基于自然启发的萤火虫算法和粒子群算法的独立交直流混合微电网技术经济分析及优化规模

Kalyani Makarand Kurundkar, G. Karve, G. Vaidya
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引用次数: 0

摘要

微电网的技术经济分析及其最优规模是一个复杂的多目标问题。这种复杂性是由于资源和连接负载的不确定性造成的。在独立模式下的目标是在满足所有连接负载需求的同时将总成本最小化。在本研究中,微电网组成系统包括光伏发电系统、可调度柴油发电机系统、风能转换系统和蓄电池储能系统。在优化规模的同时,对两种不同的场景进行了技术经济分析,并使用自然启发的萤火虫算法(FA)和粒子群算法(PSO)对结果进行了比较。对于储能微电网的优化规模,电池荷电状态是决策因素,而柴油发电机组燃料成本是技术经济分析中最重要的因素。方案1考虑补贴燃料成本,电池SOC;方案2考虑无补贴燃料成本,且不考虑充电状态。结果表明,在补贴燃料成本的情况下,运行成本最低,但污染程度很高。如果取消补贴,那么只有可再生能源发电才是更有吸引力的选择。电池的能量水平是影响系统整体成本的重要因素。计算了单机模式下微电网的可靠性指标“失载概率指标”,考察了系统的最优规模。比较两种自然启发算法的结果,发现萤火虫算法比粒子群算法收敛更早,并且具有更好的最小化成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Techno-Economic Analysis and Optimal Sizing of Stand-alone Hybrid AC-DC Microgrid by Nature inspired Firefly algorithm and Particle Swarm Optimization
Techno-Economic analysis of microgrid and its optimal sizing is a complex multi-objective problem. This complexity is due to the uncertainty of resources and connected load. The objective in standalone mode is overall cost minimization while fulfilling all the connected load demand. In this study, microgrid components are system are Photovoltaic system, dispatchable Diesel Generator, Wind Energy Conversion system and Battery Energy Storage System. Along with Optimal sizing, techno-economic analysis is carried out for two different scenarios and results are compared using nature inspired Firefly Algorithm (FA) and Particle Swarm optimization (PSO). For optimal sizing of microgrid with energy storage, State of charge of battery (SOC) is decision making factor and for techno-economic analysis diesel generator fuel cost is most important factor. Scenario 1 is considering subsidized fuel cost, and SOC of battery and scenario 2 is considering unsubsidized fuel cost and without considering the State of charge. The results show that only under subsidized cost of fuel, the operation cost is minimum of the but pollution level is very high. If the subsidy is eliminated then, only power from renewable energy sources is more attractive option. The Energy level in battery is very important factor which impacts overall cost of the system. Reliability indices of microgrid in Stand-alone mode “Loss of load probability indices” are also calculated to examine the optimal sizing of the system. Comparing the results of both Nature inspired algorithms, it is found that Firefly algorithm converges earlier and gives better minimized cost as compared to PSO.
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