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.
Highlights
Distributed Generation plays an important role in electricity markets and power systems
Step 2: We find the node that has the least voltage profile and select it as the first candidate for installing distributed generation (DG)
Scenario I: The system is without reconfiguration and DG (Base case); Scenario II: The system is with reconfiguration and without DG unit; Scenario III: The system is without reconfiguration and with installation of the first DG unit; Scenario IV: The system is with reconfiguration and installation of the first DG unit; Scenario V: The system is without reconfiguration and with installation of the two DG units; Scenario VI: The system is with reconfiguration and installation of the two DG units; Scenario VII: The system is without reconfiguration and with installation of the three DG units; Scenario VIII: The system is with reconfiguration and installation of the three DG units (Optimal solution)
Summary
Distributed Generation plays an important role in electricity markets and power systems. Installation of DG on distribution feeders can have a significant impact on power system operation and control [1]. DG can be fitted with different strategies in the power network. Reducing power losses, cost reduction peak load, improving voltage profile or system reliability, all depend on the location and size of the DG [2]. Since selection of the best locations and sizes of DG units is a complex combinatorial optimization problem, many methods are proposed in this area in the recent past [3]. Wang and Nehrir [4] proposed an analytical method to determine optimal location to place a DG in distribution system for power loss minimization. Celli et al [5] presented a multi-objective algorithm using GA for sitting and sizing of DG in distribution system
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