Competence-Oriented Decision Model for Optimizing the Operation of a Cascading Hydroelectric Power Reservoir

Abstract

The operation of the four Perak cascading reservoirs namely, Temenggor, Bersia, Kenering and Chenderoh analyzed using the newly developed genetic algorithm model. The reservoirs are located in the state of Perak of Peninsular Malaysia that used for hydroelectric power generation and flood mitigation. The hydroelectric potential of the cascading scheme is 578 MW. However, the actual annual average generation was 228 MW, which is about 39% of the potential. The research aimed to improve the annual average hydroelectric power generation. The result of the fitness value used to select the optimal option from the test of eight model runs options. After repeated runs of the optimal option, the best model parameters are found. Therefore, optimality achieved at population size of 150, crossover probability of 0.75 and generation number of 60. The operation of GA model produced an additional of 12.17 MW per day. The additional power is found with the same total annual volume of release and similar natural inflow pattern. The additional hydroelectric power can worth over 22 million Ringgit Malaysia per year. In addition, it plays a significant role on the growing energy needs of the country.

An Application of Artificial Bee Colony Algorithm for Reservoir Optimization: A Case Study of Chenderoh Dam, Malaysia

“…The setup of food source in the ABC algorithm for the bee as the searching space for optimum releases is mathematically expressed as Equation (1). A set of release options which consisted of 52 values for each month was taken as a food source.…”

“…The algorithm simulates the foraging behaviour of the honey bee in identifying and exploitation the infeasible region of the search area. ABC algorithm was developed by Karaboga (2005) which inspired many researchers to do further improved and 1 Civil and Structural Engineering Department, National University of Malaysia, Malaysia 2 Civil Engineering Department, University of Malaya, Malaysia applied it to various problems. Karaboga andBastuk (2007a, 2007b) allocated ABC algorithm on multidimensional task and compared its performance with the performances of Particle Swarm Optimization (PSO), Particle Swarm Inspired Evolutionary Algorithm (PS-EA) and Genetic Algorithm (GA).…”