Economic Dispatch of Combined Heat and Power Systems using Particle Swarm Optimization

Shady M. Sadek
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Abstract

Due to the limitations and high cost of fossil fuel energy sources, combined heat and power units (CHPs) are gaining more attention recently as they are more efficient and less pollutant than conventional sources. In order to use CHP units more efficiently, the economic dispatch problem (EDP) is applied to obtain the optimal power and heat sources’ outputs to satisfy heat and power demands while meeting the different operational constraints. The problem is nonlinear and non-convex which requires heuristic technique to be used to solve this complex problem. Particle Swarm Optimization (PSO) is utilized due to its effectiveness in solving complex problems due to its high convergence speed with less number of iterations. The EDP main objective is to obtain optimal output power and heat of each unit while the total generation cost is minimized. The obtained results justify the superiority of the proposed method in solving such complicated problems.
基于粒子群算法的热电联产系统经济调度
由于化石燃料能源的局限性和高成本,热电联产装置(CHPs)由于其效率更高、污染更少而受到越来越多的关注。为了更有效地利用热电联产机组,应用经济调度问题(EDP),在满足不同运行约束的情况下,获得最优的功率和热源输出,以满足热电需求。该问题具有非线性和非凸性,需要使用启发式技术来解决这一复杂问题。粒子群优化算法(Particle Swarm Optimization, PSO)由于收敛速度快、迭代次数少,在解决复杂问题方面具有较好的应用前景。EDP的主要目标是在发电总成本最小的情况下,使各机组的输出功率和输出热量达到最优。所得结果证明了该方法在解决此类复杂问题方面的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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