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Analyzing The Effect Of Practical Constraints On Optimal Power Flow In The Presence Of Optimal Unified Power Flow Controller
Objectives: In this paper, a multi objective function is formulated by combining Convex Fuel Cost (CFC) and Total Power Losses (TPL). Multi objective problem has been solved with proposed IKGMO to enhance the security of the power system by minimizing TPL with CFC. Methods/Statistical Analysis: Current injections based model of Optimal Unified Power Flow Controller (OUPFC) is developed to solve optimal power flow problem with and without considering the effect of operational and practical constraints, a hybrid algorithm has been developed known as kinetic gas molecules optimization Improved Kinetic Gas Molecules Optimization (IKGMO). Findings: The comprehensive procedure is described to solve optimization problem with OUPFC while satisfying practical constraints and operational with device limits. Standard IEEE-30 bus and IEEE-57 bus test systems were tested with proposed method and verified with supporting numerical and graphical results. Application/Improvements: Convergence characteristics for the objectives minimization which conveys that the solution is converged with in lesser number of iterations using proposed method than existing methods shown in the literature.
Current Based Model, IKGMO, OUPFC, POZ limits, Ramp-rate limits, Spinning Reserve Constraints.
- Mohammadi-Ivatloo B, Rabiee A, Soroudi A. Nonconvex Dynamic Economic Power Dispatch Problems Solution Using Hybrid Immune-Genetic Algorithm. IEEE System Journal. 2013; 7(4):717–85.
- Basu M. Modified particle swarm optimization for nonconvex economic dispatch problems. Electrical Power and Energy Systems. 2015;304–12.
- Duman S, Yorukeren N, Altas H. A novel modified hybrid PSOGSA based on fuzzy logic for non-convex economic dispatch problem with valve-point effect. Electrical Power and Energy Systems. 2015; 64:121–35.
- Zhan J, Guo Q H C, Zhou X. Economic Dispatch With Non-Smooth Objectives—Part I: Local Minimum Analysis.IEEE Transactions On Power systems. 2015; 30(2):710–21.
- Elattar EE. A hybrid genetic algorithm and bacterial foraging approach for dynamic economic dispatch problem.Electrical Power and Energy Systems. 2015; 69:18–26.
- Gandomi A H, Alavi A H. Krill herd: A new bio-inspired optimization algorithm Commun Nonlinear Sci Numer Simulat. 2012;17: 4831–45.
- Mandal B, Roy P K, Mandal S. Economic load dispatch using krill herd algorithm. Electrical Power and Energy Systems. 2014;57:1–10.
- Basu M. Artificial bee colony optimization for multi area economic dispatch. Electrical Power and Energy Systems. 2013; 49:181–7.
- Khorsandhi A, Hosseinian SH, Ghazanfari A. Modified artificial bee colony algorithm based on fuzzy multi objective technique for optimal power flow problem. Electrical Power and Energy Systems. 2013; 95:206–13.
- Tsai MT, Gow HJ, Lin WM. A novel stochastic search method for the solution of economic dispatch problems with non-convex fuel cost functions. Electrical Power and Energy Systems. 2011; 33:1070–6.
- Afzalan E, Joorabian M. Emission, reserve and economic load dispatch problem with non-smooth and non-convex cost functions using epsilon-multi-objective genetic algorithm variable. Electrical Power and Energy Systems. 2013; 52:55–67.
- Pandit M, Srivastava L, Sharma M. Environmental economic dispatch in multi-area power system employing improved differential evolution with fuzzy selection. Applied Soft Computing. 2015; 28:498–510.
- Jin J, Zhou D, Zhou P, Miao Z. Environmental/economic power dispatch with wind power. Renewable Energy. 2014; 71:234–42.
- Reddy BY. Developement of Distributed Power Flow Controller For Improved Performance of Power System Network.Indian Journal of Science and technology. 2015 Sep; 8(23):1–5.
- Fathima K A R, Raghavendrian TA. A Novel Intelligent Unified Controller for the Management of the Unified Power Flow Controller (UPFC) Using a single Back propagation Feed forward Artificial Neural Network. Indian Journal of Science and Technology. 2014 Jan; 7(8):1–15.
- Kumar KS, Rao DN. Simulation of Distributed power Flow Controller for Voltage Sag Compensation. Indian Journal of Science and Technology. 2015 sep; 8(23):1–5.
- Ara A L, Miao Z, Niaki SAN. Modelling of Optimal Unified Power Flow Controller (OUPFC) for optimal steadystate performance of power systems. Energy Conversion and Management. 2011; 52:1325–33.
- Basu M. Multi-objective optimal power flow with FACTS devices. Energy Conversion and Management. 2011; 52:903–10.
- Rajaram RM. Optimal location of FACTS devices using Improved Particle Swarm Optimization. Electrical Power and Energy Systems. 2013; 49:333–8.
- Sarker J, Goswami SK. Solution of multiple UPFC placement problems using Gravitational Search Algorithm.Electrical Power and Energy Systems. 2014; 55:531–41.
- Sayah S, Zehar K. Modified differential evolution algorithm for optimal power flow with non-smooth cost functions.Energy conversion and management. 2008; 49:3036–42.
- Moein S, Logeswaran R. KGMO: A swarm optimization algorithm based on the Kinetic Energy of Gas Molecules.Information Sciences. 2014; 275:127–44.
- Duman S, Guvenc S, Sonmez Y, Yorukeren N. Optimal power flow using gravitational search algorithm. Energy Conversion and Management. 2012; 59:86–95.
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