Abstract
Most of the power electronic components act as non-linear loads because they draw non- sinusoidal current from the power supply. Due to these non-linear loads, current harmonics are injected in the power network. For normal operation, any power network is equipped with provisions to keep the harmonics level to a minimum value. Whenever a fault occurs in the distribution system, the primary goal is to re-energize the healthy part of the network which got interrupted. It can be done by changing the topology of the network. This method is called as Service Restoration (SR). In this paper, a service restoration strategy is proposed when non-linear loads are present in the radial distribution system. Service restoration problem is formulated as a multi-objective, constrained optimization problem. Three new objectives are included to address the problem of harmonics injection by non-linear loads. Multi-Objective Particle Swarm Optimization (MOPSO) and Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) are used to find the optimal switching sequence for restoration. To test the effectiveness of the proposed methodology, IEEE 33 bus and IEEE 69 bus test systems are taken.
Highlights
Automation in the electric power sector results in better integration of control and monitoring resources
Network is modeled in PSCAD, and Total Harmonic Distortion (THD) values are measured at the bus through which priority customers are connected
Results of the IEEE 69 bus test system suggest that the service restoration plans obtained through and test effective in minimizing all theplans objectives of Results of the Multi-Objective Particle Swarm Optimization (MOPSO)
Summary
Automation in the electric power sector results in better integration of control and monitoring resources. The presence of automation techniques for the electric distribution system will ensure better service quality and improved investment utilization. Network reconfiguration is the automation technique which can be used to re-route power supply for the healthy part of the system with some fault. Whenever a fault occurs in a distribution network, the first step is to isolate the affected portion of the network by changing the status of surrounding switches. One of the main objectives of service restoration is to reduce the number of affected customers after a fault occurs in the system. Service restoration can be formulated as a multi-objective, combinatorial, constrained non-linear optimization problem; for such a case finding a robust solution is difficult
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