Optimized integration of photovoltaic systems and distribution static compensators in distribution networks using a novel discrete-continuous version of the adaptive JAYA algorithm (AJAYA)

• Published in: Results in engineering Vol. 26; p. 104726
• Main Authors: Cubillo-Leyton, Paolo Iván, Montoya, Oscar Danilo, Grisales-Noreña, Luis Fernando
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.06.2025; Elsevier
• Subjects: D-STATCOMs; Investment cost reduction; Master-slave optimizer: JAYA; Metaheuristic optimization; Operating cost reduction; PV generation; Metaheuristic optimization; Operating cost reduction; Investment cost reduction; PV generation; Master-slave optimizer: JAYA; D-STATCOMs
• ISSN: 2590-1230; 2590-1230
• DOI: 10.1016/j.rineng.2025.104726

This document addresses the problem regarding the optimal siting and sizing of photovoltaic generators (PVs) and distributed static compensators (D-STATCOMs) in electrical distribution networks, with annualized investment and operating costs minimization as the objective function, incorporating a 10% investment recovery rate and a 2% annual energy cost increase. All of the above is subject to the set of technical and operational constraints associated with electrical feeders that incorporate distributed energy resources (DERs). As a solution methodology, this work proposes a master-slave methodology. Here, the master stage employs an adapted discrete-continuous version of the JAYA algorithm, which is entrusted with siting and sizing the aforementioned devices. Meanwhile, the slave stage uses a matrix-based power flow version of the successive approximations (SA) method to evaluate the problem's objective function and constraints for the solution proposed by the master stage. For comparison, the discrete-continuous versions of the vortex search algorithm (VSA), the sine-cosine algorithm (SCA), Phasor Particle Swarm Optimization (PPSO), New Self-Organising Hierarchical PSO (NHPSO-JTVAC), Differential Evolution (DE), Gold Search Optimization (GSO) and the classical version of JAYA are used, validating the effectiveness of our proposal on the 33- and 69-bus test systems while considering variable generation and demand. In terms of the best solution, the average solution, and the required processing times, the AJAYA-SA strategy yields the best results in both test systems, making it the most efficient method to solve the problem under study. •Optimal PV and D-STATCOM placement minimizes annual costs in distribution networks.•JAYA-Successive Approximations method outperforms other optimization techniques.•Superior results achieved in solution quality and processing time on 33 and 69-bus systems.