Multiple DGs for Reducing Total Power Losses in Radial Distribution Systems Using Hybrid WOA-SSA Algorithm

Abstract

Distributed generators (DGs) are currently extensively used to reduce power losses and voltage deviations in distribution networks. The optimal location and size of DGs achieve the best results. This study presents a novel hybridization of new metaheuristic optimizations in the last two years, namely, salp swarm algorithm (SSA) and whale optimization algorithm (WOA), for optimal placement and size of multi-DG units in radial distribution systems to minimize total real power losses (kW) and solve voltage deviation. This hybrid algorithm is implemented on IEEE 13- and 123-node radial distribution test systems. The OpenDSS engine is used to solve the power flow to find the power system parameters, such power losses, and the voltage profile through the MATLAB coding interface. Results describe the effectiveness of the proposed hybrid WOA-SSA algorithm compared with those of the IEEE standard case (without DG), repeated load flow method, and WOA and SSA algorithms applied independently. The analysis results via the proposed algorithm are more effective for reducing total active power losses and enhancing the voltage profile for various distribution networks and multi-DG units.

Multi‐objective planning model for multi‐phase distribution system under uncertainty considering reconfiguration

“…The proposed method also reduces the current unbalance and makes the system more balanced. Table 9 Comparison of proposed methodology with different existing method for IEEE 123-bus system Cases WOA [11] SSA [11] WOA-SSA [11] Fuzzy and sensitivity index based method [10] PSO [12] Jaya [12] Proposed method number of DGs/DG penetration 3 3 3 20% 3 3 3 optimal locations 90, 28, 160 149, 56, 97 152, 45, 67 85, 95, 114 67, 72, 47 64, 44, 86 49, 47, 23 optimal sizes,…”

“…Most of the studies simplified the unbalanced distribution system to single phase equivalents. In the given literature, the authors of [10][11][12] have taken feeder to unbalance into consideration, but demand uncertainty and network reconfiguration are not taken into consideration, and the study is performed only for wind DG integration by Zheng et al [10]. The authors of [11,12] have note considered uncertainty in DG output, demand uncertainty, network reconfiguration, and reliability analysis.…”

“…The proposed technique is also compared with the different existing algorithms in Table 9, and the highest reduction in loss and ENS is observed using the proposed methodology. Alzaidi et al [11] have not taken DG output and load demand uncertainty into consideration. Additionally, network reconfiguration is also not taken into consideration.…”

Coordinated Planning and Energy Conservation for Distribution Network with Renewable Energy: Standardized Information Model and Software

“…On the contrary, the electromagnetic radiation from distribution transformer, overhead lines, and cable lines may affect nearby residents which leads to a great deal of criticism. Furthermore, the research on renewable energy access planning of distribution network mainly includes planning algorithm [10][11][12], planning model [13][14][15], renewable energy siting and sizing [16][17][18][19][20], and collaborated planning between renewable energy and power system [21,22]. And, the evaluation indexes and intelligent planning software of distribution network environmental protection planning need to be further studied.…”

Hybrid PIPSO-SQP Algorithm for Real Power Loss Minimization in Radial Distribution Systems with Optimal Placement of Distributed Generation

“…Salp-swarm optimization [20] for real power loss reduction and muted salp swarm optimization [21] for compensation of reactive power were proposed in distribution systems. Meta-heuristic optimization techniques called salp swarm algorithm (SSA) and whale optimization algorithm (WOA),and a new hybrid method of WOA-SSA were explored in [22] for reducing the voltage deviation in IEEE 13 and 123 node RDS. Multi-objective optimization was attained with whale optimization algorithm by placing real and reactive power injecting DGs in RDS [23].…”