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Holistic Evaluation of Demand Response Events in Real Pilot Sites: From Baseline Calculation to Evaluation of Key Performance Indicators

Author

Listed:
  • Nikoleta Andreadou

    (Seidor Italy, 21027 Ispra, Italy)

  • Dimitrios Thomas

    (Energy Security, Distribution and Markets Unit, Energy, Transport and Climate Directorate, Joint Research Centre (JRC), European Commission, 21027 Ispra, Italy)

  • Antonio De Paola

    (Energy Security, Distribution and Markets Unit, Energy, Transport and Climate Directorate, Joint Research Centre (JRC), European Commission, 21027 Ispra, Italy)

  • Evangelos Kotsakis

    (Energy Security, Distribution and Markets Unit, Energy, Transport and Climate Directorate, Joint Research Centre (JRC), European Commission, 21027 Ispra, Italy)

  • Gianluca Fulli

    (Energy Security, Distribution and Markets Unit, Energy, Transport and Climate Directorate, Joint Research Centre (JRC), European Commission, 21027 Ispra, Italy)

Abstract

Explicit demand response plays a significant role in the future energy grid transition, as it involves end consumers in smart grid activities and, at the same time, exploits the potential of flexibility, giving the opportunity to grid operators to accommodate a total amount of energy without the need to reinforce the grid infrastructure. For evaluating the successfulness of a demand response program, thus, evaluating its advantages, it is fundamental to have an accurate baseline curve consumption along with meaningful key performance indicators. In this work, we propose a novel way of calculating the baseline consumption using artificial intelligence techniques. In particular, regression models have been applied to a database of historical data. In order to present a complete evaluation of demand response programs, we present five key performance indicators (KPIs). The KPIs have been selected so as to depict the successfulness of the explicit demand response program. We suggest a novel way of evaluating two of the five KPI using a quantitative approach. We also apply the proposed methodology for baseline calculation and KPIs evaluation in a practical example: two pilot sites have been used and real-life scenarios of demand response events have been applied for this scope to actual nonindustrial consumers and especially residential consumers. The baseline has been calculated for these pilot sites and the KPIs have been evaluated for them. The presented results complete the picture of evaluating a real-life demand response program and show the effectiveness of the selected approach. The proposed schemes for baseline calculation and KPI evaluation can be used by the scientific community for evaluating future demand response programs, especially in the residential sector.

Suggested Citation

  • Nikoleta Andreadou & Dimitrios Thomas & Antonio De Paola & Evangelos Kotsakis & Gianluca Fulli, 2023. "Holistic Evaluation of Demand Response Events in Real Pilot Sites: From Baseline Calculation to Evaluation of Key Performance Indicators," Energies, MDPI, vol. 16(16), pages 1-28, August.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:16:p:6048-:d:1220037
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    References listed on IDEAS

    as
    1. Ottavia Valentini & Nikoleta Andreadou & Paolo Bertoldi & Alexandre Lucas & Iolanda Saviuc & Evangelos Kotsakis, 2022. "Demand Response Impact Evaluation: A Review of Methods for Estimating the Customer Baseline Load," Energies, MDPI, vol. 15(14), pages 1-36, July.
    2. Vivien Kizilcec & Catalina Spataru & Aldo Lipani & Priti Parikh, 2022. "Forecasting Solar Home System Customers’ Electricity Usage with a 3D Convolutional Neural Network to Improve Energy Access," Energies, MDPI, vol. 15(3), pages 1-25, January.
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