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Price Based Unit Commitment Problem Solution using Shuffled Frog Leaping Algorithm

机译:基于混搭蛙跳算法的基于价格的机组承诺问题求解

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In this paper, an algorithm to solve the Price Based Unit Commitment Problem (PBUCP) under deregulated environment has been proposed using Shuffled Frog Leaping Algorithm (SFLA) intelligent technique to maximize the GENeration COmpanies (GENCOs) profit. Price / Profit-based UC formulation which considers the softer demand constraint and allocates fixed and transitional costs to the scheduled hours. Deregulation in power sector increases the efficiency of electricity production and distribution, offer lower prices, higher quality, a secure and a more reliable product to consumers. This methodology performed great challenges for the power industry and thus an individual human can take their own decision by choosing the reliable continuous supply of power from the electricity markets at an affordable price. Under restructured system, GENCOs schedules their generators with the objective of maximizing their profit. This proposed algorithm is for a small unit test system with 10 units 24 hour data and the simulations are carried out to show the performance of proposed methodology using MATLAB software. It is observed from the simulation results that the proposed algorithm provides maximum profit with less computational time compared to existing methods.
机译:本文提出了一种使用随机蛙跳算法(SFLA)智能技术来解决管制环境下基于价格的单位承诺问题(PBUCP)的算法,以最大化发电公司(GENCO)的利润。基于价格/利润的UC公式,该公式考虑了较弱的需求约束,并将固定成本和过渡成本分配给计划工时。电力部门放松管制可以提高电力生产和分配的效率,为消费者提供更低的价格,更高的质量,更安全,更可靠的产品。这种方法对电力行业提出了巨大挑战,因此,每个人都可以通过以可承受的价格从电力市场中选择可靠的持续电力供应来做出自己的决定。在重组系统下,GENCO调度发电机的目的是最大程度地提高他们的利润。该算法适用于具有10个单元的24小时数据的小型单元测试系统,并通过仿真进行了仿真,以证明使用MATLAB软件的方法的性能。从仿真结果可以看出,与现有方法相比,所提出的算法以更少的计算时间提供了最大的收益。

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