Locational marginal emissions: Analysis of pollutant emission reduction through spatial management of load distribution

Wang, Y.; Wang, C.; Miller, Carol J.; McElmurry, Shawn P.; Miller, Stephen; Rogers, Michelle M.

doi:10.1016/j.apenergy.2013.12.052

Cited by 30 publications

(18 citation statements)

References 16 publications

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“…studied a locational marginal emissions methodology to shift the location of loads to reduce emissions, which succeeded in reducing emissions depending on the diversity of generators, spatial flexibility and CO2 pricing 105. Industries distributed evenly throughout the entire U.S. can use an EF for the U.S., but this distribution is atypical and overly applied.…”

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confidence: 99%

Comparative Assessment of Models and Methods To Calculate Grid Electricity Emissions

Ryan

Johnson

Keoleian

2016

Environ. Sci. Technol.

123

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Due to the complexity of power systems, tracking emissions attributable to a specific electrical load is a daunting challenge but essential for many environmental impact studies. Currently, no consensus exists on appropriate methods for quantifying emissions from particular electricity loads. This paper reviews a wide range of the existing methods, detailing their functionality, tractability, and appropriate use. We identified and reviewed 32 methods and models and classified them into two distinct categories: empirical data and relationship models and power system optimization models. To illustrate the impact of method selection, we calculate the CO2 combustion emissions factors associated with electric-vehicle charging using 10 methods at nine charging station locations around the United States. Across the methods, we found an up to 68% difference from the mean CO2 emissions factor for a given charging site among both marginal and average emissions factors and up to a 63% difference from the average across average emissions factors. Our results underscore the importance of method selection and the need for a consensus on approaches appropriate for particular loads and research questions being addressed in order to achieve results that are more consistent across studies and allow for soundly supported policy decisions. The paper addresses this issue by offering a set of recommendations for determining an appropriate model type on the basis of the load characteristics and study objectives.

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confidence: 99%

Comparative Assessment of Models and Methods To Calculate Grid Electricity Emissions

Ryan

Johnson

Keoleian

2016

Environ. Sci. Technol.

123

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“…LECP and LCF are the price of consumed energy due to transmission loss and the corresponding carbon emitted to the atmosphere, respectively. The contributions of unit g to calculate LECP and LCF are presented in (33) and (34), respectively, while the total LECP and LCF of demand i are obtained in (35) and (36).…”

Section: ) Loss Energy Consumption Price (Lecp) and Loss Carbon Footmentioning

confidence: 99%

“…Finding the Lagrange multipliers in a linear system is an easy task; however, in order to find these multipliers in a nonlinear model, an iterative process is used. At each iteration, the demand at a bus is increased by 1 MW and the difference between the optimal solutions before and after that 1 MW increase produces the Lagrange multiplier at that bus [36]. Using the marginal prices at generating bus g, the generator's profit is obtained in (43), [37].…”

Section: Generation Side Profit Analysismentioning

confidence: 99%

Carbon Footprint Management: A Pathway Toward Smart Emission Abatement

Pourakbari‐Kasmaei

Lehtonen

Contreras

et al. 2020

IEEE Trans. Ind. Inf.

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There is an increasing concern about controlling and reducing carbon emissions in power systems. In this regard, researchers have focused on managing emissions on the generation side, which is the main source of emissions. Considering emission limits on the generation side results in an increase in locational marginal prices that negatively affects social welfare. However, carbon emissions are a by-product of electricity generation that is used to satisfy the demands on the consumer side. Consequently, demand side emission control may not be achieved if only generation is taken into account. In order to fill this existing gap, in this paper, a demand-side management approach aiming at carbon footprint control is proposed. First, the carbon footprint is allocated among the consumers using an improved proportional sharing theorem method. Each consumer learns about their real-time carbon footprint, excess carbon footprint, and the incurred surcharge tax. Then, demands are adjusted via a proper adjustment procedure. This provides enough information for consumers where demand management may result in carbon footprint and demand reductions as well as the exemption of incurred taxes. Profit analysis for both generation and demand sides is carried out to show the effectiveness of the proposed framework using two illustrative case studies. The results obtained, compared with existing policies such as carbon cap, cap-and-trade, and carbon tax, prove the fairness and the advantages of the proposed model for both the demand and the generation sides.Index Terms-Carbon footprint allocation, carbon abatement, demand side management, power tracing, tax exemption.

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“…With the idea that supply is generated by demand, researchers have begun to study energy-saving methods from the load side. Reference [10] puts forward the concept of locational marginal emission (LME) and demand-side management method based on LME. A load-source interaction model is proposed in [11] which considers the users' satisfaction and carbon emission.…”

Section: Introductionmentioning

confidence: 99%

A low‐carbon dispatch of power system incorporating active distribution networks based on locational marginal emission

Jiang

Hao

et al. 2017

IEEJ Transactions Elec Engng

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Involvement of active distribution networks (ADNs) in emission management can give full play to the carbon-reduction potential of distributed generations (DGs) and demand response. With the development of smart grid, low-carbon coordinated scheduling of power system with ADNs will become a new trend. A bilevel dispatch model based on locational marginal emission (LME) is proposed to achieve carbon reduction from both generation and load sides. The main grid dispatch is a problem of dynamic optimal power flow aiming at reducing both the operating and emission costs, in which LME under AC condition is adopted to calculate the carbon emission produced by node power. The ADN level is the DG generation schedule with the objective of minimizing both the cost and system emission based on LME. The main grid and ADNs interact and cooperate with each other by locational marginal price (LMP) and LME to cut the carbon pollution. Simulation results in a modified IEEE 30-bus system and an IEEE 118-bus system show that compared with the traditional LMP-based coordinated scheduling, the bilevel dispatch model based on LME can reduce carbon emission effectively and promote ADNs' participation in system carbon emission management.

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Locational marginal emissions: Analysis of pollutant emission reduction through spatial management of load distribution

Cited by 30 publications

References 16 publications

Comparative Assessment of Models and Methods To Calculate Grid Electricity Emissions

Comparative Assessment of Models and Methods To Calculate Grid Electricity Emissions

Carbon Footprint Management: A Pathway Toward Smart Emission Abatement

A low‐carbon dispatch of power system incorporating active distribution networks based on locational marginal emission

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