Energy flexibility under the IoT paradigmthe role of occupants

Zusammenfassung

In the context of the energy crisis and the fight against climate change, we cannot ignore that the primary energy consumption in buildings represents 40% of the total, creating peak demands that are not sustainable for the grid. One widely accepted countermeasure is reshaping the end-users’ patterns of consumption through a series of strategies called Demand Response, which applies IoT technologies to energy strategies in buildings. Modifying the end-users’ pattern means involving people in the strategies, which adds complexity since several transversal topics are involved, e.g. thermal comfort, lack of knowledge, acceptance of new technologies, behavioural beliefs. To explore these facets of the role of the users in the energy flexibility strategies under the IoT paradigm, a multi-disciplinary approach was needed. The aim of understanding and preparing for the energy and technology transition that we are experiencing has been pursued through the definition of the objectives listed as follows: O1. To identify challenges and facets related to the energy and technology transition. O2. To study the role given to the users in energy efficiency and flexibility strategies within the IoT paradigm, toward a user-centric view of the problem. O3. To analyse the state-of-the-art regarding the IoT application to energy efficiency and flexibility strategies. O4. To evaluate the acceptability of the users to the main energy efficiency and flexibility strategies performed with an IoT platform. O5. To study the interaction of the end-users’ with smart technologies during energy efficiency and flexibility strategies. O6. To estimate the users’ thermal comfort during energy efficiency and flexibility strategies. O7. To support methods, e.g. the modification of users' patterns of use, to unburden and respond to the needs of the grid. O8. To offer the cognitive tools to optimise the planning of DR events at a district level. The methodology used to cover these objectives is developed through several techniques. Through the state of the art, it was possible to distinguish the consumers depending on their roles into categories and create an adapted methodology for each one of them. For consumers who are not enrolled or do not know the demand response programs, the chosen methodology consisted of creating a questionnaire to evaluate the awareness and the attitude of consumers toward the topic. As a step forward, tests of significance were used to spot which aspects influence their decisions. For consumers who are already enrolled, we used a real-world dataset to spot non-efficient energy behaviour. In this case, clustering was used to categorise occupants’ acceptance and patterns of use in order to create groups of consumers with similar behaviours, in order to propose an application of the strategies at a district scale. In the results and conclusions, it is explained the need to introduce IoT technologies as a means to achieve personalised solutions for the occupants. The response of people to the energy-saving pursuit is far from being objective nor unanimous, making the one-fits-all formula hardly applicable. The IoT is proposed in this work as a link between the needs of both the users and the grid. It also enables a user-centric approach, by assigning an active role to the end-users while leading to smarter use of energy. To achieve that, communication with the users is essential, since it was demonstrated that simple explanations were enough to raise users’ interest. Computational times can be contained by applying this principle at a district level. The districts can be formed by users that have similar energy behaviours, or at least similar demographic and background information, since one of the main results of this thesis is that such characteristics are predictors of the behaviour.