Load Flexibility Forecast for DR Using Non-Intrusive Load Monitoring in the Residential Sector

Alexandre Lucas, Luca Jansen, Nikoleta Andreadou, Evangelos Kotsakis and Marcelo Masera
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Alexandre Lucas: European Commission, Joint Research Centre (JRC), 21027 Ispra (VA), Italy
Luca Jansen: European Commission, Joint Research Centre (JRC), 21027 Ispra (VA), Italy
Nikoleta Andreadou: European Commission, Joint Research Centre (JRC), 21027 Ispra (VA), Italy
Evangelos Kotsakis: European Commission, Joint Research Centre (JRC), 21027 Ispra (VA), Italy
Marcelo Masera: European Commission, Joint Research Centre (JRC), 21027 Ispra (VA), Italy

Energies, 2019, vol. 12, issue 14, 1-19

Abstract: Demand response services and energy communities are set to be vital in bringing citizens to the core of the energy transition. The success of load flexibility integration in the electricity market, provided by demand response services, will depend on a redesign or adaptation of the current regulatory framework, which so far only reaches large industrial electricity users. However, due to the high contribution of the residential sector to electricity consumption, there is huge potential when considering the aggregated load flexibility of this sector. Nevertheless, challenges remain in load flexibility estimation and attaining data integrity while respecting consumer privacy. This study presents a methodology to estimate such flexibility by integrating a non-intrusive load monitoring approach to load disaggregation algorithms in order to train a machine-learning model. We then apply a categorization of loads and develop flexibility criteria, targeting each load flexibility amplitude with a corresponding time. Two datasets, Residential Energy Disaggregation Dataset (REDD) and Refit, are used to simulate the flexibility for a specific household, applying it to a grid balancing event request. Two algorithms are used for load disaggregation, Combinatorial Optimization, and a Factorial Hidden Markov model, and the U.K. demand response Short Term Operating Reserve (STOR) program is used for market integration. Results show a maximum flexibility power of 200–245 W and 180–500 W for the REDD and Refit datasets, respectively. The accuracy metrics of the flexibility models are presented, and results are discussed considering market barriers.

Keywords: flexibility forecast; demand response; STOR; disaggregated loads; non-intrusive monitoring (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: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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