An inexact programming approach for urban electric power systems management under random-interval-parameter uncertainty

In electric power management problems, a number of system parameters are subjected to many powerful and unpredictable influences (e.g. economic situation, technologies in energy conservation). This leads to the difficulty in accurately qualifying them through conventional approaches. In this paper, a concept of random-boundary interval (RBI) whose upper and lower bounds are random variables is introduced to account for the high-uncertain components, like electricity demand, in electric power systems. A fuzzy integer programming model with RBI parameters is developed to support effective planning of urban electric power systems (UEPS). A case study is then provided for demonstrating the applicability of the proposed model. The obtained solutions can be used for generating efficient electricity-supply and capacity-expansion schemes under various situations. Compared with the existing methods, the proposed model could tackle the complex parameter uncertainty in electric power systems, and the potential system-failure risks arising from such uncertainty could be quantified by means of violation levels and satisfaction levels.