2019EnergiesOpen access

The Potential Role of Flexibility During Peak Hours on Greenhouse Gas Emissions: A Life Cycle Assessment of Five Targeted National Electricity Grid Mixes

Íngrid Munné‐Collado, Fabio Maria Aprà, Pol Olivella‐Rosell, Roberto Villafáfila‐Robles

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Abstract

On the path towards the decarbonization of the electricity supply, flexibility and demand response have become key factors to enhance the integration of distributed energy resources, shifting the consumption from peak hours to off-peak hours, optimizing the grid usage and maximizing the share of renewables. Despite the technical viability of flexible services, the reduction of greenhouse gas emissions has not been proven. Traditionally, emissions are calculated on a yearly average timescale, not providing any information about peak hours’ environmental impact. Furthermore, peak-hours’ environmental impacts are not always greater than on the base load, depending on the resources used for those time periods. This paper formulates a general methodology to assess the potential environmental impact of peak-hourly generation profiles, through attributional life cycle assessment. This methodology was applied to five different countries under the INVADE H2020 Project. Evaluation results demonstrate that countries like Spain and Bulgaria could benefit from implementing demand response activities considering environmental aspects, enhancing potential greenhouse gas reductions by up to 21% in peak hours.

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On the path towards the decarbonization of the electricity supply, flexibility and demand response have become key factors to enhance the integration of distributed energy resources, shifting the consumption from peak hours to off-peak hours, optimizing the grid usage and maximizing the share of renewables. Despite the technical viability of flexible services, the reduction of greenhouse gas emissions has not been proven. Traditionally, emissions are calculated on a yearly average timescale, not providing any information about peak hours’ environmental impact. Furthermore, peak-hours’ environmental impacts are not always greater than on the base load, depending on the resources used for those time periods. This paper formulates a general methodology to assess the potential environmental impact of peak-hourly generation profiles, through attributional life cycle assessment. This methodology was applied to five different countries under the INVADE H2020 Project. Evaluation results demonstrate that countries like Spain and Bulgaria could benefit from implementing demand response activities considering environmental aspects, enhancing potential greenhouse gas reductions by up to 21% in peak hours.

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Available abstract

On the path towards the decarbonization of the electricity supply, flexibility and demand response have become key factors to enhance the integration of distributed energy resources, shifting the consumption from peak hours to off-peak hours, optimizing the grid usage and maximizing the share of renewables. Despite the technical viability of flexible services, the reduction of greenhouse gas emissions has not been proven. Traditionally, emissions are calculated on a yearly average timescale, not providing any information about peak hours’ environmental impact. Furthermore, peak-hours’ environmental impacts are not always greater than on the base load, depending on the resources used for those time periods. This paper formulates a general methodology to assess the potential environmental impact of peak-hourly generation profiles, through attributional life cycle assessment. This methodology was applied to five different countries under the INVADE H2020 Project. Evaluation results demonstrate that countries like Spain and Bulgaria could benefit from implementing demand response activities considering environmental aspects, enhancing potential greenhouse gas reductions by up to 21% in peak hours.

Key concepts: Greenhouse gas, Life-cycle assessment, Flexibility (engineering), Environmental economics, Electricity, Renewable energy, Environmental science, Environmental impact assessment

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