Ver o conteúdo principal

Docentes

Biografia

Ian Scott é um economista quantitativo com mais de 10 anos de experiência internacional em consultoria e pesquisa, abrangendo análise económica, ciência de dados e estatística, políticas governamentais e modelação de mercado em toda a Europa, América do Norte e Ásia. Ian concluiu recentemente um doutoramento em Sistemas de Energia Sustentável no Instituto Superior Técnico (IST), como parte do Programa MIT Portugal. Ian é apaixonado pela aplicação das ciências económicas e estatísticas a problemas do mundo real. As suas áreas de interesse de pesquisa incluem tomada de decisão e modelação do comportamento de mercado no setor da energia, aplicação da tecnologia blockchain e desenvolvimento de cidades inteligentes. Atualmente, está a desenvolver soluções baseadas em blockchain para várias aplicações em cidades inteligentes, incluindo gestão de resíduos e comércio de eletricidade peer-to-peer, como parte do NOVA Cidade Urban Analytics Lab.

Publicações Cientificas

Almeida, F. D., Scott, I. J., Soro, J., Fernandes, D., Amaral, A. R., Catarino, M. L., Arêde, A., & Boto Ferreira, M. (2024)

Financial scarcity and cognitive performance: a meta-analysis. Journal Of Economic Psychology, 101, 1-19. Article 102702. https://doi.org/10.1016/j.joep.2024.102702

Huang, Chung-Ting & Scott, I. J. (2024)

Peer-to-peer multi-period energy market with flexible scheduling on a scalable and cost-effective blockchain. Applied Energy, vol. 367, 123331.DOI: https://doi.org/10.1016/j.apenergy.2024.123331

He, R., Small, M. J., Scott, I. J., Olarinre, M., Sandoval-Reyes, M., & Ferrão, P. (2023)

A Novel Domain Knowledge-Informed Machine Learning Approach for Modeling Solid Waste Management Systems. Environmental Science & Technology, Preprints. https://doi.org/10.1021/acs.est.3c04214

Schwidtal, J. M., Piccini, P., Troncia, M., Chitchyan, R., Montakhabi, M., Francis, C., Gorbatcheva, A., Capper, T., Mustafa, M. A., Andoni, M., Robu, V., Bahloul, M., Scott, I. J., Mbavarira, T., España, J. M. E., & Kiesling, L. (2023)

Emerging business models in local energy markets: a systematic review of peer-to-peer, community self-consumption, and transactive energy models. Renewable and Sustainable Energy Reviews, 179(June), 1-48. [113273]. https://doi.org/10.1016/j.rser.2023.113273

Scott, I., Neto, M. D. C., & Pinheiro, F. L. (2023)

Bringing trust and transparency to the opaque world of waste management with blockchain: a Polkadot parathread application. Computers & Industrial Engineering, 182(August), 1-17. [109347]. https://doi.org/10.2139/ssrn.3825072, https://doi.org/10.1016/j.cie.2023.109347

Vorobeva, D., Scott, I. J., Oliveira, T., & Neto, M. (2023)

Leveraging technology for waste sustainability: Understanding the adoption of a new waste management system. Sustainable Environment Research, (33), 1-10. [12]. https://doi.org/10.1186/s42834-023-00174-x

Kireeva, T., Scott, I., & Almeida, F. D. (2023)

Exploring trust in emerging technologies: an integrative model. (SSRN Electronic Journal). Social Science Research Network (SSRN), Elsevier. https://doi.org/10.2139/ssrn.4358570

Capper, T., Gorbatcheva, A., Mustafa, M. A., Bahloul, M., Schwidtal, J. M., Chitchyan, R., Andoni, M., Robu, V., Montakhabi, M., Scott, I. J., Francis, C., Mbavarira, T., Espana, J. M., & Kiesling, L. (2022)

Peer-to-peer, community self-consumption, and transactive energy: A systematic literature review of local energy market models. Renewable and Sustainable Energy Reviews, 162(July), 1-24. [112403]. https://doi.org/10.1016/j.rser.2022.112403

He, R., Sandoval-reyes, M., Scott, I., Semeano, R., Ferrão, P., Matthews, S., & Small, M. J. (2022)

Global knowledge base for municipal solid waste management: Framework development and application in waste generation prediction. Journal of Cleaner Production, 377(December), 1-11. [134501]. https://doi.org/10.1016/j.jclepro.2022.134501

Sarmento, P., Motta, M., Scott, I., Pinheiro, F. L., & De Castro Neto, M. (2022)

Impact of COVID-19 lockdown measures on waste production behavior in Lisbon. Waste Management, 138(February), 189-198. [Advanced online publication on 7th  December 2021]. https://doi.org/10.1016/j.wasman.2021.12.002

Vorobeva, D., Scott, I. J., Oliveira, T., & Neto, M. (2022)

Adoption of new household waste management technologies: The role of financial incentives and pro-environmental behavior. Journal of Cleaner Production, 362(August), 1-10. [132328]. https://doi.org/10.1016/j.jclepro.2022.132328

Scott, I. J., Carvalho, P. M. S., Botterud, A., & Silva, C. A. (2021)

Long-term uncertainties in generation expansion planning: Implications for electricity market modelling and policy. Energy, 227(Julho), 1-12. [120371]. https://doi.org/10.1016/j.energy.2021.120371

Diawuo, F. A.; Scott, I. J.; Baptista, P. C. & Silva, C. A. (2020)

Assessing the costs of contributing to climate change targets in sub-Saharan Africa: The case of the Ghanaian electricity system. Energy for Sustainable Development, Vol. 57, pp.32-47,. Doi: https://doi.org/10.1016/j.esd.2020.05.001.

Neves, D.; Scott, I. & Silva, C. A. (2020)

Peer-to-peer energy trading potential: An assessment for the residential sector under different technology and tariff availabilities, Energy, Vol. 205, 118023. Doi: https://doi.org/10.1016/j.energy.2020.118023.

Scott, I. J.; Carvalho, P. M. S.; Botterud, A. & Silva, Ca. A. (2019)

Clustering representative days for power systems generation expansion planning: Capturing the effects of variable renewables and energy storage. Applied Energy, Vol. 253, 113603. Doi: https://doi.org/10.1016/j.apenergy.2019.113603.

Scott, I. J.; Botterud, A.; Carvalho, PMS & Silva, CA (2019)

Renewable support policy evaluation: The importance of uncertaintyRenewable support policy evaluation: The importance of uncertainty. Conference: Applied Energy Symposium: MIT A+B, May 22-24, 2019 • Boston, USA. Link: http://www.energy-proceedings.org/wp-content/uploads/2020/01/AEAB2019_paper_121.pdf

Scott, I. J.; Botterud, A.; Carvalho, P. M. S.; Silva, C. A. S. (2020)

Renewable energy support policy evaluation: The role of long-term uncertainty in market modelling,