Real-time Cascading Reservoirs Operation using the Genetic Algorithm and Seasonally Varied Models - DERIB ASFAW, TILAHUN (2012)
The Perak cascading scheme located in the state of Perak, Malaysia, consists of four reservoirs, namely, Temenggor, Bersia, Kenering and Chenderoh. The reservoirs are used for hydroelectric power generation and flood control. The hydroelectric power potential of the cascading scheme is 578 MW, while the annual long-term historical average (HA) hydroelectric power generation was around 228 MW. It was about 39.46% of the potential capacity. Accordingly, the study aimed to improve the hydroelectric power generation of the scheme. The genetic algorithm and the seasonally varied models have been developed to maximize the annual hydroelectric power generation of the Perak cascading reservoir. The fitness function of the genetic algorithm model (GAM) was to minimize the difference between the potential capacity and actual generation of the scheme. GAM was established with a total of 208 and I 04 equality and inequality constraints, respectively. The optimal release decisions were found after checking the optimality of the population size (PS), the crossover probability (CRP) and the generation number (GN). Whereas, a seasonally varied model (SVM) has been developed after the analysis of the long-term HA operation data. Consequently, from the annual variation of the headrace level of Temenggor, the most upstream reservoir in the cascading scheme, four seasons are identified. The seasons are the refill, upper level, deplete and lower level that occurs in sequentially and repeatedly per year. The two seasons that require a ranking order to maximize the energy-storage and to minimize the spill of water in the scheme are the refill and deplete. Hence, the refill rank order performed according to the decrease order of the change of power production in the change of storage volume, while the order of depletion has been conducted with the increase order of the storage effectiveness ratio.