Anticipatory reactive power reserve maximization using differential evolution

This paper presents an algorithm for anticipatory control of load bus voltages. The algorithm optimizes a set of reactive power control variables and maximizes reactive reserve available at generating buses. Voltage dependent reactive power limits have been accounted. The optimal settings of reactive power control variables have been obtained for next interval predicted loading condition. These optimized settings satisfy the operating inequality constraints in predicted load condition as well as in present base case loading conditions. A population based differential evolution strategy has been used for optimization. Results obtained have been compared with those obtained using another population based technique known as PSO.

[1]  Hao Wu,et al.  An OPF based approach for assessing the minimal reactive power support for generators in deregulated power systems , 2008 .

[2]  R. Storn,et al.  Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series) , 2005 .

[3]  J.G. Vlachogiannis,et al.  A Comparative Study on Particle Swarm Optimization for Optimal Steady-State Performance of Power Systems , 2006, IEEE Transactions on Power Systems.

[4]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[5]  E. Vaahedi,et al.  Dynamic security constrained optimal power flow/VAr planning , 2001 .

[6]  Bala Venkatesh,et al.  A new computational method for reactive power market clearing , 2009 .

[7]  Goran Andersson,et al.  Voltage dependent reactive power limits for voltage stability studies , 1995 .

[8]  Kalyanmoy Deb,et al.  Multi-objective optimization using evolutionary algorithms , 2001, Wiley-Interscience series in systems and optimization.

[9]  J. Lampinen A constraint handling approach for the differential evolution algorithm , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[10]  Joong-Rin Shin,et al.  A particle swarm optimization for economic dispatch with nonsmooth cost functions , 2005, IEEE Transactions on Power Systems.

[11]  Josef Tvrdík Adaptation in differential evolution: A numerical comparison , 2009, Appl. Soft Comput..

[12]  K. S. Swarup,et al.  Differential evolutionary algorithm for optimal reactive power dispatch , 2008 .

[13]  A. F. Mistr,et al.  Reactive management a key to survival in the 1990s , 1995 .

[14]  Gareth A. Taylor,et al.  Multi-objective optimal reactive power flow including voltage security and demand profile classification , 2008 .

[15]  Yoshikazu Fukuyama,et al.  A particle swarm optimization for reactive power and voltage control considering voltage security assessment , 2000 .

[16]  D. Kothari,et al.  A technique for load-shedding based on voltage stability consideration , 2005 .

[17]  R. Adapa,et al.  A review of selected optimal power flow literature to 1993. II. Newton, linear programming and interior point methods , 1999 .

[18]  S. C. Choube,et al.  Loadability margin enhancement using co-ordinated aggregation based particle swarm optimization (CAPSO) , 2010 .

[19]  L.C.P. da Silva,et al.  Dynamic VAr sources scheduling for improving voltage stability margin , 2003 .

[20]  Q. H. Wu,et al.  Optimal reactive power dispatch using an adaptive genetic algorithm , 1997 .

[21]  R. K. Ursem Multi-objective Optimization using Evolutionary Algorithms , 2009 .

[22]  Cw W. Yu,et al.  An investigation of reactive power planning based on chance constrained programming , 2007 .

[23]  Chaohua Dai,et al.  Dynamic multi-group self-adaptive differential evolution algorithm for reactive power optimization , 2010 .

[24]  Shang He,et al.  An improved particle swarm optimizer for mechanical design optimization problems , 2004 .

[25]  Yutian Liu,et al.  Multi-objective reactive power and voltage control based on fuzzy optimization strategy and fuzzy adaptive particle swarm , 2008 .

[26]  B. Gao,et al.  Voltage Stability Evaluation Using Modal Analysis , 1992, IEEE Power Engineering Review.