltage fluctuations, Electricity Supply Costs, initial cost, operation cost, fuel cost, and demand side management. Finally, the optimal energy management is done on distributed energy resources, and this developed model experiments on the IEEE-33 bus network. Throughout the result analysis, the developed M-SOA obtains 3.84 %, 0.98 %, 5.72 %, and 4.63 % better performance with less latency than the AGTO, BOA, WOA, and SOA. Finally, the result evaluation is done for minimizing the Electricity Supply Costs, initial cost, operation cost, and fuel cost and maximize energy efficiency.</abstract><cop>Berlin</cop><pub>De Gruyter</pub><doi>10.1515/ehs-2023-0036</doi><tpages>20</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Demand side management distributed energy resources Distributed generation Economic factors Electric power demand Electric power loss Electricity Energy costs Energy efficiency Energy management Energy resources Energy sources Energy storage Fuels Heuristic methods microgrid modified sandpiper optimization algorithm Objective function Optimization Optimization algorithms Storage systems techno-economical optimization Turbines Wind power Wind turbines |
title | Intelligent techno-economical optimization with demand side management in microgrid using improved sandpiper optimization algorithm |
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