Uncertainty attached to municipal power systems has long been crucial considerations for the related planners. Such an uncertainty could be expressed as random-boundary intervals (RBIs). In this study, an integer programming with random-boundary intervals (IPRBI) approach was developed for...

In this study, a dynamic interval-parameter community-scale energy systems planning model (DIP-CEM) was developed for supporting greenhouse-gas emission (GHG) management and sustainable energy development under uncertainty. The developed model could reach insight into the interactive...

In this study, an inexact community-scale energy model (ICS-EM) has been developed for planning renewable energy management (REM) systems under uncertainty. This method is based on an integration of the existing interval linear programming (ILP), chance-constrained programming (CCP) and mixed...

In this study, a large-scale integrated modeling system (IMS) was applied for supporting climate change impact analysis and adaptation planning of the energy management system in the Province of Manitoba, Canada. The system was based on the integration of the fuzzy-interval inference method...

In this study, a large-scale integrated modeling system (IMS) was developed for supporting climate-change impact analysis and adaptation planning under multi-level uncertainties. A number of methodologies were seamlessly incorporated within IMS, including fuzzy-interval inference method (FIIM),...

In this study, an inexact two-stage water management (ITWM) model is developed for planning agricultural irrigation in the Zhangweinan River Basin, China. The ITWM model is derived from the incorporation of interval-parameter programming (IPP) within a two-stage stochastic programming (TSP)...

In this study, an interval-valued minimax regret analysis (IMRA) method is proposed for planning greenhouse gas (GHG) abatement under uncertainty. The IMRA method is a hybrid of interval-parameter programming (IPP) and minimax regret analysis (MMR) techniques. The developed method is applied to...

Non-point source (NPS) pollution from agricultural lands has aroused widespread concerns throughout the world. In this study, an interval fuzzy two-stage stochastic non-point source pollution mitigation (IFTNS) model was developed for agricultural systems management under uncertainty through...

In this study, an IFJMP (interval-parameter full-infinite joint-probabilistic mixed-integer programming) method is developed for supporting EPS (electric power systems) management. The IFJMP-EPS model cannot only deal with uncertainties expressed as joint probabilities, crisp interval values and...

In this study, a multistage inexact stochastic robust model was developed for regional energy system management in Jining City, China. Three scenarios about the electric power structure adjustment, clean power generation, and the emission reduction target are designed. Methods of interval...