Assessment of marginal emissions factor in power systems under ramp-rate constraints

Zheng, Zhoutao; Han, Fengxia; Li, Furong; Zhu, Jiahui

doi:10.17775/cseejpes.2015.00049

Cited by 34 publications

(14 citation statements)

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“…Beyond distributed data centres, this problem also concerns smart-grid applications that aimed to minimize emissions in real time. Especially, some authors already recommend using real-time marginal emission factors to evaluate and minimize GHG emissions of smart buildings (Roux et al, 2016), electric vehicles (McCarthy & Yang, 2010;Thomas, 2012) and users adapting their power demand (Zheng et al, 2015). Indeed, a low average emission factor at a given time in a region does not guarantee that the marginal sources of electricity will also have low emissions at that time.…”

Section: The Discussion Begins With the Description Of The Problematic Of Real-time Minimization And Assessment Of Emissions Andmentioning

confidence: 99%

Consideration of marginal electricity in real-time minimization of distributed data centre emissions

Dandres

Moghaddam

Nguyen

et al. 2017

Journal of Cleaner Production

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Among the innovative approaches to reduce the greenhouse gas (GHG) emissions of data centres during their use phase, cloud computing systems relying on data centres located in different regions appear promising. Cloud computing technology enables real-time load migration to a data centre in the region where the GHG emissions per kWh are the lowest. In this paper, we propose a novel approach to minimize GHG emissions cloud computing relying on distributed data centres. Unlike previous optimization approaches, our method considers the marginal GHG emissions caused by load migrations inside the electric grid instead of only considering the average emissions of the electric grid's prior load migrations. Results show that load migrations make it possible to minimize marginal GHG emissions of the cloud computing service. Comparison with the usual approach using average emission factors reveals its inability to truly minimize GHG emissions of distributed data centres. There is also a potential conflict between current GHG emissions accounting methods and marginal GHG emissions minimization. This conflict may prevent the minimization of GHG emissions in multi-regional systems such as cloud computing systems and other smart systems such as smart buildings and smart-grids. While techniques to model marginal electricity mixes need to be improved, it has become critical to reconcile the use of marginal and average emissions factors in minimization of and accounting for GHG emissions.

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Section: The Discussion Begins With the Description Of The Problematic Of Real-time Minimization And Assessment Of Emissions Andmentioning

confidence: 99%

Consideration of marginal electricity in real-time minimization of distributed data centre emissions

Dandres

Moghaddam

Nguyen

et al. 2017

Journal of Cleaner Production

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show abstract

“…This work provides a robust and consistent economic and carbon analysis of electricity generation statistics of balancing services used for SoES in the highly decarbonised GB power system. While some studies in the literature [61][62][63][64][65][66] attempted an indirect statistical analysis of grid data to estimate the carbon factor of the marginal power, the original contribution of this work is in elaborating the direct analysis of the marginal markets, focusing on affordability, decarbonisation and SoES. As a byproduct, this work provides a new consistent dataset of CI per fuel, suggesting an improvement to the current global standard methodologies [79][80][81].…”

Section: Discussionmentioning

confidence: 99%

“…The calculation of carbon impact of the marginal electricity generation is not new. Several authors calculate the marginal emission factors (MEF) by statistically analysing the hourly or half-hourly variation in load and fuel mix of the grid as a whole (e.g., [61][62][63][64][65][66]). Whilst the established statistical methods for the calculation of the MEF are an effective indirect proxy, this article directly analyses the data of balancing services.…”

Section: Methodsmentioning

confidence: 99%

Economic and Carbon Costs of Electricity Balancing Services: The Need for Secure Flexible Low-Carbon Generation

et al. 2021

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The electricity sector aims to achieve a balanced progress in all three dimensions of the energy trilemma: affordability, decarbonisation and security of supply. Separate strategies for decarbonisation and security of supply have been pursued; each with close attention to minimising costs, thus consistent with the affordability aspect of the trilemma. However, while it is evident that the pathway for decarbonisation increases pressure on security of supply, the pressures that cost-minimising security of supply measures are putting on decarbonisation goes unaddressed. The United Kingdom (UK) is a global leader in the transition towards a decarbonised economy and aims to achieve net-zero emissions by 2050. As a major part of the UK, Great Britain (GB) has achieved greater than 50% of low-carbon electricity generation and the grid’s carbon intensity has dropped by 36% over the period 2015–2019. However, balancing services that provide security of supply uses only 8% of low-carbon generation. Their carbon intensity is double the grid’s average and this gap is widening. This is an effect of a systemic reliance on carbon-intensive fuels. Financial support for capital investment for flexible low-carbon technologies is much needed. The GB context suggests that an integrated strategy covering all three dimensions of the trilemma might achieve an improved balance between them and unlock an affordable, net-zero emissions and secure power system.

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“…In the first group, the normative economic behavior of power plants in the event of a change in demand is examined. For this purpose, a permanent marginal power plant can be defined in a simple manner, to which the entire change in demand is attributed, or a merit order of the power plants employed can be formed [31]. However, more than just one generation unit, but not all of them as in the case of the AEF, reacts to changes in demand.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Prospective Average and Marginal GHG Emission Factors—Scenario-Based Method for the German Power System until 2050

Seckinger

Radgen

2021

Energies

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Due to the continuous diurnal, seasonal, and annual changes in the German power supply, prospective dynamic emission factors are needed to determine greenhouse gas (GHG) emissions from hybrid and flexible electrification measures. For the calculation of average emission factors (AEF) and marginal emission factors (MEF), detailed electricity market data are required to represent electricity trading, energy storage, and the partial load behavior of the power plant park on a unit-by-unit, hourly basis. Using two normative scenarios up to 2050, different emission factors of electricity supply with regard to the degree of decarbonization of power production were developed in a linear optimization model through different GHG emission caps (Business-As-Usual, BAU: −74%; Climate-Action-Plan, CAP: −95%). The mean hourly German AEF drops to 182 gCO2eq/kWhel (2018: 468 gCO2eq/kWhel) in the BAU scenario by the year 2050 and even to 29 gCO2eq/kWhel in the CAP scenario with 3700 almost emission-free hours from power supply per year. The overall higher MEF decreases to 475 and 368 gCO2eq/kWhel, with a stricter emissions cap initially leading to a higher MEF through more gas-fired power plants providing base load. If the emission intensity of the imported electricity differs substantially and a storage factor is implemented, the AEF is significantly affected. Hence, it is not sufficient to use the share of RES in net electricity generation as an indicator of emission intensity. With these emission factors it is possible to calculate lifetime GHG emissions and determine operating times of sector coupling technologies to mitigate GHG emissions in a future flexible energy system. This is because it is decisive when lower-emission electricity can be used to replace fossil energy sources.

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Assessment of marginal emissions factor in power systems under ramp-rate constraints

Cited by 34 publications

References 0 publications

Consideration of marginal electricity in real-time minimization of distributed data centre emissions

Consideration of marginal electricity in real-time minimization of distributed data centre emissions

Economic and Carbon Costs of Electricity Balancing Services: The Need for Secure Flexible Low-Carbon Generation

Dynamic Prospective Average and Marginal GHG Emission Factors—Scenario-Based Method for the German Power System until 2050

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