In this study, an interval-parameter minimax regret programming (IMRP) method is developed for supporting the power management systems planning under uncertainty. This method incorporates techniques of interval linear programming (ILP) and minimax regret programming (MRP) within a general...

In this research, a simulation-based fuzzy possibilistic programming (SFPP) model was advanced through integrating California puff (CALPUFF), fuzzy sets theory and inexact optimization within a general framework. It has advantages in uncertainty reflection, pollutant dispersion modeling, and the...

Management of energy resources is crucial for many regions throughout the world. Many economic, environmental and political factors are having significant effects on energy management practices, leading to a variety of uncertainties in relevant decision making. The objective of this research is...

In this study, an inexact mixed-integer fractional energy system planning (IMIF-EP) model is developed for supporting sustainable energy system management under uncertainty. Based on a hybrid of interval-parameter programming (IPP), fractional programming (FP) and mixed integer linear...

Greenhouse gas (GHG) concentrations are expected to continue to rise due to the ever-increasing use of fossil fuels and ever-boosting demand for energy. This leads to inevitable conflict between satisfying increasing energy demand and reducing GHG emissions. In this study, an integrated...

In this study, a two-stage inexact-stochastic programming (TISP) method is developed for planning carbon dioxide (CO2) emission trading under uncertainty. The developed TISP incorporates techniques of interval-parameter programming (IPP) and two-stage stochastic programming (TSP) within a...

In this study, an inexact fuzzy-stochastic energy model (IFS-EM) is developed for planning energy and environmental systems (EES) management under multiple uncertainties. In the IFS-EM, methods of interval parameter fuzzy linear programming (IFLP) and multistage stochastic programming with...

In this study, an interval full-infinite mixed-integer municipal-scale energy model (IFMI-MEM) is developed for planning energy systems of Beijing. IFMI-MEM is based on an integration of existing interval-parameter programming (IPP), mixed-integer linear programming (MILP) and full-infinite...

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 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...