Risk-based parameter selection for short-term reservoir operation

Abstract

A methodology has been developed to determine the optimal operating horizon for short-term reservoir operation. The modelling procedure includes: (1) an adaptive forecasting algorithm; (2) a real-time reservoir operation model; (3) a multiobjective compromise programming algorithm. The compromise programming algorithm utilizes a multiobjective compromise between the conflicting objectives of hydrologic forecast reliability and reservoir operation penalties. The algorithm requires predetermined weights defining the relative importance of the two objectives. This paper presents a risk-based methodology developed to help a decision maker in selecting the appropriate weights. Reliability, vulnerability, and resiliency are used as three risk-based criteria for assisting in selection of the weights. The methodology is presented in the form of a rule-based system designed to aid the user in the selection process. The methodology is illustrated through an application of the technique to the operation of Green Reservoir in Kentucky. The reservoir model is implemented for four different historical periods and its performance in terms of total penalties, reliability, vulnerability, and resiliency is presented as a function of the multi-objective weighting parameters. The rule-based expert system is then used for deriving recommendations regarding the selection of appropriate weights. The paper also discusses the rule-based expert system development tool, used in this research.