A queue-based interval-fuzzy programming approach for electric-power systems planning

In this study, a queue-based interval-fuzzy electric-power system (QIF-ESP) model is developed through coupling fuzzy queue (FQ) theory with interval-parameter programming (IPP). QIF-ESP cannot only handle uncertainties that are presented in terms of fuzzy sets and interval numbers, but also reflect the effects of fuzzy queue on energy resources allocation and system cost. The QIF-EPS model is applied to a case study of planning a regional-scale electric-power system, where two FM/FM/1 (fuzzy exponential interarrival time, fuzzy exponential service time, and one server) queues are incorporated within the modeling framework. Interval solutions with fuzzy arrival and service rates have been generated, which result in different energy resources allocation patterns as well as changed waiting costs and system costs. Compared with the conventional optimization methods, the QIF-ESP model can effectively handle queue problems and multiple uncertainties exist in energy-related processes and activities. Moreover, consideration of queuing problem impacts in the optimization model can provide more useful information for decision makers and gain in-depth insights into the effects of queuing problems for electric-power systems under multiple uncertainties.