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

Nikoleta Andreadou, Dimitrios Thomas, Antonio De Paola, Evangelos Kotsakis () and Gianluca Fulli
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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

Energies, 2023, vol. 16, issue 16, 1-28

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.

Keywords: explicit demand response; residential demand response; baseline; key performance indicators (KPIs) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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