Optimal Planning of Power Distribution Network by a Novel Modified Jaya Algorithm in Multiobjective Perspective

• Published in: IEEE systems journal Vol. 16; no. 3; pp. 4411 - 4422
• Main Authors: Pemmada, Sumanth, Patne, Nita, T, Ajay Kumar, Manchalwar, Ashwini
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.09.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Analytic hierarchy process; Capacitors; Costs; Distributed generation; Distributed generation (DG); Electric power distribution; Elitism; Graph theory; improved elitism oppositional Jaya algorithm (IEO-JA); Indexes; Minimization; multiobjective optimization; network reconfiguration; optimal planning; Optimization; Particle swarm optimization; power distribution network (PDN); Reactive power; Reconfiguration; Variable inertia; Voltage
• ISSN: 1932-8184; 1937-9234
• DOI: 10.1109/JSYST.2021.3132300

This article presents a novel improved Elitism oppositional Jaya algorithm for the optimal power distribution network reconfiguration and optimal sizing, siting of multiple distributed generations (DGs) with P , PQV buses. Here, PQV bus is a voltage-specified PQ type bus controlled by the P bus. In this proposed planning model, the basic Jaya algorithm is modified by incorporating variable inertia weight, vicinity searching capability, elitism property, and blended with an opposition learning-based strategy. This establishes an effective approach between global search and local search in quest of an optimal solution. A multiobjective framework is developed to optimize technical and economic objectives simultaneously. Optimal weights are allocated to each objective using an improved analytical hierarchy process method. Novel indices are proposed to identify the optimal locations of DGs also considering critical loads. During reconfiguration, the line data sequence is rearranged by a smart graph theory mechanism. Furthermore, different schemes have been studied by the suggested method on IEEE 33 and 69 bus distribution test systems. The findings of the study by using the proposed algorithm in comparison with particle swarm optimization (PSO) and enhanced leader PSO show its effectiveness and validity.