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首页> 外文会议>International Conference on Intelligent Technologies >Techno-Economic Analysis and Optimal Sizing of Stand-alone Hybrid AC-DC Microgrid by Nature inspired Firefly algorithm and Particle Swarm Optimization
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Techno-Economic Analysis and Optimal Sizing of Stand-alone Hybrid AC-DC Microgrid by Nature inspired Firefly algorithm and Particle Swarm Optimization

机译：特质启发萤火虫算法及粒子群优化独立杂交AC-DC微电网的技术经济分析和最优尺寸

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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.
机译：微电网的技术经济分析及其最佳尺寸是复杂的多目标问题。这种复杂性是由于资源和连接负载的不确定性。独立模式的目标是整体成本最小化，同时满足所有连接的负载需求。在该研究中，微电网部件是系统是光伏系统，可调度柴油发电机，风能转换系统和电池储能系统。随着最佳施胶，技术经济分析是针对两种不同场景进行的，并使用自然启发萤火虫算法（FA）和粒子群优化（PSO）进行比较结果。为了最佳地尺寸微电网与储能存储，电池（SOC）的充电状态是决策因素，而且技术经济分析柴油发电机燃料成本是最重要的因素。场景1正在考虑补贴燃料成本，电池和场景2的SOC考虑取消补贴的燃料成本，而不考虑充电状态。结果表明，只有在燃料的补贴成本下，运营成本最低，但污染水平非常高。如果删除了补贴，那么只有来自可再生能源的电源更具吸引力。电池中的能级是影响系统总成本的重要因素。单机模式中的微电网的可靠性指数还计算出概率的“负载概率指数”中的“丢失”以检查系统的最佳尺寸。比较两种自然启发算法的结果，发现萤火虫算法更早地收敛并提供与PSO相比的更大最小化成本。

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