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

Abstract

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.

Simulation-based optimization of sustainable national energy systems

“…The integration of energy systems [22,25] into smart energy systems [26] had advantages over separated "sector by sector" modeling. The need for planning in a competitive environment and existing energy markets [27,28] was favorable to the modeling of separated national monopolies. All such advantages are included in the EnergyPLAN model.…”

Multistage generation expansion planning incorporating large scale energy storage systems and environmental pollution

“…GEP has also been studied considering several objective functions such as minimizing planning cost [2,17], maximizing planning profit in deregulated electricity market [18], maximizing reliability [13], minimizing environmental pollution [19], and considering demand-side management programs [20]. As well, GEP has been investigated subject to various constraints such as reliability [3], environmental pollution [21], investment cost [22], and security [23].…”

Coordinated generation and transmission expansion planning in deregulated electricity market considering wind farms

“…In electricity market, the GEP scheme is mainly presented in pool market; where, GEP is divided into two programming levels: master and slave. In master level, the system constraints are checked by ISO and in the slave level; the best solution of each GENCO for maximizing the profit is obtained [17,18]. The other issue that is usually associated with GEP and TEP is uncertainty.…”