In this study, an interval-robust nonlinear optimization (IRNO) method is developed for planning energy system and managing CO2 emissions with trading scheme, through incorporating interval-parameter programming (IPP) within a robust optimization (RO) framework. In the modeling formulation, two...

In this study, a hybrid fuzzy-stochastic programming method is developed for planning water trading under uncertainties of randomness and fuzziness. The method can deal with recourse water allocation problems generated by randomness in water availability and, at the same time, tackle...

In recent years, the issue of water allocation among competing users has been of great concern for many countries due to increasing water demand from population growth and economic development. In water management systems, the inherent uncertainties and their potential interactions pose a...

In this study, a full-infinite interval-stochastic mixed-integer programming (FIMP) method is developed for planning carbon emission trading (CET) under dual uncertainties. FIMP has advantages in uncertainty reflection and policy analysis, particularly when the input parameters are provided as...

An interval-parameter chanced-constrained full-infinite mixed-integer programming (ICFMP) approach is proposed for planning energy systems under functional interval uncertainties. ICFMP cannot only deal with crisp intervals, functional intervals, and probability distributions, but also support...

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...

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...