Real-time flood control operations of a cascade reservoir system under emergency conditions can reduce the social and economic loss caused by natural disasters. This paper proposes a risk-based model for real-time flood control operation of reservoirs under emergency conditions and uncertainties. The proposed model consists of three modules: emergency scenarios establishing, Monte Carlo simulations, and risk analysis. The emergency scenarios considered are earthquakes, extreme floods and failure of the spillways of a reservoir. The uncertainty factor considered is the forecast error of reservoir inflows, arising from model structural uncertainty and parameter estimating. The Monte Carlo simulations conduct the real-time flood control operation of reservoirs considering the proposed emergency events and uncertainties. The module of risk analysis performs the assessment of the operation schedules and calculates the risk of dam overtopping, based on the results from Monte Carlo simulations. The proposed model is applied to a cascade reservoir system in the upper reaches of Daduhe river basin in China. The results show that the maximum initial water level of the Shuangjiangkou reservoir is 2447 m a.s.l. (meters above sea level) using the release capacity model and is 2444.5 m a.s.l. using the command model under the scenario of upstream dam break. The integrated risk of the reservoir increases with the initial water level and the uncertainty degree of the reservoir inflows. The decision-makers can choose the operation models according to the actual initial water level of the reservoir under different emergency scenarios.

Utilizing floodwater resources is important in relieving water shortages, and dynamic control of the flood limited water level (FLWL) for reservoir operation in a flood season is an effective method to achieve this objective. Based on the capacity-constrained pre-release method, this study proposed an improved dynamic control method that considered the duration of dry periods and the lead time of flood forecasts. The pre-release process was divided into two periods: water use and flood control. Taking Xianghongdian Reservoir in the Huai River Basin of China as an example, this study analyzed the statistical laws of continuous dry periods and effective flood forecast lead times and compared the effects of the negative exponential and asymptotic regression models in fitting the dry period distribution. We also calculated the floodwater volume over the FLWL in different situations and evaluated the flood control risks in a worst-case scenario. Statistical law of the dry period duration showed obvious negative index distribution characteristics; the relationship between increased water storage, dry period, and lead time can provide support for the operation decisions of the reservoir. The method did not increase the flood control risk under worst-case scenarios, and it can be used to effectively utilize reservoir floodwater resources.

Seeking the optimal strategy of a multi-reservoir system is an important approach to develop hydropower energy, in which the Genetic Algorithm (GA) is commonly used as an effective tool. However, when the traditional GA is applied in solving the problem, the constraints of water balance equation, hydraulic continuity relationship and power system load demand might be violated by the crossover and mutation operator, which decreases the efficiency of the algorithm in searching for a feasible region or even leads to a convergence on an infeasible chromosome within the expected generations. A modified GA taking stochastic operators within the feasible region of variables is proposed. When determining the feasible region of constraints, the progressive optimal approach is applied to transform constraints imposed on reservoirs into a singular-reservoir constraint, and a joint solution with consideration of adjacent periods at crossover or mutation points is used to turn the singular-reservoir constraints into singular variable constraints. Some statistic indexes are suggested to evaluate the performances of the algorithms. The experimental results show that compared to GA adopting a penalty function or pair-wise comparison in constraint handling, the proposed modified GA improves the refinement of the quality of a solution in a more efficient and robust way.