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21	Determining the Technical Potential of Demand Response on the Åland Islands / Utvärdering av den tekniska potentialen för efterfrågeflexibilitet på Åland Nordlund, Edvard, Lind, Emil January 2021 (has links) With increasing intermittency from renewable energy production, such as solar and wind power, the need for increased flexibility is quickly arising. The Åland Islands have an ambitious energy transition agenda with the goal of having a 100 % renewable energy system. Since there is no possibility of hydropower acting as regulatory power on Åland, reaching the goal is a challenging task. Increasing flexibility can be achieved by either implementing energy storage in the system or by matching the demand with the production. The purpose of this study was to estimate and evaluate the technical potential of demand response (DR) on Åland, both in 2019 and for a scenario in 2030 when domestic production of wind and solar have increased. Six areas of interest were identified; electric heating, refrigeration processes, lighting, ventilation and air conditioning, electric vehicles and industries. Electricity import from Sweden to Åland was examined since high import coincides with either low domestic renewable production or high consumption. Import is therefore a good indicator for when flexibility is most required. The results show that the technical potential of DR on Åland can lower the maximum electricity import from Sweden by 18 % in 2019. 4.3 % of the total import can be moved to times when there is less stress on the grid. Electric heating is the biggest contributor, and can by itself lower the import with three fourths of the total reduction. The domestic renewable production for 2019 is too low for DR to have an effect on the self-sufficiency. In 2030, the self-sufficiency and utilization of domestic renewable production could be increased with 4.2-9.9 % and 5.4-12 % respectively when using DR, depending on if vehicle-to-grid is implemented on a large scale or not. The cost of implementing DR is still uncertain, and varies between different resources. Nonetheless, DR in electric heating is presumably a less expensive alternative in comparison to batteries, while providing a similar service. Åland Demand response Energy storage system Virtual power plant Peak shaving Self-sufficiency Grid stability Smart Energy Åland Åland Efterfrågeflexibilitet Energilagring Virtuella kraftverk Effekttoppar Självförsörjning Nätstabilitet Smart Energy Åland Energy Systems Energisystem
22	Vägval för Uppsala kommun : Ett utvecklat verktyg som kan beskriva och förutspå ett distrikts effektkonsumtion och dess effekttoppar Johansson Thorell, Elias, Shakkal, Elias, Hallström, Jonatan, Rosten, Martin, Lindhe, Moses, Spjut, Vilmer, Lundgren, William January 2023 (has links) This report is based on the work carried out on behalf of Uppsala Municipality within the framework of the course Independent Work in Energy Systems.The main purpose of the project was to develop a tool capable of generatingreliable simulations of power demand in 24 areas for the future developmentof the Southeast District in Uppsala. The goal was also for the tool to assistin sizing the energy system in the areas and provide suggestions for futuresolutions that can be adapted for the district.The tool was developed in the Python programming language to be compatible with Excel, as agreed upon with Uppsala Municipality. The tool hasthe ability to simulate the total power demand from different types of buildings and model the power load resulting from electric vehicle charging. Inaddition to this, the tool can calculate the electricity production from solar panels, thereby creating simulations of the total power demand in theSoutheast District. Energianvändning stadsplanering hållbar stadsplanering flexibilitet. effekttoppar område verktyg förutse effektanvändningsmönster förnybar enlproduktion energilagring optimisering elanvändning framtida krav estimerat elbehov Energy Systems Energisystem Human Computer Interaction Information Systems
23	Peak shaving optimisation in school kitchens : A machine learning approach Alhoush, George, Edvardsson, Emil January 2022 (has links) With the increasing electrification of todays society the electrical grid is experiencing increasing pressure from demand. One factor that affects the stability of the grid are the time intervals at which power demand is at its highest which is referred to as peak demand. This project was conducted in order to reduce the peak demand through a process called peak shaving in order to relieve some of this pressure through the use of batteries and renewable energy. By doing so, the user of such systems could reduce the installation cost of their electrical infrastructure as well as the electrical billing. Peak shaving in this project was implemented using machine learning algorithms that predicted the daily power consumption in school kitchens with help of their food menus, which were then fed to an algorithm to steer a battery according to the results. All of these project findings are compared to another system installed by a company to decide whether the algorithm has the right accuracy and performance. The results of the simulations were promising as the algorithm was able to detect the vast majority of the peaks and perform peak shaving intelligently. Based on the graphs and values presented in this report, it can be concluded that the algorithm is ready to be implemented in the real world with the potential to contribute to a long-term sustainable electrical grid while saving money for the user. Peak shaving Machine learning Peak-shaving Battery optimisation Random Forest Gradient Boosting Peak demand Peak-demand Sustainable Electrification AI A.I Artificial intelligence Energy system Maskininlärning Utjämnings av effekttoppar Batterioptimering Hållbarhet Elektrifiering Artificiell intelligens Energisystem Energy Systems Energisystem Software Engineering Programvaruteknik Computer Sciences Datavetenskap (datalogi)

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