Simultaneous Optimization of Network Reconfiguration and DG Installation Using Heuristic Algorithms
Network reconfiguration and distributed generation (DG) installation are important approaches for loss mitigation and system efficiency improvement. To date, these approaches are generally implemented separately. In this work, simultaneous network reconfigurations and DG installation is solved in order to minimize real power loss and improve system efficiency using popular heuristic algorithms such as Artificial Bee Colony (ABC), Differential Evaluation (DE), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). While decision making is carried out for open switches and DG sizing by given algorithms, optimal locations of DGs are decided using loss sensitivity factor in order to reduce searching space. Different cases of network reconfiguration and DG installation are implemented to compare the performances of given heuristic algorithms. Branch current, bus voltages and DG capacity are considered as constraints and 69 bus system is used for simulation. This study demonstrates that simultaneous network reconfiguration and DG installation presents better solutions than any other cases and ABC has proven minimum losses and maximum voltage improvement.
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