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Swarm intelligence based algorithms for reactive power planning with Flexible AC transmission system devices |
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| Affiliation: | 1. School of Economics and Management, North China Electric Power University, 102206 Beijing, China;2. Beijing Key Laboratory of New Energy and Low-Carbon Development (North China Electric Power University), Changping, Beijing 102206, China;3. Electric Engineering Corporation, Southwest Electric Power Design Institute, 610056 Chengdu, China;1. Faculty of Electrical & Electronics Engineering, University Malaysia Pahang (UMP), 26600 Pekan, Pahang, Malaysia;2. Faculty of Computer Systems & Software Engineering, University Malaysia Pahang (UMP), 26300 Gambang, Pahang, Malaysia;1. School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran;2. Department of Electrical Engineering, Lashtenesha-Zibakenar Branch, Islamic Azad University, Lashtenesha, Iran;1. Higher Education Center of Eghlid, Eghlid, Iran;2. Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, Iran;3. School of Energy Systems, Lappeenranta-Lahti University of Technology (LUT), Lappeenranta, Finland;4. School of Technology and Innovations, University of Vaasa, 65200, Vaasa, Finland;5. Faculty of Engineering of University of Porto and INESC TEC, Porto, Portugal |
| Abstract: | In the proposed work, authors have applied swarm intelligence based algorithms for the effective Co-ordination of Flexible AC transmission system (FACTS) devices with other existing Var sources present in the network. IEEE 30 and IEEE 57 bus systems are taken as standard test systems. SPSO (Simple Particle Swarm Optimization) and other two swarm based intelligence approaches like APSO (Adaptive Particle Swarm Optimization) and EPSO (Evolutionary Particle Swarm Optimization) are used for the optimal setting of the Var sources and FACTS devices. The result obtained with the proposed approach is compared with the result found by the conventional RPP (Reactive power planning) approach where shunt capacitors, transformer tap setting arrangements and reactive generations of generators are used as planning variables. It is observed that reactive power planning with FACTS devices yields much better result in terms of reducing active power loss and total operating cost of the system even considering the investment costs of FACTS devices. |
| Keywords: | Swarm intelligence based algorithms Reactive power planning FACTS devices Active power loss Operating cost |
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