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This paper describes a computational procedure to establish the optimal distribution of network reconfiguration by means of a novel gray wolf optimization (GWO) algorithm. The procedure aimed to diminish the system’s power loss and produce a better voltage profile while fulfilling the operating constraints described by different operating conditions. Under practical restrictions, the distribution network reconfiguration (DNR) problem is classified as multimodal and highly nonlinear. Constraint breaches were appropriately handled to produce stable convergence characteristics, and high-quality solutions were obtained in a shorter execution time. The 33-bus and 69-bus systems were used to obtain the optimal reconfiguration by incorporating the method developed in this work. The simulation results obtained were collated and compared with the outcomes of other well-known optimization techniques, confirming the efficacy of the GWO algorithm in solving the DNR problem.

This paper presents the analysis of Static Synchronous Series Compensator (SSSC) and Capacitive Energy storage (CES) based on hydrothermal system under open market scenario employing fuzzy logic controller. The formulation of Load Frequency Control (LFC) problem has been greatly affected due to open transmission access and evolution of more socialized companies for generation, transmission and distribution. The traditional LFC has been modified by taking into account the concept of bilateral contracts. Attempt has also been made to incorporate the concept of SSSC and CES to further improve the performance of the system. A detailed representation of design of Fuzzy Logic Controller (FLC) has been represented and the results have been compared with those of dual mode controller. The results indeed demonstrate the superior working of FLC than that of dual mode controller and the system shows better response with respect to peak time, overshoot and settling time in the presence of FLC.

Purpose The purpose of this paper is to focus on the cost-effective and environmentally sustainable operation of thermal power systems to allocate optimum active power generation resultant for a feasible solution in diverse load patterns using the grey wolf optimization (GWO) algorithm. Design/methodology/approach The economic dispatch problem is formulated as a bi-objective optimization subjected to several operational and practical constraints. A normalized price penalty factor approach is used to convert these objectives into a single one. The GWO algorithm is adopted as an optimization tool in which the exploration and exploitation process in search space is carried through encircling, hunting and attacking. Findings A linear interpolated price penalty model is developed based on simple analytical geometry equations that perfectly blend two non-commensurable objectives. The desired GWO algorithm reports a new optimum thermal generation schedule for a feasible solution for different operational strategies. These are better than the earlier reports regarding solution quality. Practical implications The proposed method seems to be a promising optimization tool for the utilities, thereby modifying their operating strategies to generate electricity at minimum energy cost and pollution levels. Thus, a strategic balance is derived among economic development, energy cost and environmental sustainability. Originality/value A single optimization tool is used in both quadratic and non-convex cost characteristics thermal modal. The GWO algorithm has discovered the best, cost-effective and environmentally sustainable generation dispatch.