Browsing by Author "Velosa, Nuno Alexandre Silva"
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- PROCSIM: an energy community simulator to develop and evaluate load balancing schemesPublication . Velosa, Nuno Alexandre Silva; Quintal, Filipe Magno Gouveia; Pereira, Amâncio Lucas de SousaClimate change is one of the biggest challenges of the present millennium. The energy sector is the biggest contributor to this problem with approximately 25% of the global emissions. In order to mitigate this problem, one of the main solutions concerns to the use of energy from renewable sources. It is important to begin taking better advantage of the renewable resources more effectively and more often. In this sense, it is very important to develop mechanisms to balance the demand and supply, with the goal of minimizing, as much as possible, the use of energy from non renewable sources. For this reason, Renewable Energy Communities (RECs) started to emerge. They allow the sharing of the resources, contributing to a better management of them. However, these are not problem free. There are two main challenges that need to be solved: avoid a bad management of the renewable resources, hence avoiding the need to acquire energy from outside the community, and guarantee a fair distribution of the resources. In this regard, many researchers are focusing their attentions in load shifting approaches (adapt the appliances running time to better balance the load). Nevertheless, most of them use implicit approaches through the use of incentives (such as tariffs and dynamic pricing), which can be considered unfair approaches since richer people tend to benefit (which is not supposed, because ideally all community members should benefit the same). Based on this, in this work it is suggested an explicit load shifting approach based on the distribution of the timeslots, using the Multiple Knapsack combinatorial optimization problem. Although there are some literature which demonstrate the applicability of Knapsack in a variety of real world problems, the same does not happen in the energy field. Furthermore, since a large quantity of data is required to test and evaluate multiple scenarios in this load balancing scheme, and taking in consideration that only two energy community datasets were found on the literature, in this thesis it is also proposed an energy community simulator that allows to create different Energy Community (EC) datasets and evaluate the impact of the optimization, considering only Photovoltaics (PV) production (other types of renewable sources as well as batteries are not considered). Finally, in order to evaluate the impact of the developed load balancing strategy, the developed sim ulator was used in three different experiments: variation in bin size, variation in community size and variation in flexibility. The results were positive and showed that this strategy can provide a better man agement of the PV resources once it increased the PV use, decreased the PV waste and also decreased the use of energy from the grid.