Exploring methods to evaluate the carbon impact of network investment deferral

Daniels, Laura; Potter, Ben; Coker, Phil

doi:10.1109/isgteurope.2014.7028931

Cited by 1 publication

(2 citation statements)

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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%

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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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Section: Selecting the Functional Unitmentioning

confidence: 99%