a decision support system for generation expansion planning in competitive electricity markets

this paper describes an approach to address the generation expansion-planning problem in order to help generation companies to decide whether to invest on new assets. this approach was developed in the scope of the implementation of electricity markets that eliminated the traditional centralized planning and lead to the creation of several generation companies competing for the delivery of power. as a result, this activity is more risky than in the past and so it is important to develop decision support tools to help generation companies to adequately analyse the available investment options in view of the possible behavior of other competitors. the developed model aims at maximizing the expected revenues of a generation company while ensuring the safe operation of the power system and incorporating uncertainties related with price volatility, with the reliability of generation units, with the demand evolution and with investment and operation costs. these uncertainties are modeled by pdf functions and the solution approach is based on genetic algorithms. finally, the paper includes a case study to illustrate the application and interest of the developed approach.