Multi objective Flower Pollination Algorithm for solving capacitor placement in radial distribution system using data structure load flow analysis

• Autorzy: Tamilselvan V. , Jayabarathi T.

Identyfikatory

DOI

10.1515/aee-2016-0014

• Języki publikacji: EN

Abstrakty

EN

The radial distribution system is a rugged system, it is also the most commonly used system, which suffers by loss and low voltage at the end bus. This loss can be reduced by the use of a capacitor in the system, which injects reactive current and also improves the voltage magnitude in the buses. The real power loss in the distribution line is the I2R loss which depends on the current and resistance. The connection of the capacitor in the bus reduces the reactive current and losses. The loss reduction is equal to the increase in generation, necessary for the electric power provided by firms. For consumers, the quality of power supply depends on the voltage magnitude level, which is also considered and hence the objective of the problem becomes the multi objective of loss minimization and the minimization of voltage deviation. In this paper, the optimal location and size of the capacitor is found using a new computational intelligent algorithm called Flower Pollination Algorithm (FPA). To calculate the power flow and losses in the system, novel data structure load flow is introduced. In this, each bus is considered as a node with bus associated data. Links between the nodes are distribution lines and their own resistance and reactance. To validate the developed FPA solutions standard test cases, IEEE 33 and IEEE 69 radial distribution systems are considered.

Słowa kluczowe

EN

Flower Pollination Algorithm; data structure; loss minimization; voltage improvement; capacitor placement

• Wydawca: Polish Academy of Sciences, Committee on Electrical Engineering
• Czasopismo: Archives of Electrical Engineering
• Rocznik: 2016
• Tom: Vol. 65, nr 2
• Strony: 203--220
• Opis fizyczny: Bibliogr. 12 poz., fig., tab., wz.

Twórcy

autor

Tamilselvan V.

• School of Electrical Engineering, VIT University, Vellore, Tamilnadu, India

autor

Jayabarathi T.

• School of Electrical Engineering, VIT University, Vellore, Tamilnadu, India

Bibliografia

• [1] Baran E.M., Wu F.F., Optimal capacitor placement on radial distribution systems, IEEE Transactions on Power Delivery 4(1): 725-734 (1989).
• [2] Gallego R.A., Monticelli A.J., Romero R., Optimal capacitor placement in radial distribution networks, IEEE Transactions on Power Systems 16(4): 630-637 (2001).
• [3] Haque, M.H., Capacitor placement in radial distribution systems for loss reduction, IEE Proceedings-Generation, Transmission and Distribution 146(5): 501-505 (1999).
• [4] Baghzouz Y., Ertem S., Shunt capacitor sizing for radial distribution feeders with distorted substation voltages, IEEE Transactions on Power Delivery 5(2): 650-657 (1990).
• [5] Das D., Kothari D.P., Kalam A., Simple and efficient method for load flow solution of radial distribution networks, International Journal of Electrical Power & Energy Systems 17(5): 335-346 (1995).
• [6] Rao R.S., Narasimham S.V.L., Optimal Capacitor Placement in a Radial Distribution System using Plant Growth Simulation Algorithm, World Academy of Science, Engineering and Technology 2:589-596 (2008).
• [7] Rao R.S., Ravindra K., Satish K., Narasimham S. V. L., Power Loss Minimization in Distribution System Using Network Reconfiguration in the Presence of Distributed Generation, IEEE Transactions on Power Systems 28(1):317-325 (2013).
• [8] Sultana S., Roy P.K., Optimal capacitor placement in radial distribution systems using teaching learning based optimization, International Journal of Electrical Power & Energy Systems 54: 387-398 (2014).
• [9] Shuaib Y.M., Kalavathi M.S., Rajan C.C.A., Optimal capacitor placement in radial distribution system using gravitational search algorithm, International Journal of Electrical Power & Energy Systems 64: 384-397(2015).
• [10] Yang X.S., Karamanoglu M., He X.S., Multi-objective flower algorithm for optimization, Procedia Computer Science 18: 861-868 (2013).
• [11] Yang X.S., Flower pollination algorithm for global optimization, Unconventional Computation and Natural Computation, Lecture Notes in Computer Science 7445: 240-249 (2012).
• [12] Yang X.S., Karamanoglu M., He X.S., Flower pollination algorithm: A novel approach for multiobjective optimization, Engineering Optimization 46( 9): 1222-1237 (2014).

Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę