Chance constrained capital investment decision model for electric utilities

The electric utility industry is currently moving toward a competitive market from a traditionally regulated monopoly. Under such circumstances, the economic consequences of capital investment decisions regarding the selection of projects for generation expansion would be highly stochastic due to the fact that the market is no longer controlled by any small number of economic agents. To address this stochastic nature, in this paper, the electricity price is modeled as a random variable. With this random variable price, the capital investment decision process is formulated and solved as a chance constrained programming (CCP) problem. Based on CCP, we maximize the weighted expected total profit minus the weighted standard deviation of the total profit from all projects to be selected in all periods. This optimization is subject to the constraint that the sum of profits from all projects in a period will meet a minimum profit requirement with a pre-determined probability bound. The optimal set of projects is then obtained via mathematical optimization. A numerical example is provided to illustrate the main features of our model.