Optimal Power Dispatch of DGs in Radial and Mesh AC Grids: A Hybrid Solution Methodology between the Salps Swarm Algorithm and Successive Approximation Power Flow Method

Abstract

In this paper, we address the problem of the optimal power dispatch of Distributed Generators (DGs) in Alternating Current (AC) networks, better known as the Optimal Power Flow (OPF) problem. We used, as the objective function, the minimization of power losses (Ploss) associated with energy transport, which are subject to the set of constraints that compose AC networks in an environment of distributed generation. To validate the effectiveness of the proposed methodology in solving the OPF problem in any network topology, we employed one 10-node mesh test system and three radial text systems: 10, 33, and 69 nodes. In each test system, DGs were allowed to inject 20%, 40%, and 60% of the power supplied by the slack generator in the base case. To solve the OPF problem, we used a master–slave methodology that integrates the optimization method Salps Swarm Algorithm (SSA) and the load flow technique based on the Successive Approximation (SA) method. Moreover, for comparison purposes, we employed some of the algorithms reported in the specialized literature to solve the OPF problem (the continuous genetic algorithm, the particle swarm optimization algorithm, the black hole algorithm, the antlion optimization algorithm, and the Multi-Verse Optimizer algorithm), which were selected because of their excellent results in solving such problems. The results obtained by the proposed solution methodology demonstrate its superiority and convergence capacity in terms of minimization of Ploss in both radial and mesh systems. It provided the best reduction in minimum Ploss in short processing times and showed excellent repeatability in each test system and scenario under analysis.

An Energy Management System for PV Sources in Standalone and Connected DC Networks Considering Economic, Technical, and Environmental Indices

“…In order to evaluate the effectiveness and robustness of the proposed methodology in terms of solution quality, repeatability, and processing times, this paper adapted three continuous optimization methods highly used in the literature for solving the optimal power flow problem in DC networks while considering the operation of PV distributed generators: MVO, PSO, and the CSA. These methodologies were selected due to their excellent performance and high effectiveness [50]. The complete description and iterative algorithms of said techniques are presented in the cited references.…”

Parameter Estimation of a Thermoelectric Generator by Using Salps Search Algorithm

“…This value is compared with real power measured in the TEG by obtaining the RMSE used by the SSA as the objective function. The SSA was chosen for this study due to its proven effectiveness in optimizing the parameter estimation of electrical devices, as demonstrated in previous research [30][31][32]. This optimization method is a bio-inspired algorithm that is based on the collective behavior of salps, gelatinous marine organisms that move in swarms to locate the best sources of food.…”