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The influence of carbon dioxide trading scheme on economic dispatch of generators

机译:二氧化碳交易计划对发电机经济调度的影响

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This paper aims at probing into the topic of power units' operation and dispatch based on Carbon Dioxide (CO_2) trading scheme. The trading cost of CO_2 emission is embedded into the traditional economic dispatch model, which will be solved by the New Particle Swarm Optimization (NPSO). By considering the CO_2 trading scheme, the influences of the various strategies for unit's dispatch are simulated and analyzed in this paper. The proposed method, NPSO is developed in such a way that PSO with Constriction Factor (PSO-CF) algorithm is applied as a based level search. NPSO introduces two operators, "Random Particles" and "Fine-Tuning" into the PSO-CF algorithm to improve the drawback of searching global optimum and make the search method more efficient at the end of search. The efficiency and ability of NPSO is demonstrated by the six generating units. Simulation results indicated that reasonable solutions provide a practical and flexible framework for power sectors. They can be also used for generating alternatives and thus help decision makers to obtain the goals of minimal operation cost under their desired emission's policies.
机译:本文旨在探讨基于二氧化碳(CO_2)交易方案的动力装置的运行和调度问题。 CO_2排放的交易成本已嵌入到传统的经济调度模型中,这将通过新粒子群算法(NPSO)解决。通过考虑CO_2交易方案,模拟分析了各种策略对单位派遣的影响。提出的方法NPSO的开发方式是将具有收缩因子的PSO(PSO-CF)算法用作基于级别的搜索。 NPSO在PSO-CF算法中引入了两个运算符“随机粒子”和“微调”,以改善搜索全局最优的缺点,并使搜索方法在搜索结束时更加高效。六个发电单元证明了NPSO的效率和能力。仿真结果表明,合理的解决方案为电力部门提供了一种实用且灵活的框架。它们还可以用于生成替代方案,从而帮助决策者在其所需的排放政策下实现最低运营成本的目标。

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