Short-term power purchases considering uncertain prices

In deregulated systems, utilities have partial knowledge of the price and amount of power available in the market. Other variables such as forecasted load in utility and fuel availability may also be uncertain. In the paper, an optimisation procedure that models uncertainties using fuzzy numbers is presented. The proposed method defines the range of control variables (local generations and imports) for satisifying operational constraints with a total operation cost lower than a predefined goal. Price of imported power, local generation as well as line flows and loads are defined as linguistic variables and represented with fuzzy numbers. The fuzzy optimisation is transformed into a classical (crisp) optimisation problem by considering a degree of acceptance for each constraint. The problem is formulated with a linear objective function and nonlinear constraints. An iterative procedure is used to compute the minimum operation cost. An example system is used to show applications of the proposed method in the decision-making process inherent in uncertain environments.