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CHP Economic Dispatch Considering Prohibited Zones to Sustainable Energy Using Self-Regulating Particle Swarm Optimization Algorithm

机译:考虑禁止区域对可持续能源的CHP经济派遣使用自调节粒子群优化算法

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摘要

Economic dispatch is the optimal scheduling for generating units with technical constraints. Combined heat and power economic dispatch (CHPED) refers to minimization of the total energy cost for generating electricity and heat supply to load demand. This planning model integrates heat and power energy to balance energy supply and demand, mitigate climate change and improve energy efficiency of sustainable cities and green buildings. In this paper for the first time, self-regulating particle swarm optimization (SRPSO) algorithm is utilized for solving the CHPED problem by considering valve point effects and prohibited zones on fuel cost function of pure generation units and electrical power losses in transmission systems. The main advantage of SRPSO algorithm to PSO algorithm is the inertia weight flexibility with respect to search conditions. In this algorithm, unlike PSO algorithm that inertia weight reduces in each iteration, this value increases or reduces proportional to particles' positions, which will lead particles to achieve optimal value with higher speed. The capability and effectiveness of the proposed algorithm are evaluated on a large-scale energy system using MATLAB environment. The results obtained by SRPSO algorithm are outperformed by other optimization methods from the economic, sustainable energy and time consumption point of view.
机译:经济调度是用技术限制产生单位的最佳调度。综合热量和功率经济调度(CHPED)是指最小化用于发电和供热以负荷需求的总能源成本。该规划模式集成了热量和电力能源来平衡能源供需,减轻气候变化,提高可持续城市和绿色建筑的能效。在本文首次,通过考虑阀点效应和禁止区域对传输系统中的燃料成本函数的燃料成本函数和电力损耗来解决对CHPED问题的自调节粒子群优化(SRPSO)算法。 SRPSO算法对PSO算法的主要优点是关于搜索条件的惯性重量灵活性。在该算法中,与惯性重量在每次迭代中减少的PSO算法不同,该值增加或减少与粒子的位置成比例,这将导致粒子以更高的速度实现最佳值。使用MATLAB环境的大规模能量系统评估所提出的算法的能力和有效性。 SRPSO算法获得的结果由来自经济,可持续能量和时间消耗的其他优化方法表现优势。

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