In this study, an environmentally friendly model of regional power system was developed to minimize the total cost of a regional power system consisting of an independent power grid. SO2 emission is controlled and capacity expansion is scheduled. In the system, the deterministic variables...

This study presents an interval de Novo programming (IDNP) approach for the design of optimal water-resources-management systems under uncertainty. The model is derived by incorporating the existing interval programming and de Novo programming, allowing uncertainties represented as intervals...

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...

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-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...

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...

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...