Two-stage Stochastic Queuing Theory Applied To Regional Electric Power System Planning

Compared with solar energy, wind energy, tidal energy and other renewable energy resources, fossil fuels is widely used in generating electric power because of its more mature technology and more economical. So, effective and reasonable planning of electric power system (EPS) plays an important role in national and regional sustainable development. However, there are always large amount of complexities and uncertainties in electric power systems, throughout the whole process of production, transportation and utilization. These complexities and uncertainties can directly affect the optimization of electric power systems, decision making, electric power systems’ stability and security. Therefore, it is necessary to develop new effective methods to deal with the complexities and uncertainties in the planning of electric power systems.Therefore, the objective of this study is to develop a two-stage stochastic queue programming (TSQP) method is developed for identifying optimal energy resources allocation through coupling stochastic queue (SQ) theory with interval two-stage stochastic programming (ITSP). The developed TSQP can not only address uncertainties for probability distributions and interval numbers, but also reflect the uncertainties in stochastic queue problems. The developed method is then applied to a case study of planning of a regional-scale electric-power system to demonstrate its applicability. Interval solutions with stochastic arrival and service rates have been generated, which result in different energy resources allocation patterns as well as changed waiting costs and system costs. They can be used for generating decision alternatives and thus help managers to gain in-depth insights into the effects of queuing problems for electric-power systems under uncertainty.