摘要
In this research, a new method is developed to determine the optimal contract load for a hydropower reservoir, which is achieved by incorporating environ- mental flows into the determination process to increase hydropower revenues, while mitigating the negative impacts ofhydropower generation on riverine ecosystems. In this method, the degree of na^ral flow regime alteration is adopted as a constraint of hydropower generation to protect riverine ecosystems, and the maximization of mean annual revenue is set as the optimization objective. The contract load in each month and the associated reservoir operating parameters were simultaneously optimized by a genetic algorithm. The proposed method was applied to China＇s Wangkuai Reservoir to test its effectiveness. The new method offers two advantages over traditional studies. First, it takes into account both the economic benefits and the ecological needs of riverine systems, rather than only the economic benefits, as in previous methods. Second, although many measures have been established to mitigate the negative ecological impacts ofhydropower generation, few have been applied to the hydropower planning stage. Thus, since the contract load is an important planning parameter for hydropower generation, influencing both economic benefits and riverine ecosystem protection, this new method could provide guidelines for the establishment of river protection measures at the hydropower planning stage.
In this research, a new method is developed to determine the optimal contract load for a hydropower reservoir, which is achieved by incorporating environ- mental flows into the determination process to increase hydropower revenues, while mitigating the negative impacts ofhydropower generation on riverine ecosystems. In this method, the degree of na^ral flow regime alteration is adopted as a constraint of hydropower generation to protect riverine ecosystems, and the maximization of mean annual revenue is set as the optimization objective. The contract load in each month and the associated reservoir operating parameters were simultaneously optimized by a genetic algorithm. The proposed method was applied to China＇s Wangkuai Reservoir to test its effectiveness. The new method offers two advantages over traditional studies. First, it takes into account both the economic benefits and the ecological needs of riverine systems, rather than only the economic benefits, as in previous methods. Second, although many measures have been established to mitigate the negative ecological impacts ofhydropower generation, few have been applied to the hydropower planning stage. Thus, since the contract load is an important planning parameter for hydropower generation, influencing both economic benefits and riverine ecosystem protection, this new method could provide guidelines for the establishment of river protection measures at the hydropower planning stage.
