Q. Tan

TL;DR: In this paper, a fuzzy-random interval programming (FRIP) model is proposed to identify optimal strategies in the planning of energy management systems under multiple uncertainties through the development of a FRIP model, which is based on an integration of the existing interval linear programming, superiority-inferiority-based fuzzy-stochastic programming (SI-FSP) and mixed integer linear programming (MILP).

TL;DR: In this article, an inexact community-scale energy model (ICS-EM) is developed for planning renewable energy management (REM) systems under uncertainty, which allows uncertainties presented as both probability distributions and interval values to be incorporated within a general optimization framework.

TL;DR: The UREM-IDSS can be used by decision makers as an effective technique in examining and visualizing impacts of energy and environmental policies, regional/community development strategies, emission reduction measures, and climate change within an integrated and dynamic framework.

TL;DR: In this article, an interval-parameter superiority-inferiority-based two-stage programming model has been developed for supporting community-scale renewable energy management (ISITSP-CREM).

TL;DR: Comparisons on the solutions obtained from ICCP (Interval chance-constraints programming) and DIFSP demonstrated the higher application of this developed approach for supporting the water and farmland use system planning.