Interrogating Fintech-Enabled Solar Power as 'Energy Democracy' in Hong Kong
Project Description

Solar power is widely imagined as a more 'democratized' technology that can effectively intervene in the wicked problem of maintaining economic growth while curbing carbon emissions. Decentralized solar energy technologies, like home solar systems and energy trading platforms, are increasingly deployed in dense, urban environments to meet electricity needs, and often use digitalized platforms to manage energy and financial transactions between prosumers - those who consume the energy they produce and sell extra energy to a grid. With Hong Kong fast-becoming a testing bed for integrating next generation solar energy technologies into smart city initiatives and Hong Kong entrepreneurs introducing blockchain technologies to link solar panels and smart meters, this project will interrogate how decentralized and digitalized solar technologies are being built and tested in HKSAR. How do political and economic cultures shape the deployment of solar technologies for sustainability? How do different publics perceive such innovations? What do notions like 'energy democracy' mean in these contexts? The research contributes to nascent research on the sociopolitical implications of 'platformization' where different systems for energy production and provision, electricity exchange between prosumers, surveillance and monitoring systems, and cryptocurrency are being integrated together, and are then labelled as "more democratic."

DELINA Laurence Laurencio
DELINA Laurence Laurencio
Course type
Applicant's Roles

The UROP students will assist Prof. Laurence Delina in: (1) validating the transcribed primary data (i.e. checking the veracity of the transcripts versus the recorded interviews); (2) coding the data using MAXQDA, a specialized qualitative analysis software; (3) analysing the data for themes; and (4) writing journal articles.

Applicant's Learning Objectives

At the end of the UROP, the student is expected to have developed their skills to:
1. Conduct validation of the audio-recorded primary data;
2. Code primary data using MAXQDA;
3. Data analysis; and
4. Reporting of research outputs in journal/s.

Complexity of the project