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An optimal solution for Combined Economic and Emission Dispatch problem using Artificial Bee Colony Algorithm

机译:基于人工蜂群算法的经济与排放联合调度问题的最优解

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In India Electrical Energy is generated mainly Coal based Thermal Power stations and hydro Electric Power Stations. The main aim of power generating company is to provide good quality and reliable power to consumers at minimum cost. The problem of Combined Economic and Emission Dispatch deals with the minimization of both fuel cost and emission of pollutants such as oxides of Nitrogen and Oxides of Sulphur. In our power system the emission is major problem created that's why in now a days we move from green energy source or renewable energy such as Sunlight, Wind, Tides, Wave, and Geothermal Heat Energy. The Emission constrained Economic Dispatch problem treats the emission limit as an additional constraint and optimizes the fuel cost. In this paper we optimizes the Combined Economic and Emission Dispatch problem by using two different optimization method such as Artificial Bee Colony (ABC) and Genetic Algorithm (GA). The proposed ABC Algorithm has been successfully implemented is to IEEE 30 bus and Indian Utility sixty two Bus System The simulation result are compare and found the effective algorithm for Combined Economic and Emission Dispatch problem.
机译:在印度,电能主要产生于煤基热电站和水力发电站。发电公司的主要目标是以最低的成本为消费者提供优质和可靠的电力。经济和排放调度相结合的问题在于使燃料成本和污染物(例如氮氧化物和硫氧化物)的排放最小化。在我们的电力系统中,排放是造成的主要问题,这就是为什么现在我们从绿色能源或可再生能源(如阳光,风能,潮汐能,波浪能和地热能)转移到现在的原因。排放受限的经济调度问题将排放限值视为附加约束,并优化了燃料成本。在本文中,我们通过使用两种不同的优化方法,例如人工蜂群(ABC)和遗传算法(GA),优化了经济和排放分配联合问题。所提出的ABC算法已经成功地实现了对IEEE 30总线和印度公用事业的62总线系统的仿真结果,并进行了比较,发现了有效的经济与排放调度相结合的算法。

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