A risk-based optimal self-scheduling of cascaded hydro power plants in joint energy and reserve electricity markets

In this paper, the authors propose a new method for optimal self-scheduling of cascaded hydro power plants in energy and reserve electricity markets. In the proposed methodology, risk-based self-scheduling is applied with regard to volume of reservoirs impresses on both energy price and probability of presence in spinning reserve electricity market, whiles energy price influences on only probability of presence in spinning reserve market. In order to model optimal self-scheduling of cascaded hydro power plants in the energy and reserve electricity markets, daily operation in hourly interval is taken into account. The proposed method is one of Mixed-Integer, Non-Linear Programming (MINLP) problem with non-convex nature. Since, to solve the proposed MINLP problem, GAMS platform has been utilized. The newly developed method has been applied to a cascaded system with three hydro power plants over a time horizon of 24-hours. The obtained results demonstrate the feasibility and profitableness of the newly developed method in the optimal self-scheduling of cascaded hydro power plants in electricity markets, when compared with other methods.