Optimization of hydro energy storage plants by using differential evolution algorithm

The optimal dispatching of cascade Hydro Power Plants is known as a complex optimization problem. In order to solve this problem the authors have applied an adapted differential evolution algorithm by using a fixed and dynamic population size. According to the dynamic population size, the proposed algorithm uses novel random and minimum to maximum sort strategy in order to create new populations with decreased or increased sizes. This implementation enables global search with fast convergence. It also uses a multi-core processor, where all the necessary optimization data are sent to the individual core of a central processing unit. The main aim of the optimization process is to satisfy 24 h demand by minimizing the water quantity used per electrical energy produced. This optimization process also satisfies the desired reservoir levels at the end of the day. The models used in this paper were the real parameters' models of eight cascade Hydro Power Plants located in Slovenia (Europe). Also the standard model from the literature is used in order to compare the performance of the adapted optimization algorithm.

[1]  Ying Wang,et al.  Multi-objective differential evolution with adaptive Cauchy mutation for short-term multi-objective optimal hydro-thermal scheduling , 2010 .

[2]  Li Mo,et al.  Short-term hydrothermal generation scheduling using differential real-coded quantum-inspired evolutionary algorithm , 2012 .

[3]  Sajad Jafari,et al.  Pumped-storage unit commitment with considerations for energy demand, economics, and environmental constraints , 2010 .

[4]  João Peças Lopes,et al.  Characterisation of electrical energy storage technologies , 2013 .

[5]  Xiaohui Yuan,et al.  Application of enhanced PSO approach to optimal scheduling of hydro system , 2008 .

[6]  Joao P. S. Catalao,et al.  HYDRO GENERATION SCHEDULING AND OFFERING STRATEGIES CONSIDERING PRICE UNCERTAINTY AND RISK MANAGEMENT , 2011 .

[7]  Henrik Lund,et al.  Renewable energy strategies for sustainable development , 2007 .

[8]  Cihan Gokcol,et al.  Optimal wind-hydro solution for the Marmara region of Turkey to meet electricity demand , 2011 .

[9]  Abdul-Ghani Olabi,et al.  State of the art on renewable and sustainable energy , 2013 .

[10]  D. P. Kothari,et al.  Multiobjective fixed head hydrothermal scheduling using integrated predator-prey optimization and Powell search method , 2012 .

[11]  C. Christober Asir Rajan.  Hydro-thermal unit commitment problem using simulated annealing embedded evolutionary programming approach , 2011 .

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

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

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

[15]  Abdul-Ghani Olabi.  Developments in sustainable energy and environmental protection , 2012 .

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

[17]  K. K. Mandal,et al.  Parameter study of differential evolution based optimal scheduling of hydrothermal systems , 2013 .

[18]  Joao P. S. Catalao,et al.  Optimal hydro scheduling and offering strategies considering price uncertainty and risk management , 2012 .

[19]  Huifeng Zhang,et al.  Daily hydrothermal scheduling with economic emission using simulated annealing technique based multi-objective cultural differential evolution approach , 2013 .

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

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

[22]  Suzannah Yin Wa Wong,et al.  Hybrid simulated annealing/genetic algorithm approach to short-term hydro-thermal scheduling with multiple thermal plants , 2001 .

[23]  Zita Vale,et al.  Distributed energy resource short-term scheduling using Signaled Particle Swarm Optimization , 2012 .

[24]  Vahid Vahidinasab,et al.  Joint economic and emission dispatch in energy markets: A multiobjective mathematical programming approach , 2010 .

[25]  Poul Alberg Østergaard,et al.  Reviewing optimisation criteria for energy systems analyses of renewable energy integration , 2009 .

[26]  Zbigniew Michalewicz,et al.  Evolutionary Algorithms for Constrained Parameter Optimization Problems , 1996, Evolutionary Computation.

[27]  G. Sheblé,et al.  Power generation operation and control — 2nd edition , 1996 .

[28]  Abdul-Ghani Olabi,et al.  The 3rd international conference on sustainable energy and environmental protection SEEP 2009-Guest Editor's Introduction , 2010 .

[29]  Janez Brest,et al.  Population size reduction for the differential evolution algorithm , 2008, Applied Intelligence.

[30]  Mitra Basu,et al.  Artificial immune system for fixed head hydrothermal power system , 2011 .

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

[32]  Sohrab Khanmohammadi,et al.  A new three-stage method for solving unit commitment problem , 2010 .

[33]  Ying-Yi Hong,et al.  Interactive multi-objective active power scheduling considering uncertain renewable energies using adaptive chaos clonal evolutionary programming , 2013 .

[34]  Allen J. Wood,et al.  Power Generation, Operation, and Control , 1984 .

[35]  J.P.S. Catalão,et al.  Hydro energy systems management in Portugal: Profit-based evaluation of a mixed-integer nonlinear ap , 2011 .

[36]  Xiaohui Yuan,et al.  Short-term hydro-thermal scheduling using particle swarm optimization method , 2007 .

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

[38]  Secundino Soares,et al.  A nonlinear model for the long-term hydro-thermal generation scheduling problem over multiple areas with transmission constraints , 2009, 2009 IEEE/PES Power Systems Conference and Exposition.

[39]  Abdul-Ghani Olabi,et al.  Wind/hydrogen hybrid systems: opportunity for Ireland’s wind resource to provide consistent sustainable energy supply , 2010 .

[40]  Ying Wang,et al.  An adaptive chaotic differential evolution for the short-term hydrothermal generation scheduling problem , 2010 .