Using proxies to calculate the carbon impact of investment into electricity network assets

Daniels, Laura; Coker, Phil; Gunn, Alice; Potter, Ben

doi:10.1016/j.apenergy.2015.10.111

Cited by 4 publications

(4 citation statements)

References 21 publications

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“…The input sample determines the accuracy of the calculation, and the calculated carbon emissions are within a certain range. A total of 10,000 sets of carbon emission samples are generated and analyzed in the research [13,14]. The simulated results, including the mean value, standard deviation, coefficient of variation, and confidence interval, can be used to characterize the carbon emissions of the 750 kV substation in Xinjiang.…”

Section: Parameter Stochastic Analysismentioning

confidence: 99%

“…Tan et al established optimization models to study the impact of clean energy and carbon emission mechanisms on the inter-regional energy exchange [13]. Daniels et al used investment and asset data for the GB system for 2015-2023 to calculate the carbon impacts on electricity networks [14]. Garcia et al assessed the environmental life cycle impacts of electricity generation and supply in Portugal [15].…”

Section: Introductionmentioning

confidence: 99%

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Carbon Emission Evaluation Method and Comparison Study of Transformer Substations Using Different Data Sources

Liu

Zhang

et al. 2023

Buildings

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The construction of transformer substations in transmission lines is a systematic, technical, and complex project with the need for numerous materials and resources. Under the development of the green economy, the requirements for energy conservation and carbon reduction have improved; hence, an assessment of carbon emissions in transformer substations is urgently needed. A calculation method was proposed in the present study to analyze the carbon emissions of transformer substations with different kinds of data sources, which were collected from several practical projects in the west-to-east power transmission project. In this study, a detailed comparison and discussion regarding the differences in carbon emissions of 750 kV transformer substations caused by hydrology, geology, engineering quantity, and other factors were conducted. The mean value, standard deviation, and 90% confidence interval of carbon emissions were obtained by Monte Carlo simulation through MATLAB. Results show that the total carbon emissions of the selected 750 kV transformer substations are between [56,000, 68,000] t CO2 eq. Construction engineering accounts for more than 50% of carbon emissions, followed by installation engineering and additional services. In terms of input items, electricity distribution buildings contribute more than 39% of total carbon emissions, followed by cable/earthing systems, which account for 14% of total carbon emissions. Gas insulated switchgear (GIS) and air insulated switchgear (AIS) could adopt different types of equipment foundations, and GIS equipment foundations would generate fewer carbon emissions due to the smaller land area and input materials. This study can provide experience and reference for similar projects and further guide the substation carbon emission reduction work.

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Section: Parameter Stochastic Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Carbon Emission Evaluation Method and Comparison Study of Transformer Substations Using Different Data Sources

Liu

Zhang

et al. 2023

Buildings

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“…In order to calculate the embodied CO 2 per financial investment for the DNO regions, data from Table 1b is required. For the current DNO networks, previous work has determined proxies for calculating the embodied CO 2 associated with network investment at DNO level [9,10]. There are several challenges in calculating CO 2 emissions associated with network investment spend relating to the breakdown of the spend.…”

Section: Selecting the Functional Unitmentioning

confidence: 99%

“…[5][6][7], none attempt to quantify this saving. This paper builds on work from an initial LCA of the GB transmission network [8] and previous studies by the authors [9,10] which introduced the concept of proxies to calculate embodied CO 2 of network assets. Now, these proxies are applied and the embodied CO 2 of network assets is placed in the context of its proportion of total grid CO 2 over time, considering changing demand and carbon intensity.…”

Section: Introductionmentioning

confidence: 99%

Embodied carbon dioxide of network assets in a decarbonised electricity grid

2016

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Calculating carbon dioxide (CO 2 ) emissions associated with electricity is a key component in the field of Life Cycle Assessment (LCA), but is often cited as challenging due to the complex nature of electricity systems despite its importance to the outcome. While calculating the operational CO 2 emissions associated with electricity generation is an active research field, the embodied CO 2 emissions, typically referred to as embodied carbon, of network assets has far less representation in the literature. This paper focuses on the CO 2 emissions aspect of LCA to calculate the embodied CO 2 of network assets in relation to the operational grid CO 2 over time. Several functional units are defined: CO 2 per operational year, CO 2 per asset cost, CO 2 per functional unit of electricity (kWh) and the relationship between embodied emissions and operational emissions in an electricity system over time. Hybrid functional units are then applied in order to better attribute the embodied carbon to the network functions. The hybrid functional units involve network asset lifetime and the issue of temporal horizons. Several suitable horizons are suggested and the comparison of results highlight the importance of the timeframe on results. The relationship between temporal horizons and environmental discounting is discussed and recommendations are made on the appropriate level of discounting depending on the temporal horizon and the purpose of the LCA. The paper uses data from the Great Britain electricity system where planned investment in network assets is £12bn at distribution level (Dx) and £16.4bn at transmission level (Tx) over the next eight years. By using GB network data for embodied carbon, demand and asset data, as well as data from the decarbonisation of electricity generation, indicative results are provided into the way in which embodied carbon impacts could change over time, showing that by 2035, the embodied carbon of the transmission network could contribute almost 25% of total emissions associated with electricity. On a regional basis, DNO level network assets could reach anywhere between 40% and 130%. This network data is also used to show that new network investment could account for up to 6.5% of DNO level network embodied carbon when front loaded during the RIIO-ED1 period.

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Ultra-high voltage network induced energy cost and carbon emissions

Wei

et al. 2018

Journal of Cleaner Production

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Using proxies to calculate the carbon impact of investment into electricity network assets

Cited by 4 publications

References 21 publications

Carbon Emission Evaluation Method and Comparison Study of Transformer Substations Using Different Data Sources

Carbon Emission Evaluation Method and Comparison Study of Transformer Substations Using Different Data Sources

Embodied carbon dioxide of network assets in a decarbonised electricity grid

Ultra-high voltage network induced energy cost and carbon emissions

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