Utilizing Device-level Demand Forecasting for Flexibility Markets

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

3 Citationer (Scopus)

Resumé

The uncertainty in the power supply due to fluctuating Renewable Energy Sources (RES) has severe (financial and other) implications for energy market players. In this paper, we present a device-level Demand Response (DR) scheme that captures the atomic (all available) flexibilities in energy demand and provides the largest possible solution space to generate demand/supply schedules that minimize market imbalances. We evaluate the effectiveness and feasibility of widely used forecasting models for device-level flexibility analysis. In a typical device-level flexibility forecast, a market player is more concerned with the utility that the demand flexibility brings to the market, rather than the intrinsic forecast accuracy. In this regard, we provide comprehensive predictive modeling and scheduling of demand flexibility from household appliances to demonstrate the (financial and otherwise) viability of introducing flexibility-based DR in the Danish/Nordic market. Further, we investigate the correlation between the potential utility and the accuracy of the demand forecast model. Furthermore, we perform a number of experiments to determine the data granularity that provides the best financial reward to market players for adopting the proposed DR scheme. A cost-benefit analysis of forecast results shows that even with somewhat low forecast accuracy, market players can achieve regulation cost savings of 54% of the theoretically optimal.
OriginalsprogEngelsk
Titele-Energy 2018 - Proceedings of the 9th ACM International Conference on Future Energy Systems
Antal sider11
ForlagAssociation for Computing Machinery
Publikationsdato12 jun. 2018
Sider108-118
ISBN (Elektronisk)978-1-4503-5767-8
DOI
StatusUdgivet - 12 jun. 2018
BegivenhedNinth ACM International Conference on Future Energy Systems (ACM e-Energy) - , Tyskland
Varighed: 12 jun. 201815 jun. 2018

Konference

KonferenceNinth ACM International Conference on Future Energy Systems (ACM e-Energy)
LandTyskland
Periode12/06/201815/06/2018

Fingerprint

Demand forecasting
Demand response
Forecast accuracy
Uncertainty
Household
Schedule
Cost-benefit analysis
Viability
Reward
Renewable energy sources
Energy market
Energy demand
Nordic
Demand forecast
Experiment
Predictive modeling
Cost savings
Intrinsic
Imbalance

Citer dette

Neupane, B., Pedersen, T. B., & Thiesson, B. (2018). Utilizing Device-level Demand Forecasting for Flexibility Markets. I e-Energy 2018 - Proceedings of the 9th ACM International Conference on Future Energy Systems (s. 108-118). Association for Computing Machinery. https://doi.org/10.1145/3208903.3208922
Neupane, Bijay ; Pedersen, Torben Bach ; Thiesson, Bo. / Utilizing Device-level Demand Forecasting for Flexibility Markets. e-Energy 2018 - Proceedings of the 9th ACM International Conference on Future Energy Systems. Association for Computing Machinery, 2018. s. 108-118
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title = "Utilizing Device-level Demand Forecasting for Flexibility Markets",
abstract = "The uncertainty in the power supply due to fluctuating Renewable Energy Sources (RES) has severe (financial and other) implications for energy market players. In this paper, we present a device-level Demand Response (DR) scheme that captures the atomic (all available) flexibilities in energy demand and provides the largest possible solution space to generate demand/supply schedules that minimize market imbalances. We evaluate the effectiveness and feasibility of widely used forecasting models for device-level flexibility analysis. In a typical device-level flexibility forecast, a market player is more concerned with the utility that the demand flexibility brings to the market, rather than the intrinsic forecast accuracy. In this regard, we provide comprehensive predictive modeling and scheduling of demand flexibility from household appliances to demonstrate the (financial and otherwise) viability of introducing flexibility-based DR in the Danish/Nordic market. Further, we investigate the correlation between the potential utility and the accuracy of the demand forecast model. Furthermore, we perform a number of experiments to determine the data granularity that provides the best financial reward to market players for adopting the proposed DR scheme. A cost-benefit analysis of forecast results shows that even with somewhat low forecast accuracy, market players can achieve regulation cost savings of 54{\%} of the theoretically optimal.",
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Neupane, B, Pedersen, TB & Thiesson, B 2018, Utilizing Device-level Demand Forecasting for Flexibility Markets. i e-Energy 2018 - Proceedings of the 9th ACM International Conference on Future Energy Systems. Association for Computing Machinery, s. 108-118, Tyskland, 12/06/2018. https://doi.org/10.1145/3208903.3208922

Utilizing Device-level Demand Forecasting for Flexibility Markets. / Neupane, Bijay; Pedersen, Torben Bach; Thiesson, Bo.

e-Energy 2018 - Proceedings of the 9th ACM International Conference on Future Energy Systems. Association for Computing Machinery, 2018. s. 108-118.

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

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Neupane B, Pedersen TB, Thiesson B. Utilizing Device-level Demand Forecasting for Flexibility Markets. I e-Energy 2018 - Proceedings of the 9th ACM International Conference on Future Energy Systems. Association for Computing Machinery. 2018. s. 108-118 https://doi.org/10.1145/3208903.3208922