Environmental efficiency assessment of China’s integrated power system under the assumption of semi-disposability

Xie, Bai-Chen; Long, Lu; Duan, Na

doi:10.1016/j.cie.2022.108023

Cited by 10 publications

(6 citation statements)

References 54 publications

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“…Yiyi Jiang et al [24] used the SBM model to measure the carbon emission efficiency of power system in 30 provinces of China from 2004-2016 panel data. Bai-Chen Xie et al [25] proposed a modified dynamic network slacks-based measure (DNSBM) model based on semi-disposability. Jin Zhu et alTo sum up, the LCA+DEA methodology is widely used in the carbon efficiency measurement of electrical equipment.…”

Section: Carbon Efficiency and Its Research Methodsmentioning

confidence: 99%

The whole life cycle total factor carbon emission efficiency measurement method of power transmission and transformation equipment

Shi¹,

Fu²,

Wang³

et al. 2023

3rd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2023)

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Electricity generation is a major contributor to carbon emissions in the power system. However, the current carbon emission reduction strategies focus mostly on the production and consumption aspects of the power industry, without taking into account the potential for reducing emissions through the use of power transmission and transformation equipment.This paper investigates the carbon emission efficiency of power transmission and transformation equipment by combining Life Cycle Assessment (LCA) and Data Envelopment Analysis (DEA). First, data related to the power transmission and transformation projects are collected, organized, and cleaned to set weights for different stages of the equipment life cycle. Then, a whole life cycle total factor carbon emission efficiency measurement model (e-LCA-SBM model) of power transmission and transformation equipment is constructed to measure the total factor carbon emission efficiency of the equipment. The results show that the whole life cycle carbon efficiency is modest in the equipment with lower whole life cycle fixed capital investment, and vice versa. This study can provide a reference for selecting equipment with higher carbon emission efficiency and reducing carbon emissions.

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Section: Carbon Efficiency and Its Research Methodsmentioning

confidence: 99%

The whole life cycle total factor carbon emission efficiency measurement method of power transmission and transformation equipment

Shi¹,

Fu²,

Wang³

et al. 2023

3rd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2023)

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“…In recent years, with the advancement of the global sustainable development agenda, research on environmental efficiency has received extensive attention from scholars (Huang 2023;Jiang and Xie 2024;Liu et al 2022;Xie et al 2021;Xie et al 2022b). Environmental efficiency refers to the maximization of output or benefits while minimizing negative environmental impacts in situations of limited resources (Nakaishi et al 2021).…”

Section: Literature Reviewmentioning

confidence: 99%

“…For instance, Wei and Zhao (2024) considered the energy and capital inputs in the power generation industry, taking electricity consumption and the completion value of investment projects as input indicators. In addition to selecting energy inputs, Xie et al (2022b) and Xie et al (2018a) included labor and capital inputs as indicators, with capital indicators measured by the total assets of the generation division and the installed capacity of power generation units, respectively. In terms of output indicators, literature often selects industrial value added or power generation as desirable outputs.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Specifically, Wei and Zhao (2024), Mamghaderi et al (2023), Wu et al (2023), Xie et al (2021), andXie et al (2018a, b) use CO2 emissions as the sole undesirable output. On the other hand, Jiang and Xie (2024), Guo et al (2024), Xie et al (2022b), Nakaishi et al (2021), andSun et al (2020) considered not only carbon emissions but also air pollutants such as SO2, NOx and PM 2.5.…”

Section: Literature Reviewmentioning

confidence: 99%

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Evaluation of the environmental efficiency of China's power generation industry considering carbon emissions and air pollution: An improved three-stage SBM-SE-DEA model

Chai,

Li,

Chen

2024

Preprint

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Evaluating and enhancing the environmental efficiency of the power generation industry is an effective approach for addressing the challenges of climate change and environmental pollution. Considering the influence of external environmental factors and stochastic factors, this paper proposes an improved three-stage slack-based measure with superefficiency data envelopment analysis (SBM-SE-DEA) model to evaluate the environmental efficiency of the power generation industry in China’s 30 provincial regions during 2015–2021. The model integrates three-stage DEA model, SBM-DEA model, and SE-DEA model while accounting for undesirable outputs such as carbon emissions and air pollutants. The results show that (1) regions with a high proportion of renewable energy generation demonstrate the best environmental efficiency when considering the environmental constraints from carbon emissions and air pollution. However, the results of the first stage are evidently overestimated due to the influence of external environmental factors. (2) Rational adjustments in the economic development level, power structure, and industrial structure play a positive role in improving environmental efficiency. However, improving resource endowment does not yield the expected results. Additionally, provinces with higher electricity outputs often bear greater pressure from environmental pollution. (3) The environmental efficiency in the third stage exhibited a stable trend driven by internal factors. However, except for the Northeast and Central-South regions, most regions still experienced overestimation of environmental efficiency in the first stage. Thus, optimizing the power generation structure, promoting industrial restructuring, and strengthening interregional cooperation and coordination are imperative.

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“…The energy system is a key area of carbon emissions in a region (Huang et al, 2020). Therefore, it is of great practical significance to study the low-carbon optimization of regional integrated energy systems (Xie et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

A two-stage robust generation expansion planning framework for regional integrated energy systems with carbon growth constraints

et al. 2023

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After proposing the carbon peaking and carbon neutrality target, China further proposed a series of specific carbon emission growth limit sub-targets. How to decarbonize the energy system to ensure the realization of the carbon growth limit sub-targets is a meaningful topic. At present, generation expansion planning of renewable energy in integrated energy systems has been well studied. However, few of the existing studies consider specific carbon emission growth targets. To address this research gap, a two-stage robust generation expansion planning framework for regional integrated energy systems with carbon growth constraints is proposed in this paper, which takes into account multiple uncertainties. In this framework, the objective function is to minimize the total operation cost and wind turbine investment cost. The first stage is the decision-making level of the wind turbine capacity configuration scheme. The second stage is the optimal economic dispatching in the worst-case scenario, which is a bi-level problem of max-min form. Thus, the two-stage robust optimization framework constitutes a problem of min-max-min form, which is pretty hard to solve directly with a commercial solver. Therefore, a nested column-and-constraint generation algorithm is adopted and nested iterations are performed to solve the complex problem. Finally, case studies are carried out on a regional electric-gas integrated energy system. The MATLAB/YALMIP simulation platform with the Gurobi solver is used to verify the effectiveness and superiority of the proposed framework. Compared with other four cases, 5,000 Monte Carlo scheduling tests demonstrate that the proposed framework can ensure the system carbon emission to be controlled within a certain limit even in the worst scenario. Due to the consideration of multiple uncertainties, the proposed framework planning results are both robust and economical for investment. This study can provide theoretical support for the actual regional integrated energy system to achieve a certain carbon growth target.

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Environmental efficiency assessment of China’s integrated power system under the assumption of semi-disposability

Cited by 10 publications

References 54 publications

The whole life cycle total factor carbon emission efficiency measurement method of power transmission and transformation equipment

The whole life cycle total factor carbon emission efficiency measurement method of power transmission and transformation equipment

Evaluation of the environmental efficiency of China's power generation industry considering carbon emissions and air pollution: An improved three-stage SBM-SE-DEA model

A two-stage robust generation expansion planning framework for regional integrated energy systems with carbon growth constraints

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