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Smart energy consumption of Hong Kong households based on changing weather conditions and saving practices

About 

Climate and energy issues are interconnected in biophysical and social systems. Household energy consumption is one of the main carbon emission sources in Hong Kong, so that reducing household energy consumption is a principle approach for mitigating climate change. Smart household power management based on big data provides practical climate change solutions and facilitates comfort living. For deriving practical solutions, stakeholders and multi-disciplinary experts in social, environmental, and computer science have to work together. Based on nonlinear dynamic relationships between energy consumption patterns and climate conditions, machine learning algorithms will be used to provide power saving advices.

High frequency time-series analysis for climate variables are used to define current environmental states and to forecast short-term conditions. Reducing household energy consumption is a mitigation approach which empowers citizens to combat climate change. In Hong Kong, household energy consumption is a substantial carbon contributor. Deeper understandings of climate conditions are beneficial for climate-sensitive practices in terms of sustainable development and governance. Also, empirical relationships can be established between household electricity bill data and climate variables. We will design new smart algorithms to deliver the energy-saving advices to households based on long-term climate analysis and smart energy meter measurements.

In this project, we will work with 30 households who will install smart meters and provide information for their daily energy consumption behaviours in Sai Kung. Pre- and post-intervention questionnaires will be conducted to investigate households’ energy consumption attitudes and behaviours. For evaluating the effectiveness of smart algorithms and energy-saving advices, the electricity bills from the households will be used to quantify their energy reductions.

Overall, we will develop effective climate change adaptation and mitigation practices through high frequency time-series analysis based on smart meter data and weather conditions. Evidence and technology-driven approaches to save energy and to mitigate climate change on a household scale will be established to enhance the sustainability of our communities. 

Required skills

We look for motivated students who are interested in climate and energy approaches for pressing environmental and social issues, with our international and local collaboration networks.

Principal Investigator

 

Dr Chun

Dr. Kwok Pan Chun

Assistant Professor, Department of Geography

 

Co-Investigators
 

Dr. choi

Dr. Byron Choi

Associate Professor, Department of Computer Science

Dr Mah

Dr. Daphne Ngar-yin Mah

Assistant Professor, Department of Geography

Kevin Tek Sheng Lo

Dr. Kevin Tek Sheng Lo

Assistant Professor, Department of Geography