基于改进矶鹞优化算法的微电网需求侧智能技术经济优化

Q2 Engineering Energy Harvesting and Systems Pub Date : 2023-09-28 DOI:10.1515/ehs-2023-0036
Mande Praveen, Venkata Siva Krishna Rao Gadi
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引用次数: 0

摘要

摘要:为实现分布式能源的优化集成和配电网的发电,在微电网系统中建立能量管理系统。最后,综合考虑技术指标和经济因素,以降低成本为重点,建立了多种机制。因此,本研究提出了一种新的启发式算法,称为改进矶鹞优化算法(M-SOA),用于将类der光伏(PV)、风力涡轮机和储能系统(ESS)优化集成到微电网中。其中,ISOA技术经济优化是通过考虑电网损耗、电压波动、供电成本、初始成本、运行成本、燃料成本、需求侧管理等指标的多目标函数,确定光伏、风电和ESS的最优容量。最后,对分布式能源进行了最优能量管理,并在IEEE-33总线网络上进行了模型实验。在整个结果分析中,所开发的M-SOA比AGTO、BOA、WOA和SOA的性能分别提高了3.84%、0.98%、5.72%和4.63%,且延迟更小。最后,以最小的供电成本、初始成本、运行成本和燃料成本,最大限度地提高能源效率为目标,进行了结果评价。
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Intelligent techno-economical optimization with demand side management in microgrid using improved sandpiper optimization algorithm
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.
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来源期刊
Energy Harvesting and Systems
Energy Harvesting and Systems Energy-Energy Engineering and Power Technology
CiteScore
2.00
自引率
0.00%
发文量
31
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