Planning of community-scale renewable energy management systems in a mixed stochastic and fuzzy environment

In this study, an interval-parameter superiority–inferiority-based two-stage programming model has been developed for supporting community-scale renewable energy management (ISITSP-CREM). This method is based on an integration of the existing interval linear programming (ILP), two-stage programming (TSP) and superiority–inferiority-based fuzzy-stochastic programming (SI-FSP). It allows uncertainties presented as both probability/possibilistic distributions and interval values to be incorporated within a general optimization framework, facilitating the reflection of multiple uncertainties and complexities during the process of renewable energy management systems planning. ISITSP-CREM can also be used for effectively addressing dynamic interrelationships between renewable energy availabilities, economic penalties and electricity-generation deficiencies within a community scale. Thus, complexities in renewable energy management systems can be systematically reflected, highly enhancing applicability of the modeling process. The developed method has then been applied to a case of long-term renewable energy management planning for three communities. Useful solutions for the planning of renewable energy management systems have been generated. Interval solutions associated with different energy availabilities and economic penalties have been obtained. They can be used for generating decision alternatives and thus help decision makers identify desired policies under various economic and system-reliability constraints. The generated solutions can also provide desired energy resource/service allocation plans with a minimized system cost (or economic penalties), a maximized system reliability level and a maximized energy security. Tradeoffs between system costs and energy security can also be tackled. Higher costs will increase potential energy generation amount, while a desire for lower system costs will run into a risk of energy deficiency. They are helpful for supporting: (a) adjustment or justification of allocation patterns of renewable energy resources and services, (b) formulation of local policies regarding energy utilization, economic development and energy structure under various energy availabilities and policy interventions, and (c) analysis of interactions among economic cost, system reliability and energy-supply shortage.