Annual cost and loss minimization in a radial distribution network by capacitor allocation using pso
Increasing power demand from passive distribution networks has led to deteriorated voltage profiles and increased line flows. This has increased the annual operations and installation costs due to unavoidable reinforcement equipment. This work proposes the reduction in annual costs by optimal placem...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Published: |
MDPI
2021
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121234281&doi=10.3390%2fapp112411840&partnerID=40&md5=73824569bbb5bdf9e3b22027707c0fa5 http://eprints.utp.edu.my/29614/ |
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| Institution: | Universiti Teknologi Petronas |
| Summary: | Increasing power demand from passive distribution networks has led to deteriorated voltage profiles and increased line flows. This has increased the annual operations and installation costs due to unavoidable reinforcement equipment. This work proposes the reduction in annual costs by optimal placement of capacitors used to alleviate power loss in radial distribution networks (RDNs). The optimization objective function is formulated for the reduction in operation costs by (i) reducing the active and reactive power losses, and (ii) the cost and installation of capacitors, necessary to provide the reactive power support and maintain the voltage profile. Initially, the network buses are ranked according to two loss sensitivity indices (LSIs), i.e., active loss sensitivity with respect to node voltage (LSI1) and reactive power injection (LSI2). The sorted bus list is then fed to the particle swarm optimization (PSO) for solving the objective function. The efficacy of the proposed work is tested on different IEEE standard networks (34 and 85 nodes) for different use cases and load conditions. In use case 1, the values finalized by the algorithm are selected without considering their market availability, whereas in use case 2, market-available capacitor sizes close to the optimal solution are selected. Furthermore, the static and seasonal load profiles are considered. The results are compared with recent methods and have shown significant improvement in terms of annual cost, losses and line flows reduction, and voltage profile. © 2021 by the authors. Licensee MDPI, Basel, Switzerland. |
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