access icon free Research on size and location of distributed generation with vulnerable node identification in the active distribution network

This study aims to solve for the optimal location and capacity of distributed generation (DG), taking vulnerable node identification into consideration, in active distribution networks (ADN). Vulnerable nodes exist in the distribution network. Considering that the power fluctuations of those vulnerable nodes will have a significant impact on other nodes, the allocations of the DGs should avoid such nodes. Therefore vulnerable node identification and removal from the network can greatly limit the siting range of DGs. In this study, the vulnerable nodes are identified based on the small-world network theory, which is used as the preliminary location of the DG. Then, a genetic algorithm (GA) is proposed to finally address the optimal location and capacity for grid-connected DG. A GA with voltage boundary constraints is utilised to effectively prevent the bus voltage from reaching its boundary. This method improves the calculation efficiency greatly and is therefore suitable for flexible distribution network topology in ADN. According to the change of the distribution network topology, the corresponding optimal location and capacity limit for the DG can be quickly calculated. Some examples validate the algorithm and prove that it has fast convergence.

Inspec keywords: fault diagnosis; distribution networks; genetic algorithms; distributed power generation

Other keywords: convergence; grid-connected DG; ADN; calculation efflciency; flexible distribution network topology; DG; capacity limit; active distribution network; distributed generation; power fluctuations; vulnerable node identification; genetic algorithm; optimal location; small-world network theory; voltage boundary constraints

Subjects: Distributed power generation; Distribution networks; Optimisation techniques

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