A chance-constrained programming based approach to optimal hydro energy allocation

For the purpose of bringing into play its role as a peak load regulator, an on-grid electricity price shaver, and a reserve in a hydrothermal system, hydro energy available in each period is divided into two parts: the part to regulate peak loads and the other to serve as a system reserve, to cover insufficient energy supply due to the forced outage of thermal units. A recursive formula for the outage capacity models of thermal units is developed, and the expected energy loss is calculated with the probabilistic method. With the framework of chance-constrained programming, a mathematical model is proposed for determining the critical load point in hydro energy distribution optimization, On the basis of solution of the model with the Monte Carlo simulation algorithm, detailed illustration is given to the proposed model and the algorithm, with the IEEE reliability test system used as an example.