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Uncertainty handling in power system expansion planning under a robust multi-objective framework

机译:健壮的多目标框架下电力系统扩展规划中的不确定性处理

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In this study, a substantial idea has been reviewed which is useful in the investigation of the planning uncertainties. The concept relies on the optimality of an expansion plan in different conditions rather than the condition it has been optimised for. The method is developed in a manner that can be used in all sub-systems (i.e. generation, transmission and distribution) expansion planning. However, in this study the idea has been assessed for generation expansion planning (GEP). Cost and reliability have been considered as two major objectives of the planning and robustness has been added as a supplementary objective. The method can deal with uncertainty in both coefficients of the objective functions and the constraints. Two GEP models, one static and the other dynamic, have been proposed to examine the performance of the method in the uncertainty handling. In addition, the efficiency of the Taguchi's orthogonal array testing method has been compared with Monte Carlo simulation in the scenario generation. Two case studies have been provided to simplify the justification on the efficiency of the method.
机译:在这项研究中,已经审查了一个实质性的想法,这对于调查计划不确定性很有用。该概念取决于在不同条件下的扩展计划的最优性,而不是针对其进行优化的条件。以可以在所有子系统(即,发电,传输和分配)扩展计划中使用的方式开发该方法。但是,在这项研究中,已经对该想法进行了发电扩展计划(GEP)的评估。成本和可靠性已被视为规划的两个主要目标,而鲁棒性已被添加为补充目标。该方法可以处理目标函数的系数和约束的不确定性。已经提出了两种GEP模型,一种是静态模型,另一种是动态模型,以检验该方法在不确定性处理中的性能。此外,在场景生成中,田口正交阵列测试方法的效率已与蒙特卡洛模拟进行了比较。提供了两个案例研究,以简化该方法效率的合理性。

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