ENERGY PLANT OPERATION AND INSTALLATION PLANNING VIA STOCHASTIC PROGRAMMING

Abstract

An optimization model of energy plants operational planning when installing photovoltaic generation and a storage battery is developed via two-stage stochastic programming. This determines the operational planning while considering the uncertainty of the output of the photovoltaic generation. The uncertainty is represented by a set of discrete scenarios. The decisions indicating the states of the devices are made in the (cid:12)rst stage, and the amounts of the energy (cid:13)ow are determined in the second stage for each scenario. The objective is the minimization of the expected value of the operational cost. Including a nonlinear constraint for a practical operational planning, the model becomes a large-scale nonlinear mixed integer programming problem. In order to obtain an exact solution, we reformulate it as a large-scale mixed integer programming problem by introducing piecewise linear approximation. Computational results show the effectiveness of our stochastic model by comparing it with the conventional deterministic model. We also calculate recovery periods of the investment cost for the photovoltaic generation and the storage battery and make an economical evaluation of installing them in Japan.