DFACTS Devices in Asymmetrical Power Grids: a Case Study

Boicea, Valentin A.; Sidea, Dorian O.; Plamanescu, Radu; Dumitrescu, Ana-Maria; Oancea, Constantin Daniel; Petre, Viorel

doi:10.1109/atee.2019.8724937

Cited by 2 publications

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“…Studied applications for these specific meter data included, but were not limited to, evaluation of dorms carbon footprint, monitoring power quality, utilising data as input for control algorithms for hybrid microgrids in local energy communities [41] and developing unique indicators of energy usage [9].…”

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confidence: 99%

Implementing Smart City Technologies to Inspire Change in Consumer Energy Behaviour

et al. 2021

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One of the main challenges in smart city models is consumer behaviour, namely guiding the efforts to promote optimal use of energy in the dynamics of the developing cities, through lower energy consumption without impact on the comfort level. This relates to all energy vectors and can be done through different means. The uptake stage of smart metering and information and communication technologies (ICT) varies in different countries, creating the need for tailored innovative approaches in motivating behavioural change. This paper presents the work carried out within the joint research project ITCity (an ICT platform for sustainable energy ecosystem in smart cities) between the European Union and Latin American Countries. Cooperation of energy researchers and experts in ICT and application developers facilitates adoption of a multipurpose interdisciplinary approach. This work aims at providing the smart city and energy research and innovation community broader understanding of factors influencing adoption of energy efficiency technologies. Different ways of guiding optimal energy use are addressed elaborating on the building blocks for a smart city which consider load patterns based on high resolution, high reporting rate measurements, extensive consumer surveys, available communication solution analysis and end-user interaction with the ICT tool based on gamification principles.

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confidence: 99%