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Optimal operational planning and control of energy plants by e constrained particle swarm optimization

机译:约束粒子群算法对能源工厂的最佳运营计划和控制

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This paper introduces optimal operational planning of energy plants via the e constrained particle swarm optimization (PSO). In order to generate optimal operational planning for energy plants, startup/shutdown status and/or input/output values of the facilities at each control interval should be determined. The problem can be formulated as a large-scale mixed-integer nonlinear problem (MINLP). PSO is one of the solutions for MINLP. If the formulated MINLP has various equality and inequality constraints, it remains difficult to solve it by naive PSO. In this paper, to overcome the difficulty, we propose the improved PSO approach using the ε constrained method for MINLP. The result show the effectiveness of the proposed method compared with conventional methods.
机译:本文通过e约束粒子群优化(PSO)介绍了能源工厂的最佳运营计划。为了生成能源工厂的最佳运行计划,应确定每个控制间隔内设施的启动/关闭状态和/或设备的输入/输出值。该问题可以表述为大规模混合整数非线性问题(MINLP)。 PSO是MINLP的解决方案之一。如果制定的MINLP具有各种平等和不平等约束,那么仍然很难通过朴素的PSO来解决。在本文中,为克服这一困难,我们针对MINLP提出了一种使用ε约束方法的改进PSO方法。结果表明,与传统方法相比,该方法是有效的。

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