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An optimisation approach addresses the challenge of positioning and sizing distributed generation units within electricity distribution networks. By utilising cat swarm optimisation and parallel cat swarm optimisation algorithms, the method simultaneously targets several key operational goals. These objectives comprise reducing total power losses, lowering overall generation costs, decreasing emissions from generation units, and enhancing voltage stability across the network. The performance of these computational techniques was evaluated using standard IEEE 33-bus and IEEE 69-bus test distribution systems. Benchmark comparisons with existing optimisation methods demonstrate that the proposed algorithms offer an effective means for determining the ideal location and capacity of distributed generation units in distribution networks.
Integrating local power generation into existing electrical networks can lower operating costs, cut down carbon emissions, and enhance grid stability. By employing effective computational optimisation techniques, electricity network planners can determine precisely where to build generation units and what capacity to install, preventing power losses and maintaining reliable voltage delivery across power distribution grids.
The approach is intended for electricity distribution network operators and grid planning engineers seeking computational tools to site and size distributed energy resources. Given that testing was conducted on simulated standard test networks, specifically the IEEE 33-bus and IEEE 69-bus systems, the research represents early-stage algorithm development. Practical adoption would require integration into commercial power system planning software and validation on live utility networks.
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This paper presents a proposed method to allocate the distributed generation (DG) units on distribution networks using cat swarm optimization algorithm. The proposed method finds the optimal placement and sizing of DG units. The objectives of the optimization problem are minimizing: total generation costs, total power losses, total emissions produced by the generation units and improving the voltage stability. The proposed method depends on cat swarm optimization (CSO) algorithm and parallel cat swarm optimization (PCSO) algorithm. The proposed optimization methods are tested on the IEEE 33-bus and IEEE 69-bus distribution systems. The results of these algorithms are compared to other previous methods that are reported in this field. The proposed optimization methods are considered effective and perfective method to find the placement and the sizing of the DG units on distribution systems.
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DOI: 10.1109/mepcon.2016.7837015
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