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...

In this study, an inexact optimization modeling approach (IBEM: inexact Beijing energy model) was developed for supporting energy systems planning and air pollution mitigation under uncertainty. This model was based on the integration of multiple inexact optimization techniques, including...

In this paper a stochastic robust optimization problem of residential micro-grid energy management is presented. Combined cooling, heating and electricity technology (CCHP) is introduced to satisfy various energy demands. Two-stage programming is utilized to find the optimal installed capacity...

Multiple dynamics and uncertainties are involved in regional energy and greenhouse gas management (REGM) system, confronting decision makers during plan/policy makings. In this study, a greenhouse gas (GHG)-mitigation oriented inexact dynamic energy system management model (IFMP-REGM) is...

Energy management systems are highly complicated with greenhouse-gas emission reduction issues and a variety of social, economic, political, environmental and technical factors. To address such complexities, municipal energy systems planning models are desired as they can take account of these...

In this study, an IFTSP (interval-fuzzy two-stage stochastic programming) method is developed for planning carbon dioxide (CO2) emission trading under uncertainty. The developed IFTSP incorporates techniques of interval fuzzy linear programming and two-stage stochastic programming within a...

In this study, an interval fixed-mix stochastic programming (IFSP) model is developed for greenhouse gas (GHG) emissions reduction management under uncertainties. In the IFSP model, methods of interval-parameter programming (IPP) and fixed-mix stochastic programming (FSP) are introduced into an...

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...