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Application of the stochastic fractal search algorithm and compromise programming to combined heat and power economic-emission dispatch

机译：随机分形搜索算法的应用和折衷程序组合热量和电力减排派遣

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摘要

Combined heat and power (CHP) generation is a competent configuration for simultaneous production of thermal and electric energy. The interdependency of heat and power outputs of CHP units presents complications and non-convexities in modelling and optimization. The nonlinear constrained economic dispatch optimization problem becomes more complex when one considers the pollution produced by generating units, transmission losses and valve-point effects of thermal units. This article uses the stochastic fractal search algorithm to solve the bi-objective combined heat and power economic dispatch (CHPED) problem. The CHPED problem has bounded feasible operating regions and many local minima. The compromise programming method is used to transform the two objective functions into an aggregated objective function. The results are compared with previous results obtained by many different methods reported in the literature. The results reveal that the proposed algorithm achieves a better near-global solution and compares favourably with other commonly used global optimization techniques.
机译：组合的热量和功率（CHP）生成是同时生产热能和电能的主管配置。 CHP单位的热量和功率输出的相互依存性具有建模和优化中的并发症和非凸起。当考虑通过产生单位产生的污染，热单元的传输损耗和阀点效应时，非线性受限的经济派遣优化问题变得更加复杂。本文使用随机分形搜索算法来解决双目标组合热量和电力经济调度（CHPED）问题。 CHPED问题有界有界可行的操作区域和许多当地最小值。折衷程序化方法用于将两个目标函数转换为聚合目标函数。将结果与通过文献中报道的许多不同方法获得的先前结果进行了比较。结果表明，该算法达到了更好的近全球解决方案，并与其他常用的全局优化技术有利地比较。

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