Abstract
Policy and new technologies are transforming the energy landscape in the UK. Centralised control of electrical generation and unidirectional distribution have a finite part in a sustainable energy system. Subsidies have encouraged an increase in distributed resources. At the same time closure of larger fossilfuelled power plants is reducing system inertia on energy networks. In this study, a decentralised proactive approach to demand-side response exploiting building thermal inertia is presented using machine learning methods and a real-time
adaptation algorithm. This paper proposes a dynamic 2-step energy consumption prediction scheme that can be configured to provide efficiency opportunities and the potential to reduce energy costs in buildings. The approach adopted optimises energy usage through existing demand-side response mechanisms utilising decentralised frequency regulation. The
paper concludes with a discussion on the future direction of research.
adaptation algorithm. This paper proposes a dynamic 2-step energy consumption prediction scheme that can be configured to provide efficiency opportunities and the potential to reduce energy costs in buildings. The approach adopted optimises energy usage through existing demand-side response mechanisms utilising decentralised frequency regulation. The
paper concludes with a discussion on the future direction of research.
| Original language | English |
|---|---|
| Number of pages | 6 |
| Publication status | Published - 15 Mar 2019 |
| Event | International Conference on Innovative Applied Energy 2019 - Oxford Conference Center, Oxford, United Kingdom Duration: 14 Mar 2019 → 15 Mar 2019 http://iape-conference.org/ |
Conference
| Conference | International Conference on Innovative Applied Energy 2019 |
|---|---|
| Abbreviated title | IAPE’19 |
| Country/Territory | United Kingdom |
| City | Oxford |
| Period | 14/03/19 → 15/03/19 |
| Internet address |