An adaptive chaotic artificial bee colony algorithm for short-term hydrothermal generation scheduling

Abstract Short-term hydrothermal scheduling (SHS) is a complicated nonlinear optimization problem with a set of constraints, which plays an important role in power system operations. In this paper, we propose to use an adaptive chaotic artificial bee colony (ACABC) algorithm to solve the SHS problem. In the proposed method, chaotic search is applied to help the artificial bee colony (ABC) algorithm to escape from a local optimum effectively. Furthermore, an adaptive coordinating mechanism of modification rate in employed bee phase is introduced to increase the ability of the algorithm to avoid premature convergence. Moreover, a new constraint handling method is combined with the ABC algorithm in order to solve the equality coupling constraints. We used a hydrothermal test system to demonstrate the effectiveness of the proposed method. The numerical results obtained by ACABC are compared with those obtained by the adaptive ABC algorithm (AABC), the chaotic ABC algorithm (CABC) and other methods mentioned in literature. The simulation results indicate that the proposed method outperforms those established optimization algorithms.

[1]  Sato Yasuo,et al.  Daily integrated generation scheduling for thermal, pumped-storage, and cascaded hydro units and purchasing power considering network constraints , 2011 .

[2]  Hadi Hamedi,et al.  Solving the combined economic load and emission dispatch problems using new heuristic algorithm , 2013 .

[3]  Mahmood Javan,et al.  Optimization Model for Allocating Water in a River Basin during a Drought , 2007 .

[4]  Dervis Karaboga,et al.  A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm , 2007, J. Glob. Optim..

[5]  Marko Cepin,et al.  A multi-objective optimization based solution for the combined economic-environmental power dispatch problem , 2013, Eng. Appl. Artif. Intell..

[6]  Nien-Sheng Hsu,et al.  Optimization of Reservoir Management and Operation with Hedging Rules , 2003 .

[7]  K. Deb.  An Efficient Constraint Handling Method for Genetic Algorithms , 2000 .

[8]  Malabika Basu,et al.  Goal-Attainment Method Based on Simulated Annealing Technique for Economic-Environmental-Dispatch of Hydrothermal Power Systems with Cascaded Reservoirs , 2004 .

[9]  L. Lakshminarasimman,et al.  A modified hybrid differential evolution for short-term scheduling of hydrothermal power systems with cascaded reservoirs , 2008 .

[10]  R. Jha,et al.  Optimal multi-reservoir network control by augmented Lagrange programming neural network , 2007, Appl. Soft Comput..

[11]  Dervis Karaboga,et al.  AN IDEA BASED ON HONEY BEE SWARM FOR NUMERICAL OPTIMIZATION , 2005 .

[12]  Rahmat-Allah Hooshmand,et al.  A hybrid intelligent algorithm based short-term load forecasting approach , 2013 .

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

[14]  Chao-Lung Chiang,et al.  Optimal economic emission dispatch of hydrothermal power systems , 2007 .

[15]  Quentin Goor,et al.  Optimal Multipurpose-Multireservoir Operation Model with Variable Productivity of Hydropower Plants , 2011 .

[16]  Dervis Karaboga,et al.  A modified Artificial Bee Colony (ABC) algorithm for constrained optimization problems , 2011, Appl. Soft Comput..

[17]  Hui Qin,et al.  Comparison of different chaotic maps in particle swarm optimization algorithm for long-term cascaded hydroelectric system scheduling , 2009 .

[18]  E. Lorenz.  Deterministic nonperiodic flow , 1963 .

[19]  Shyh-Jier Huang,et al.  Application of artificial bee colony-based optimization for fault section estimation in power systems , 2013 .

[20]  Amita Mahor,et al.  Short term generation scheduling of cascaded hydro electric system using novel self adaptive inertia weight PSO , 2012 .

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

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

[23]  Jianzhong Zhou,et al.  An adaptive artificial bee colony algorithm for long-term economic dispatch in cascaded hydropower systems , 2012 .

[24]  A. K. Al-Othman,et al.  A hybrid real coded genetic algorithm – Pattern search approach for selective harmonic elimination of PWM AC/AC voltage controller , 2013 .

[25]  Miguel A. Mariño,et al.  Multi-Colony Ant Algorithm for Continuous Multi-Reservoir Operation Optimization Problem , 2007 .

[26]  Veena Sharma,et al.  Optimal multi-reservoir network control by two-phase neural network , 2004 .

[27]  Ying Wang,et al.  Chaotic differential evolution methods for dynamic economic dispatch with valve-point effects , 2011, Eng. Appl. Artif. Intell..

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

[29]  John W. Labadie,et al.  Optimal Operation of Multireservoir Systems: State-of-the-Art Review , 2004 .

[30]  Robert M. May,et al.  Simple mathematical models with very complicated dynamics , 1976, Nature.

[31]  Niladri Chakraborty,et al.  Short-term combined economic emission scheduling of hydrothermal systems with cascaded reservoirs using particle swarm optimization technique , 2011, Appl. Soft Comput..

[32]  Xiaohong Guan,et al.  Scheduling hydrothermal power systems with cascaded and head-dependent reservoirs , 1999 .

[33]  D. Kumar,et al.  Folded Dynamic Programming for Optimal Operation of Multireservoir System , 2003 .