Impact of climate change and socioeconomic factors on domestic energy consumption: The case of Hong Kong and Singapore (2022)
Journal Article
Lam, C., He, Q., Cheng, K. L., Fan, P. Y., Chun, K. P., Choi, B., …Yetemen, O. (2022). Impact of climate change and socioeconomic factors on domestic energy consumption: The case of Hong Kong and Singapore. Energy Reports, 8(November 2022), 12886-12904. https://doi.org/10.1016/j.egyr.2022.09.059

Temperature and population growth are key drivers of energy consumption. However, the relative importance of climatic and socioeconomic factors driving energy consumption at different temporal scales is not well-understood. Therefore, we developed a... Read More about Impact of climate change and socioeconomic factors on domestic energy consumption: The case of Hong Kong and Singapore.

Investigation of flow augmentation and dynamic stall control devices as performance enhancement of lift-driven vertical axis wind turbine using high-fidelity CFD methods (2022)
Thesis
Syawitri, T. P. Investigation of flow augmentation and dynamic stall control devices as performance enhancement of lift-driven vertical axis wind turbine using high-fidelity CFD methods. (Thesis). University of the West of England. Retrieved from https://uwe-repository.worktribe.com/output/8045334

This study performs an investigation of dynamic stall control (Gurney flap (GF)) and flow augmentation (straight upstream deflector (SUD)) devices to improve the performance of lift-driven Vertical Axis Wind Turbine (VAWT) as they can improve the pow... Read More about Investigation of flow augmentation and dynamic stall control devices as performance enhancement of lift-driven vertical axis wind turbine using high-fidelity CFD methods.

Nigeria’s legal responses to climate change obligations (2022)
Thesis
Izoukumor, N. Nigeria’s legal responses to climate change obligations. (Thesis). University of the West of England. Retrieved from https://uwe-repository.worktribe.com/output/7856248

This thesis set out to analyse the effectiveness of the Nigerian legal mechanisms (laws, policies, regulations, and institutions) to achieve the international climate change obligations stemming from the UNFCCC, Kyoto Protocol, and the Paris Agreemen... Read More about Nigeria’s legal responses to climate change obligations.

Curbing excess: High energy consumption and the fair energy transition (2022)
Report
Cass, N., Lucas, K., Adeel, M., Anable, J., Buchs, M., Lovelace, R., …Mullen, C. (2022). Curbing excess: High energy consumption and the fair energy transition. Centre for Research into Energy Demand Solutions (CREDS)

The Centre for Research into Energy Demand Solutions (CREDS) is a research programme dedicated to understanding the role of reduced energy demand in the UK’s transition to a net-zero carbon society. This research project investigated the household... Read More about Curbing excess: High energy consumption and the fair energy transition.

Life cycle optimisation of building retrofitting considering climate change effects (2022)
Journal Article
Luo, X. J., & Oyedele, L. O. (2022). Life cycle optimisation of building retrofitting considering climate change effects. Energy and Buildings, 258, 111830. https://doi.org/10.1016/j.enbuild.2022.111830

Novelty: Climate change has significant impacts on building energy performance. A novel life cycle optimisation strategy is developed for determining optimal retrofitting solutions for office buildings with climate change effects taken into considera... Read More about Life cycle optimisation of building retrofitting considering climate change effects.

A self-adaptive deep learning model for building electricity load prediction with moving horizon (2022)
Journal Article
Luo, X., & Oyedele, L. (2022). A self-adaptive deep learning model for building electricity load prediction with moving horizon. Machine Learning with Applications, 7, Article 100257. https://doi.org/10.1016/j.mlwa.2022.100257

A self-adaptive deep learning model powered by ranking selection-based particle swarm optimisation (RSPSO) is developed to predict electricity load in buildings with moving horizons. The main features of the load prediction model include its self-ada... Read More about A self-adaptive deep learning model for building electricity load prediction with moving horizon.