Parallel Self-Adaptive Differential Evolution Algorithm for Solving Short-Term Hydro Scheduling Problem

In order to optimize hydro power plants generator scheduling according to 24-h system demand, a parallel self-adaptive differential evolution algorithm has been applied. The proposed algorithm presents a novel approach to considering the multi-population and utilization of the preselection step for the improvements of the algorithm's global search capabilities. A preselection step with the best, middle, and worst populations' individuals establishes the new trial vectors. This algorithm has been verified on two different models. The first one consists of eight power plants with real parameters, and the second one consists of four power plants, mostly used as a test model in scientific papers. The main goal of the optimization process is to satisfy system demand for 24 h with a decreased usage of water quantity per electrical energy unit. The initial and final states of the reservoirs must also be satisfied.

[1]  K.P. Wong,et al.  Parallel Optimal Reactive Power Flow Based on Cooperative Co-Evolutionary Differential Evolution and Power System Decomposition , 2007, IEEE Transactions on Power Systems.

[2]  D. Petcu,et al.  Parallel implementation of multi-population differential evolution , 2004 .

[3]  P. N. Suganthan,et al.  Differential Evolution Algorithm With Strategy Adaptation for Global Numerical Optimization , 2009, IEEE Transactions on Evolutionary Computation.

[4]  C. Lyra,et al.  Optimal Generation Scheduling of Hydrothermal Power Systems , 1980, IEEE Transactions on Power Apparatus and Systems.

[5]  A. G. Bruce.  Reliability analysis of electric utility SCADA systems , 1997 .

[6]  Enrique Alba,et al.  Parallelism and evolutionary algorithms , 2002, IEEE Trans. Evol. Comput..

[7]  Hong-Chan Chang,et al.  Genetic aided scheduling of hydraulically coupled plants in hydro-thermal coordination , 1996 .

[8]  C. Sagastizábal,et al.  Solving the unit commitment problem of hydropower plants via Lagrangian Relaxation and Sequential Quadratic Programming , 2005 .

[9]  Peter B. Luh,et al.  Scheduling of hydrothermal power systems , 1993 .

[10]  Malcolm Irving,et al.  A genetic algorithm modelling framework and solution technique for short term optimal hydrothermal scheduling , 1998 .

[11]  Gexiang Zhang,et al.  Improved Differential Evolutions Using a Dynamic Differential Factor and Population Diversity , 2009, 2009 International Conference on Artificial Intelligence and Computational Intelligence.

[12]  Jingrui Zhang,et al.  Small Population-Based Particle Swarm Optimization for Short-Term Hydrothermal Scheduling , 2012, IEEE Transactions on Power Systems.

[13]  Xiaohui Yuan,et al.  Optimal self-scheduling of hydro producer in the electricity market , 2010 .

[14]  O. Nilsson,et al.  Mixed-integer programming applied to short-term planning of a hydro-thermal system , 1995 .

[15]  A. M. Jubril,et al.  Solving Multi-Objective Economic Dispatch Problem Via Semidefinite Programming , 2013, IEEE Transactions on Power Systems.

[16]  P. K. Chattopadhyay,et al.  Fast evolutionary programming techniques for short-term hydrothermal scheduling , 2003 .

[17]  Hong-Tzer Yang,et al.  Scheduling short-term hydrothermal generation using evolutionary programming techniques , 1996 .

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

[19]  I. A. Farhat,et al.  Optimization methods applied for solving the short-term hydrothermal coordination problem , 2009 .

[20]  L. Lakshminarasimman,et al.  Short-term scheduling of hydrothermal power system with cascaded reservoirs by using modified differential evolution , 2006 .

[21]  An Liu,et al.  Application of Particle Swarm Optimization to Hydro Generation Scheduling , 2009, 2009 International Conference on Energy and Environment Technology.

[22]  Antonio J. Conejo,et al.  Self-Scheduling of a Hydro Producer in a Pool-Based Electricity Market , 2002, IEEE Power Engineering Review.

[23]  N. Chakraborty,et al.  Differential evolution technique-based short-term economic generation scheduling of hydrothermal systems , 2008 .

[24]  Peter B. Luh,et al.  Hydroelectric generation scheduling with an effective differential dynamic programming algorithm , 1990 .

[25]  Luigi Fortuna,et al.  Chaotic sequences to improve the performance of evolutionary algorithms , 2003, IEEE Trans. Evol. Comput..

[26]  Renjeng Su,et al.  Augmented Lagrangian approach to hydro-thermal scheduling , 1998 .

[27]  Chun-Yin Wu,et al.  Truss structure optimization using adaptive multi-population differential evolution , 2010 .

[28]  Peter B. Luh,et al.  Hydrothermal scheduling via extended differential dynamic programming and mixed coordination , 1995 .

[29]  Janez Brest,et al.  Self-Adapting Control Parameters in Differential Evolution: A Comparative Study on Numerical Benchmark Problems , 2006, IEEE Transactions on Evolutionary Computation.

[30]  C.E. Zoumas,et al.  A genetic algorithm solution approach to the hydrothermal coordination problem , 2004, IEEE Transactions on Power Systems.

[31]  Yanbin Yuan,et al.  An enhanced differential evolution algorithm for daily optimal hydro generation scheduling , 2008, Comput. Math. Appl..

[32]  Kehinde Olukunmi Alawode,et al.  Solving Multi-Objective Economic Dispatch Problem , 2013 .

[33]  Yinghai Li,et al.  Optimal Scheduling of Cascade Hydropower System Using Grouping Differential Evolution Algorithm , 2012, 2012 International Conference on Computer Science and Electronics Engineering.

[34]  Hugh Rudnick,et al.  Short-term hydrothermal generation scheduling model using a genetic algorithm , 2003 .