Regional energy supply planning: Chance constraint programming

Abstract

Regional energy planning under uncertainty is an important concept in energy-economy models which makes the planning outcomes closer to reality and enables the decision maker to select the best decision. Reliability of local energy supply and the possibility of long-term access to resources and emissions reduction is an essential step. In this study, an urban energy demand which is supplied by electricity network is investigated with an optimal combination of alternative energy resources such as solar, wind and natural gas during the next 10 years. The optimal combination of fossil energy as well as renewable energies are determined by goal stochastic programming model. Isfahan province in Iran has been selected as a case study. Empirical results indicate that due to the importance of investment and operation costs, the dominant share of energy supply will belong to natural gas, while the shares of solar and wind energies remain constant in the next decade. In sum, the share of solar and wind energies increases by 8% in 10 years and therefore, it is not necessary to increase electricity supply by the network in order to meet annual increasing demand. CO2 and NOx emissions will decrease significantly.