Optimal Line Flow in Conventional Power System using Euclidean Affine Flower Pollination Algorithm

SHILAJA C, RAVI K

Abstract


In electric power market, electric power must be offered to the customer with high quality and least cost. In a deregulated power system, this is a difficult task because of several complicated problems. With increase in electricity cost of raw materials and its growing demand, an optimal solution is required for operation and design of an efficient power system. Conventional energy resource like solar system can be opted for generating electric energy using Photovoltaic (PV) cells. To address the power flow problems using PV cells, Optimal Line Flow (OLF) solution is used for solving and obtaining an optimal operating result for all the generators in distributed power systems. We proposed an Euclidean affine flower pollination algorithm (eFPA) to addresses the line flow OLF constraint for minimizing the fuel cost, loss, emission and voltage stability index. A multi-objective function for all the above constraints is used in eFPA to solve the OLF constraint. Results proved that the eFPA optimization for OLF constraint proved to be efficient because of its minimization of cost, loss, emission and voltage stability index. The  analysis is performed on IEEE 30 bus system and IEEE 57 bus system.

Keywords


OLF; FPA; multi objective; Emission;OPF.

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References


Dommel HW, Tinney WF. Optimal Power Flow Solutions. IEEE Trans Power Apparat Syst 1968; 87,10: 1866-1876.

Alsac O, Stott B. Optimal load flow with steady state security. IEEE Trans. Power Apparat. Syst 1974; 93, 3: 745–751.

Venkatesh P, Gnanadass R, Narayana Prasad Padhy. Comparison and Application of Evolutionary Programming Techniques to Combined Economic Emission Dispatch with Line Flow Constraints. IEEE TPS 2003; 18, 2: 688-697.

Abido M. A. Environmental/Economic Power Dispatch Using Multiobjective Evolutionary Algorithms. IEEE TPS 2003; 18, 4: 1529 – 1537.

Niknam T, Narimani M R. Improved particle swarm optimization for multi-objective optimal power flow considering the cost, loss, emission and voltage stability index. IET Gen Trans Distri 2012; 6, 6: 515–527.

Ravi C N, Rajan C C A. Line flow constraint combined economic emission dispatch with valve point loading by differential evolution algorithm. Int rev of Mod & Sim 2013; 6, 1: 114 – 120.

Ming NIU, Can WAN, Zhao XU. A review on applications of heuristic optimization algorithms for optimal power flow in modern power systems. J. Mod. Power Syst. Clean Energy 2014; 2, 4:289–297.

Kumar R A, Premalatha L. Optimal power flow for a deregulated power system using adaptive real coded biogeography-based optimization. Electrical Power and Energy Systems 2015; 73: 393–399.

Yang X S. Flower pollination algorithm for global optimization. Lecture Notes in Computer Science 2012; 7445: 240-249.

Kim JY, Mun KJ, Kim HS, Park JH. Optimal power system operation using parallel processing system and PSO algorithm. Int J Electr Power Energy Syst 2011; 33(8): 1457–61.

Amer Draa. On the performances of the flower pollination algorithm – Qualitative and quantitative analyses. Applied Soft Computing 2015; 34:349–371.

Varadarajan M, Swarup KS. Solving multi-objective optimal power flow using differential evolution. IET Gener Transm Distrib 2008; 2(5): 720–30.

Osman MS, Abo-Sinna MA, Mousa AA. A solution to the optimal power flow using genetic algorithm. Appl Math Comput 2004; 155(2): 391–405.

Xin-She Yang, Flower Pollination Algorithm for Global Optimization, 11th in proc. International Conference UCNC, 2012; pp 240-249.

Hari Mohan Dubey, Manjaree Pandit , B. K. Panigrahi, A Biologically Inspired Modified Flower Pollination Algorithm for Solving Economic Dispatch Problems in Modern Power Systems. Cognitive Computation. 2015; 7(5): pp. 594-608.

Coelho LDS, Bora TC, Mariani VC. Differential evolution based on truncated Lévy-type flights and population diversity measure to solve economic load dispatch problems. Int J Electr Power Energy Syst. 2014; 57: 178–88.

Yang XS, Karamanoglu M, He X. Flower pollination algorithm: a novel approach for multi-objective optimization. Eng Optim. 2013; 46(9): 1222–37.

Yog Raj Sood, Evolutionary programming based optimal power flow and its validation for deregulated power system analysis, Electrical Power and Energy Systems, 2007; 29: pp. 65–75.

H. Wu, C. W. Yu, N. Xu, X.J. Lin, An OPF based approach for assessing the minimal reactive power support for generators in deregulated power systems. Electrical Power and Energy Systems, 2008; 30: pp. 23–30.

Ferrero, S.M. Shahidehpour, Dynamic economic dispatch in deregulated systems, International Journal of Electrical Power & Energy Systems, 1997; 19(7): pp. 433–439.




DOI (PDF): https://doi.org/10.20508/ijrer.v6i1.3074.g6790

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