Paulo Manuel Sousa

Abstract
Renewable Energy Communities (RECs) are emerging as an effective concept and model to empower the active participation of citizens in the energy transition, not only as energy consumers but also as promoters of environmentally friendly energy generation solutions, particularly through the use of photovoltaic panels. This paper aims to contribute to the management and optimization of individual and community Distributed Energy Resources (DER). The solution follows a price and source-based REC management program, in which consumers' day-ahead flexible loads (Flex Offers) are shifted according to electricity generation availability, prices, and personal preferences, to balance the grid and incentivize user participation. The heuristic approach used in the proposed algorithms allows for the optimization of energy resources in a distributed edge-and-fog approach with a low computational overhead. The simulations performed using real-world energy consumption and flexibility data of a REC with 50 dwellings show an average cost reduction, taking into consideration all the seasons of the year, of 6.5%, with a peak of 12.2% reduction in the summer, and an average increase of 32.6% in individual self-consumption. In addition, the case study demonstrates promising results regarding grid load balancing and the introduction of intra-community energy trading.

Abstract
The electricity field is facing major challenges in the implementation of Renewable Energy Sources (RES) at a large scale. End users are taking on the role of electricity producers and consumers simultaneously (prosumers), acting like Distributed Energy Resources (DER), injecting their excess electricity into the grid. This challenges the management of grid load balance, increases running costs, and is later reflected in the tariffs paid by consumers, thus threatening the widespread of RES. The Flexigy project explores a solution to this topic by proposing a smart-grid architecture for day-ahead flexibility scheduling of individual and Renewable Energy Community (REC) resources. Our solution is prepared to allow Transmission System Operators (TSO) to request Demand Response (DR) services in emergency situations. This paper overviews the grid balance problematic, introduces the main concepts of energy flexibility and DR, and focuses its content on explaining the Flexigy architecture.

Abstract
Schedulability analyses, while valuable in theoretical research, cannot be used in practice to reason about the timing behaviour of a real-time system without including the overheads induced by the implementation of the scheduling algorithm. In this paper, we provide an overhead-aware schedulability analysis based on demand bound functions for two hard real-time semi-partitioned scheduling algorithms, EDFWM- and C=D. This analysis is based on a novel implementation that uses a global clock to reduce the overheads incurred due to the release jitter of migrating subtasks. The analysis is used to guide the respective off-line task assignment and splitting procedures. Finally, results of an evaluation are provided highlighting how the different algorithms perform with and without a consideration of overheads.

Abstract
Hard real- time multiprocessor scheduling has seen, in recent years, the flourishing of semi-partitioned scheduling algorithms. This category of scheduling schemes combines elements of partitioned and global scheduling for the purposes of achieving efficient utilization of the system's processing resources with strong schedulability guarantees and with low dispatching overheads. The sub-class of slot-based "task-splitting" scheduling algorithms, in particular, offers very good trade-offs between schedulability guarantees (in the form of high utilization bounds) and the number of preemptions/migrations involved. However, so far there did not exist unified scheduling theory for such algorithms; each one was formulated in its own accompanying analysis. This article changes this fragmented landscape by formulating a more unified schedulability theory covering the two state-of-the-art slot-based semi-partitioned algorithms, S-EKG and NPS-F (both fixed job-priority based). This new theory is based on exact schedulability tests, thus also overcoming many sources of pessimism in existing analysis. In turn, since schedulability testing guides the task assignment under the schemes in consideration, we also formulate an improved task assignment procedure. As the other main contribution of this article, and as a response to the fact that many unrealistic assumptions, present in the original theory, tend to undermine the theoretical potential of such scheduling schemes, we identified and modelled into the new analysis all overheads incurred by the algorithms in consideration. The outcome is a new overhead-aware schedulability analysis that permits increased efficiency and reliability. The merits of this new theory are evaluated by an extensive set of experiments.

Abstract
We present Carousel-EDF, a new hierarchical scheduling algorithm for a system of identical processors, and its overhead-aware schedulability analysis based on demand bound functions. Carousel-EDF is an offshoot of NPS-F and preserves its utilization bounds, which are the highest among algorithms not based on a single dispatching queue and that have few preemptions. Furthermore, with respect to NPS-F, Carousel-EDF reduces by up to 50% the number of context switches and of preemptions caused by the high-level scheduler itself. The schedulability analysis we present in this paper is grounded on a prototype implementation of Carousel-EDF that uses a new implementation technique for the release of periodic tasks. This technique reduces the pessimism of the schedulability analysis presented and can be applied, with similar benefits, to other scheduling algorithms such as NPS-F.