Possibilistic programming approach for mid-term electric power planning in deregulated markets

The mid-term electric power planning problem under uncertainty for a generation company (GenCo) in a deregulated market having some thermal, hydro and wind power plants is addressed. We propose a novel possibilistic price-based mixed integer linear programming approach to solve the considered problem. Because the uncertainties especially those are related to market could not usually be based upon probabilities, the possibilistic distribution functions are used to simulate some key imprecise/ambiguous parameters: GenCo’s electricity market share; electricity, fuel and emission market prices; possible wind electric power; availability of generating units; available water reservoir for hydro units. To solve the proposed model, we develop an interactive possibilistic solution method based upon two recent solution approaches. Finally, we use a real-world case study to show the ability and appropriateness of our model and report computational results. Notably, the proposed approach can be easily applied for a regulated environment.

► We give possibilistic MILP for mid-term electric power planning in deregulated market.
► We explicitly model the differences in various regions in national electricity grid.
► We use unserved load along with profit to match model with a regulated environment.
► We model explicitly bilateral contract, emission and fuel consumption and storage.
► Take-or-pay fuel contracts and cap-and-trade emission regulation is modeled.