A modeling approach for investigating climate change impacts on renewable energy utilization

Abstract

SUMMARY In this study, an integrated community‐scale energy model (ICEM) was developed for supporting renewable energy management (REM) systems planning with the consideration of changing climatic conditions. Through quantitatively reflecting interactive relationships among various renewable energy resources under climate change, not only the impacts of climate change on each individual renewable energy but also the combined effects on power‐generation sector from renewable energy resources could be incorporated within a general modeling framework. Also, discrete probability levels associated with various climate change impacts on the REM system could be generated. Moreover, the ICEM could facilitate capacity–expansion planning for energy‐production facilities within a multi‐period and multi‐option context in order to reduce energy‐shortage risks under a number of climate change scenarios. The generated solutions can be used for examining various decision options that are associated with different probability levels when availabilities of renewable energy resources are affected by the changing climatic conditions. A series of probability levels of hydropower‐, wind‐ and solar‐energy availabilities can be integrated into the optimization process. The developed method has been applied to a case of long‐term REM planning for three communities. The generated solutions can provide desired energy resource/service allocation and capacity–expansion plans with a minimized system cost, a maximized system reliability and a maximized energy security. Tradeoffs between system costs, renewable energy availabilities and energy‐shortage risks can also be tackled with the consideration of climate change, which would have both positive and negative impacts on the system cost, energy supply and greenhouse‐gas emission. Copyright © 2011 John Wiley & Sons, Ltd.

A pseudo-optimal inexact stochastic interval T2 fuzzy sets approach for energy and environmental systems planning under uncertainty: A case study for Xiamen City of China

“…In these works, optimization programming played a significant role by providing desired decision alternatives under such complex energy systems [26,27,28,29,30,31,32,12,13,14,10,33,34,24]. For example, a hybrid inexact chance-constrained missed-integer linear programming method was introduced by Liu et al [19] for nonrenewable energy resources management under uncertainty.…”

“…In past decades, a large number of optimal research works made proposals to deal with such uncertainties and resulted in a compromise between environmental and economic targets [16] required in the planning of energy systems [17,18,19,20,21,22,23,24,25]. In these works, optimization programming played a significant role by providing desired decision alternatives under such complex energy systems [26,27,28,29,30,31,32,12,13,14,10,33,34,24].…”

Process optimization and robustness analysis of municipal solid waste gasification using air‐carbon dioxide mixtures as gasifying agent

“…Fossil fuel–based power sources arising mostly from coal, petroleum, and natural gas have been maintaining their dominance for well over the past 100 years . The ever‐growing energy demands potentiated by the increasing world population growth, alongside with the anticipated future fossil fuel, supplies shortage, and the current climate change paradigm has led to a sustainable energy revolution . Global climate change implications are now a subject of major concern to the general public.…”

Optimal Use of Agricultural Water and Land Resources through Reconfiguring Crop Planting Structure under Socioeconomic and Ecological Objectives

“…In those studies, a wide spectrum of optimization techniques were used, such as linear programming, non-linear programming, dynamic programming, mixed-integer programming, and multi-objective programming. Among these methods, linear programming-based methods have been extensively used due to their high computational efficiency and easy application to large-scale problems [11][12][13][14][15]. The management of agricultural land and water resources is a complex problem with multi-faceted implications on the economy, society and eco-environment.…”