Dwindling of Real Power Loss by Enriched Big Bang-Big Crunch Algorithm

In this paper, Enriched Big Bang-Big Crunch (EBC) algorithm is proposed to solve the reactive power problem. The problem of converging to local optimum solutions occurred for the Bang-Big Crunch (BB-BC) approach due to greedily looking around the best ever found solutions. The proposed algorithm takes advantages of typical Big Bang-Big Crunch (BB-BC) algorithm and enhances it with the proper balance between exploration and exploitation factors. Proposed EBC algorithm has been tested in standard IEEE 118 & practical 191 bus test systems and simulation results show clearly the improved performance of the proposed algorithm in reducing the real power loss.

[1]  F. Capitanescu,et al.  Assessing Reactive Power Reserves With Respect to Operating Constraints and Voltage Stability , 2011, IEEE Transactions on Power Systems.

[2]  D.C. Yu,et al.  A novel optimal reactive power dispatch method based on an improved hybrid evolutionary programming technique , 2004, IEEE Transactions on Power Systems.

[3]  A. Monticelli,et al.  Security-Constrained Optimal Power Flow with Post-Contingency Corrective Rescheduling , 1987, IEEE Transactions on Power Systems.

[4]  A.C.Z. de Souza,et al.  Comparison of performance indices for detection of proximity to voltage collapse , 1996 .

[5]  Kwang Y. Lee,et al.  Fuel-cost minimisation for both real-and reactive-power dispatches , 1984 .

[6]  Cristian Bovo,et al.  A GA approach to compare ORPF objective functions including Secondary Voltage Regulation , 2012 .

[7]  Eric Hcbson,et al.  Network Constrained Reactive Power Control Using Linear Programming , 1980, IEEE Transactions on Power Apparatus and Systems.

[8]  Ching-Tzong Su,et al.  Optimal setting of reactive compensation devices with an improved voltage stability index for voltage stability enhancement , 2012 .

[9]  Bala Venkatesh,et al.  A new optimal reactive power scheduling method for loss minimization and voltage stability margin maximization using successive multi-objective fuzzy LP technique , 2000 .

[10]  Bo Xing,et al.  Innovative Computational Intelligence: A Rough Guide to 134 Clever Algorithms , 2013 .

[11]  K. Lee,et al.  A United Approach to Optimal Real and Reactive Power Dispatch , 1985, IEEE Transactions on Power Apparatus and Systems.

[12]  H. K. Verma,et al.  TLBO based Voltage Stable Environment Friendly Economic Dispatch Considering Real and Reactive Power Constraints , 2013 .

[13]  Ibrahim Eksin,et al.  A new optimization method: Big Bang-Big Crunch , 2006, Adv. Eng. Softw..

[14]  Songtao Xue,et al.  Big Bang-Big Crunch optimization for parameter estimation in structural systems , 2010 .

[15]  Sakti Prasad Ghoshal,et al.  Optimal VAR control for improvements in voltage profiles and for real power loss minimization using Biogeography Based Optimization , 2012 .

[16]  Juan Yu,et al.  An Unfixed Piecewise-Optimal Reactive Power-Flow Model and its Algorithm for AC-DC Systems , 2008, IEEE Transactions on Power Systems.

[17]  Zechun Hu,et al.  Stochastic optimal reactive power dispatch: Formulation and solution method , 2010 .

[18]  B. Yegnanarayana,et al.  Genetic-algorithm-based optimal power flow for security enhancement , 2005 .

[19]  S. M. Shahidehpour,et al.  Linear reactive power optimization in a large power network using the decomposition approach , 1990 .

[20]  Fang Liu,et al.  A hybrid genetic algorithm-interior point method for optimal reactive power flow , 2006, IEEE Transactions on Power Systems.

[21]  M. Fesanghary,et al.  An improved harmony search algorithm for solving optimization problems , 2007, Appl. Math. Comput..

[22]  R. Eberhart,et al.  Empirical study of particle swarm optimization , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[23]  Amin Kargarian,et al.  Probabilistic reactive power procurement in hybrid electricity markets with uncertain loads , 2012 .

[24]  Kwang Y. Lee,et al.  Optimal Real and Reactive Power Control Using Linear Programming , 1993 .

[25]  Fuli Wang,et al.  An Improved Biogeography-based Optimization Algorithm for Optimal Reactive Power Flow , 2014 .

[26]  A. Rezaee Jordehi,et al.  A chaotic-based big bang–big crunch algorithm for solving global optimisation problems , 2014, Neural Computing and Applications.

[27]  S. R. Paranjothi,et al.  Optimal Power Flow Using Refined Genetic Algorithm , 2002 .

[28]  V. M. Istemihan Genc,et al.  Preventive and corrective control applications in power systems via Big Bang–Big Crunch optimization , 2015 .

[29]  O. Alsac,et al.  Optimal Load Flow with Steady-State Security , 1974 .