Optimal Network Reconfiguration and Distributed Generation Placement in Distribution System Using a Hybrid Algorithm

Abstract

In this paper a method for solving optimal distribution network reconfiguration and optimal placement distributed generation (DG) with the objective of reducing power losses and improving voltage profile with the least amount of time using a combination of various techniques is offered. In the proposed method, first, a meta-heuristic algorithm (MHA) is used to solve the problem of optimal DG placement. The search space for using this technique has been reduced to the optimal scale which is why this technique is accurate and quick. After solving optimal DG placement using the abovementioned technique, a binary particular swarm optimization algorithm (BPSO) is presented for solving the network reconfiguration. In fact, by reducing the search space, the speed of the technique for solving the problem is improved. The proposed technique has been implemented with different scenarios on IEEE 33-and 69-node test systems. The comparison of the results with those of other methods indicates the effectiveness of this technique.

Distribution network reconfiguration considering DGs using a hybrid CS-GWO algorithm for power loss minimization and voltage profile enhancement

“…In this paper, both DNR and DG allocation problem is solved simultaneously by applying a hybrid CS-GWO algorithm to obtain a desired optimal solution. [41], hypercube ant colony optimization algorithm [42], Fireworks Algorithm [43], modified plant growth simulation algorithm [44], adaptive cuckoo search [45], binary particular swarm optimization algorithm [46], enhanced evolutionary algorithm [47], uniform voltage distribution based constructive reconfiguration algorithm [48], discrete artificial bee colony algorithm [49], Harmony search algorithm (HSA) and particle artificial bee colony algorithm (PABC) [50], hybrid Grey Wolf Optimizer (GWO)-Sine Cosine Algorithm (SCA) [51], hybrid Particle Swarm Optimizer (PSO)-ant colony optimization (ACO) [52], comprehensive teaching-learning-based optimization algorithm [53], Grey Wolf Optimizer (GWO) and Particle Swarm Optimizer (PSO) [54], Strength Pareto Evolutionary Algorithm 2 [55], adaptive shuffled frogs leaping algorithm [56], Particle swarm optimization (PSO) and Dragonfly algorithm (DA) [57], Stochastic fractal search algorithm [58], Mixed Particle Swarm Optimization [59], Symbiotic Organism Search Algorithm [60], Equilibrium optimization algorithm [61], Harris Hawks Optimization [62], Meta-heuristic matrix moth-flame algorithm [63], Bacterial Foraging with Spiral Dynamic (BF-SD) algorithm [64], chaotic stochastic fractal search algorithm [66], Modified Selective particle swarm optimization (SPSO) method [73], Grasshopper optimization algorithm (GOA) [74], Grid based Multi-Objective Harmony Search Algorithm (GrMHSA) [75], Modified Whale Optimization (MOWOA) algorithm and fuzzy decision-making method [77], Fuzzy Expert System (FES) method [78], Manta-Ray Foraging Optimization (MRFO) algorithm [79], Rider Optimization Algorithm [80]. The summary of rece...…”

A Mixed-Integer Linear Programming Model for the Simultaneous Optimal Distribution Network Reconfiguration and Optimal Placement of Distributed Generation

“…[50] uses a Modified Teaching-Learning-Based Optimization Algorithm to address the simultaneous DG siting and DNR. In [51], the authors handle the problem of optimal DG placement with a metaheuristic algorithm, and subsequently solve the network reconfiguration problem with a Binary Particle Swarm Optimization Technique (BPSO). In [52], the authors implement a metaheuristic Grasshopper Optimization Algorithm (GOA) inspired by the swarming behavior of grasshoppers in nature to solve the simultaneous optimal DNR and DG placement to minimize active power losses.…”

Wireless Control System for Three Phase Loads Balancing in Distribution Networks

“…As the operating time of the network increases, the percentage of consumption of electricity will increase and in the same time the imbalance between the three phases will increase [2]. The tendency to increase in unbalance load is due to [1]:…”

“…The current of neutral conductor in substation transformer can be reduced by this method but the cost of the used device is another problem [2]. Another method for balancing the current in the substation transformer is by always measuring the output currents and exchanging the connection of largest and smallest load phases [3].…”