Incentive-Based Demand Response Framework for Residential Applications: Design and Real-Life Demonstration
In 2020, residential sector loads reached 25% of the overall electrical consumption in Europe and it is foreseen to stabilise at 29% by 2050. However, this relatively small increase demands, among others, changes in the energy consuming behaviour of households. To achieve this, Demand Response (DR)...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-07-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/14/14/4315 |
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| author | Angelina D. Bintoudi Napoleon Bezas Lampros Zyglakis Georgios Isaioglou Christos Timplalexis Paschalis Gkaidatzis Athanasios Tryferidis Dimosthenis Ioannidis Dimitrios Tzovaras |
| author_facet | Angelina D. Bintoudi Napoleon Bezas Lampros Zyglakis Georgios Isaioglou Christos Timplalexis Paschalis Gkaidatzis Athanasios Tryferidis Dimosthenis Ioannidis Dimitrios Tzovaras |
| author_sort | Angelina D. Bintoudi |
| collection | DOAJ |
| description | In 2020, residential sector loads reached 25% of the overall electrical consumption in Europe and it is foreseen to stabilise at 29% by 2050. However, this relatively small increase demands, among others, changes in the energy consuming behaviour of households. To achieve this, Demand Response (DR) has been identified as a promising tool for unlocking the hidden flexibility potential of residential consumption. In this work, a holistic incentive-based DR framework aiming towards load shifting is proposed for residential applications. The proposed framework is characterised by several innovative features, mainly the formulation of the optimisation problem, which models user satisfaction and the economic operation of a distributed household portfolio, the customised load forecasting algorithm, which employs an adjusted Gradient Boosting Tree methodology with enhanced feature extraction and, finally, a disaggregation tool, which considers electrical features and time of use information. The DR framework is first validated through simulation to assess the business potential and is then deployed experimentally in real houses in Northern Greece. Results demonstrate that a mean 1.48% relative profit can be achieved via only load shifting of a maximum of three residential appliances, while the experimental application proves the effectiveness of the proposed algorithms in successfully managing the load curves of real houses with several residents. Correlations between market prices and the success of incentive-based load shifting DR programs show how wholesale pricing should be adjusted to ensure the viability of such DR schemes. |
| first_indexed | 2024-03-10T09:39:57Z |
| format | Article |
| id | doaj.art-2db6a1282e804f8fa85b59611c8fb69f |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T09:39:57Z |
| publishDate | 2021-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-2db6a1282e804f8fa85b59611c8fb69f2023-11-22T03:43:34ZengMDPI AGEnergies1996-10732021-07-011414431510.3390/en14144315Incentive-Based Demand Response Framework for Residential Applications: Design and Real-Life DemonstrationAngelina D. Bintoudi0Napoleon Bezas1Lampros Zyglakis2Georgios Isaioglou3Christos Timplalexis4Paschalis Gkaidatzis5Athanasios Tryferidis6Dimosthenis Ioannidis7Dimitrios Tzovaras8Information Technologies Institute, Centre for Research and Technology—Hellas, 57001 Thessaloniki, GreeceInformation Technologies Institute, Centre for Research and Technology—Hellas, 57001 Thessaloniki, GreeceInformation Technologies Institute, Centre for Research and Technology—Hellas, 57001 Thessaloniki, GreeceInformation Technologies Institute, Centre for Research and Technology—Hellas, 57001 Thessaloniki, GreeceInformation Technologies Institute, Centre for Research and Technology—Hellas, 57001 Thessaloniki, GreeceInformation Technologies Institute, Centre for Research and Technology—Hellas, 57001 Thessaloniki, GreeceInformation Technologies Institute, Centre for Research and Technology—Hellas, 57001 Thessaloniki, GreeceInformation Technologies Institute, Centre for Research and Technology—Hellas, 57001 Thessaloniki, GreeceInformation Technologies Institute, Centre for Research and Technology—Hellas, 57001 Thessaloniki, GreeceIn 2020, residential sector loads reached 25% of the overall electrical consumption in Europe and it is foreseen to stabilise at 29% by 2050. However, this relatively small increase demands, among others, changes in the energy consuming behaviour of households. To achieve this, Demand Response (DR) has been identified as a promising tool for unlocking the hidden flexibility potential of residential consumption. In this work, a holistic incentive-based DR framework aiming towards load shifting is proposed for residential applications. The proposed framework is characterised by several innovative features, mainly the formulation of the optimisation problem, which models user satisfaction and the economic operation of a distributed household portfolio, the customised load forecasting algorithm, which employs an adjusted Gradient Boosting Tree methodology with enhanced feature extraction and, finally, a disaggregation tool, which considers electrical features and time of use information. The DR framework is first validated through simulation to assess the business potential and is then deployed experimentally in real houses in Northern Greece. Results demonstrate that a mean 1.48% relative profit can be achieved via only load shifting of a maximum of three residential appliances, while the experimental application proves the effectiveness of the proposed algorithms in successfully managing the load curves of real houses with several residents. Correlations between market prices and the success of incentive-based load shifting DR programs show how wholesale pricing should be adjusted to ensure the viability of such DR schemes.https://www.mdpi.com/1996-1073/14/14/4315demand-responseload managementincentive-basedoptimisation |
| spellingShingle | Angelina D. Bintoudi Napoleon Bezas Lampros Zyglakis Georgios Isaioglou Christos Timplalexis Paschalis Gkaidatzis Athanasios Tryferidis Dimosthenis Ioannidis Dimitrios Tzovaras Incentive-Based Demand Response Framework for Residential Applications: Design and Real-Life Demonstration Energies demand-response load management incentive-based optimisation |
| title | Incentive-Based Demand Response Framework for Residential Applications: Design and Real-Life Demonstration |
| title_full | Incentive-Based Demand Response Framework for Residential Applications: Design and Real-Life Demonstration |
| title_fullStr | Incentive-Based Demand Response Framework for Residential Applications: Design and Real-Life Demonstration |
| title_full_unstemmed | Incentive-Based Demand Response Framework for Residential Applications: Design and Real-Life Demonstration |
| title_short | Incentive-Based Demand Response Framework for Residential Applications: Design and Real-Life Demonstration |
| title_sort | incentive based demand response framework for residential applications design and real life demonstration |
| topic | demand-response load management incentive-based optimisation |
| url | https://www.mdpi.com/1996-1073/14/14/4315 |
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