Planning an Energy–Water–Environment Nexus System in Coal-Dependent Regions under Uncertainties

Abstract

Energy, water, and environment are inextricably interwoven in the complex social and economic networks. This study proposes an optimization model for planning the energy–water–environment nexus system (EWENS) through incorporating the linear autoregressive integrated moving average model prediction model (ARIMA), Monte Carlo simulation, chance-constrained programming (CCP), and type-2 fuzzy programming (T2FP) into one general framework. This method effectively tackles type-2 fuzzy set and stochastic uncertainties. The proposed model can quantitatively explore the interconnections between water, energy, and environment systems and generate an optimized solution for EWENS. The proposed model was applied to a coal-dominated region of China, i.e., Inner Mongolia. Several findings and policy implications were obtained. First, the total water supply for energy-generating activities will range from 1368.10 × 106 m3 to 1370.62 × 106 m3, at the end of planning periods. Second, the electricity for water supply will range from 2164.07 × 106 kWh to 2167.65 × 106 kWh at the end of the planning periods, with a growth rate of 46.06–48.72%. Thirdly, lifecycle carbon dioxide emission (LCDE) is projected to range from 931.85 × 106 tons to 947.00 × 106 tons at the end of the planning periods. Wastewater and SO2, NOx, and particulate matter (PM) emissions are projected to be 42.72 × 103–43.45 × 103 tons, 183.07 × 103–186.23 × 103 tons, 712.38 × 103–724.73 × 103 tons, and 38.14 × 103–38.80 × 103 tons at the end of the planning periods. Fourthly, as the largest electricity-exporting city of China, Inner Mongolia’s electricity outflows will export 1435.78 × 106 m3 of virtual water to other regions, implying that Inner Mongolia is pumping its important water resource to support other regions’ electricity demands. Finally, high carbon mitigation levels can effectively optimize the electricity power mix, reduce consumption amounts of water and coal, and mitigate air pollutants, wastewater, and LCDE. The obtained results provide useful information for managers to develop a sustainability plan for the EWENS.

Analysis of Extreme Random Uncertainty in Energy and Environment Systems for Coal-Dependent City by a Copula-Based Interval Cost–Benefit Stochastic Approach

“…Other methods are also applied, such as Chance-constrained programming (CCP). Chen [21] used CCP to deal with the uncertainty of energy-water-environment systems in a coal-dependent region. Li [22] applied CCP to handle the uncertainties in the optimal siting and sizing of a distributed generation system.…”

Assessment of Power System Sustainability and Compromises between the Development Goals

“…At the third stage (Interpretation), the recommendations for ensuring power system sustainability are developed. Such recommendations can be made using different methods of scenario modeling, namely, fuzzy synthetic evaluation [30,31], Monte Carlo simulation [32,33], multiobjective optimization [34][35][36], or other techniques. Multiobjective optimization is considered to be the most appropriate method to use when making longterm strategic decisions, whereas Monte Carlo simulation is focused on the uncertainties in the development of power systems.…”

An Integrated Comparative Assessment of Coal-Based Carbon Capture and Storage (CCS) Vis-à-Vis Renewable Energies in India’s Low Carbon Electricity Transition Scenarios

“…For instance, Viebahn et al [24,[48][49][50] proposed an integrated assessment methodology to capture the techno-economic and climate mitigation aspects of coal-CCS development pathways in Germany, China, India and South Africa. The "nexus" approach has been developed in recent years to investigate the inter-linkages between the energy technologies and their use of natural resources; for example, an energy-water nexus [51][52][53], energy-climate-water nexus [54,55], energy-food-water nexus [56,57] and energy-land-water nexus [58,59]. However, the nexus perspective has been very limited in its application in the context of coal-CCS [45].…”