In this article, a modified version of the teaching-learning-basedoptimizationalgorithm is proposed for a combined optimization problem: simultaneous distributed generation (DG) scheduling, capacitor sizing, and rec...
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In this article, a modified version of the teaching-learning-basedoptimizationalgorithm is proposed for a combined optimization problem: simultaneous distributed generation (DG) scheduling, capacitor sizing, and reconfiguration of distribution networks to minimize active power loss and maximize reliability of the network. The objective of loss reduction is modeled as the benefit of not purchasing active power from the transmission grid. Customer interruption cost reduction is also used as the reliability improvement index. In this article, a new method for customer interruption cost calculation based on the bus injection to branch current (BIBC) matrix and Dijkstra's path-finding algorithm is proposed for different network topologies. The proposed approach is applied on a 69-bus test system that has been used in many previous studies. The results of the modifiedteaching-learning-basedoptimization are compared with those of some other optimization methods, including the conventional teaching-learning-basedoptimizationalgorithm. The results demonstrate the superiority of the proposed method and approach.
Classic unit commitment is the important and challenging task of allocating generating units subject to basic constraints over a scheduled time horizon to obtain the least generation cost. Penetration of distributed e...
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Classic unit commitment is the important and challenging task of allocating generating units subject to basic constraints over a scheduled time horizon to obtain the least generation cost. Penetration of distributed energy resources in modern power systems makes generation planning more complex. This article presents the individual and combined effect of three distributed energy resources, namely wind power generator as a renewable energy source, plug-in electric vehicles, and emergency demand response program on unit commitment. The inconsistent nature of wind speed and wind power is characterized by the Weibull probability distribution function considering overestimation and underestimation costs of stochastic wind power. The comprehensive comparative analysis of the economic viability on unit commitment is carried out to minimize the total cost of the entire system. To obtain the optimum solution, a modified teaching-learning-based optimization algorithm is used. The IEEE standard ten-unit test system is used for this study. To validate the efficacy of the modified teaching-learning-based optimization algorithm, a 26-unit reliability test system is also considered. It is found that the collective effect of wind power generator, plug-in electric vehicles, and emergency demand response program on unit commitment provides significant reduction in the total cost.
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