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首页> 外文期刊>Journal of Intelligent Learning Systems and Applications >A Novel Self Adaptive Modification Approach Based on Bat Algorithm for Optimal Management of Renewable MG
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A Novel Self Adaptive Modification Approach Based on Bat Algorithm for Optimal Management of Renewable MG

机译：基于Bat算法的新型MG优化管理自适应修改新方法。

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摘要

In the new competitive electricity market, the accurate operation management of Micro-Grid (MG) with various types of renewable power sources (RES) can be an effective approach to supply the electrical consumers more reliably and economically. In this regard, this paper proposes a novel solution methodology based on bat algorithm to solve the op- timal energy management of MG including several RESs with the back-up of Fuel Cell (FC), Wind Turbine (WT), Photovoltaics (PV), Micro Turbine (MT) as well as storage devices to meet the energy mismatch. The problem is formulated as a nonlinear constraint optimization problem to minimize the total cost of the grid and RESs, simultaneously. In addition, the problem considers the interactive effects of MG and utility in a 24 hour time interval which would in- crease the complexity of the problem from the optimization point of view more severely. The proposed optimization technique is consisted of a self adaptive modification method compromised of two modification methods based on bat algorithm to explore the total search space globally. The superiority of the proposed method over the other well-known algorithms is demonstrated through a typical renewable MG as the test system.
机译：在新的竞争性电力市场中，具有各种类型的可再生电源（RES）的Micro-Grid（MG）的精确运行管理可以成为更可靠，更经济地为用电者供电的有效方法。在这方面，本文提出了一种基于蝙蝠算法的新颖的解决方案方法，以解决包括多个RES在内的MG的最佳能量管理，其中包括燃料电池（FC），风力涡轮机（WT），光伏（PV） ，微型涡轮机（MT）以及存储设备可满足能源不匹配的需求。将该问题表述为非线性约束优化问题，以同时最小化网格和RES的总成本。此外，该问题考虑了MG和实用程序在24小时时间间隔内的交互作用，从优化的角度来看，这将严重增加问题的复杂性。所提出的优化技术由一种自适应修改方法组成，该方法对基于蝙蝠算法的两种修改方法进行了折衷，以全面探索整个搜索空间。通过典型的可再生MG作为测试系统，证明了该方法相对于其他知名算法的优越性。

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