Transições para a energia sustentável na indústria de catering

O1: To collect year-long water and electricity consumption from five IKs in Lisbon in real operation conditions and to enrich this data with detailed information about the IKs operation. To the best of our knowledge, the only two datasets with IK data are the ones that were developed by us in the FIK and nexIK projects. While this data is relevant to test some initial methods, to generalize the research efforts, a longer and more diverse sample is necessary. More importantly, in the SENCY project, we will seek to collect data on restaurants that have different characteristics among them, e.g., traditional restaurants that serve pre-fixed meals, to a la carte restaurants, and snack bars. O2: To provide an In-depth characterization of the Portuguese IK sector through a phone survey with at least 250 restaurants in Portugal. Due to the unforeseen events at the beginning of this decade, the IK sector had the need to reinvent itself, and what was true before 2020 is probably not today. In this sense, in order to fully the project goals and pave the way to national and international generalization, it is necessary to gain an in-depth knowledge of the sector considering several aspects such as the type of cuisine prepared, the size and constitution of the IKs, reliance in electricity and available of renewables, and the cost of operation. O3: To extract value from electricity and water consumption data from IKs using data-driven methodologies. Unlike the domestic sector, which has seen great efforts to leverage smart-meter data, the same is not true in the IK sector. The SENCY project aims to leverage state-of-the-art ML and data science methods to extract value for smart meter data. More precisely, this project is focused on three key research areas that are still widely under-explored, particularly in the industrial sector: i) data-driven system dynamics to model appliance interactions, ii) federated learning for privacy-preserving forecasts, and iii) data-driven feature extraction and transfer-learning for energy and water disaggregation. O4: To assess the potential of IKs to contribute to increasing the penetration of RES in the energy mix, by participating in electricity markets. Unlike the domestic sector, which has seen significant research towards increasing the penetration of RES and big industrial players that are allowed to participate in electricity markets, the IK sector has been largely ignored despite being a sector with very high energy demand. In this sense, this project will first develop data-driven methodologies to understand the flexibility of IK appliances. Then, control strategies will be developed and tested to show how this flexibility can be aggregated and used to enable participation in electricity markets. O5: To engage with the major IK stakeholders and understand their perceptions and motivations towards the introduction of DERs and participation in electricity markets. When it comes to IKs there is an almost complete absence of research on human aspects. Ultimately, this restricts the assessment of the proposed methodologies/models. The SENCY project will not only develop user-centered research methodologies to understand the stakeholder's main pains and gains, but it will also promote user testing of research prototypes where the users will be able to simulate their participation in energy efficiency initiatives and electricity markets.