The need for optimizing wind farms’ production and maximizing the profitability of projects necessitates power performance analysis. Nowadays, the use of remote sensing devices for this purpose becomes more and more popular due to many advantages this technology has over traditional met masts. The main objective of this study is to assess the performance of a wind turbine in wake and wake-free conditions through measurements performed with a nacelle mounted lidar. The analysis is based on the data obtained during a Power Curve Measurement campaign performed on an onshore wind farm in Sweden. The power production and power curves are compared for a range of wind direction sectors in order to assess turbine performance in different wake conditions. Surprisingly low power output is observed in wake-free sectors [180°, 240°) and [240°, 300°), whereas production in wake wind directions [300°, 360°) is relatively high. The main reason for this is the wind speed distribution, however the terrain complexity and roughness should also be considered as possible factors. Generally, the wind speed distribution seems to have more influence on the results than the wake conditions. Moreover, the correlation between the met mast and lidar datasets is investigated in the study. The results indicate a good agreement between the wind speed measurement from the two devices, however, a poor correlation is found for turbulence intensity and wind shear exponent. Additionally, the influence of turbulence intensity and wind shear on the power production was analyzed. Generally, the results were in line with the reviewed literature: at low and moderate wind speeds the power production was higher for higher TI values, while the opposite was observed for higher wind speeds, where the higher TI resulted in lower production. As for the wind shear, a pattern is observed for moderate wind speeds, where the higher wind shear resulted in lower power production.

Transient analyses at Forsmark nuclear power plant are currently performed using realistic computer models in conjunction with conservative estimates of initial- and boundary conditions. This is known as the combined methodology. Due to the conservative estimates, the methodology runs the risk of sometimes over-estimating certain safety criteria which will negatively affect the optimization of reactor operation. The Best Estimate Plus Uncertainty (BEPU) methodology can provide higher safety margins by using probabilities instead of conservatisms when estimating initial and boundary conditions. The BEPU methodology applies a Monte Carlo method to assess the distribution of one or several key outputs. This study focuses on the lowest dryout margin achieved during each Monte Carlo simulation. The tolerance limits of the output are set with the help of Wilks formula using a one-sided 95% tolerance limit with 95% confidence. A total of 36 unique parameters describing initial and boundary conditions have been sampled for each Monte Carlo simulation. The parameters have been sampled using either Gaussian or Uniform distribution functions. The random nature of the Monte Carlo simulations has uncovered alternative event sequences and end states that are not seen in the combined methodology. Assessing the choice of order statistic in Wilks formula also concludes that there are diminishing returns the higher the order statistic is. When choosing the order statistic, one should consider the trade-off between an increased accuracy in the estimated outputs and the increased computational time required. The conservative methodology uses a mix of conservative and nominal estimations of key parameters. The difference in dryout margin between the conservative and the Monte Carlo results should therefore not be used to draw a conclusion about which methodology out-performs the other. While the Monte Carlo simulations do not result in an improved core optimization, they can act as a complement to the combined methodology by providing a more detailed analysis of possible event pathways for a postulated transient.

Urban areas house most of the global population and are also responsible for large shares of global greenhouse gas emissions. Cities and municipalities thus play a significant role in modern society to achieve an energy transition to renewable energy sources and to adapt to climate change. Achieving such a transition is a difficult process due to the high energy density and complexity of urban multi-energy systems. This is further exacerbated by the adverse effect future climate hazards will likely have on urban infrastructure. Despite this, energy development and climate adaptation plans are often researched and drafted in a disjointed manner. In many instances, future energy strategies do not consider climate impacts, whereas climate adaptation tactics disregard energy production. This study proposed that such mutually exclusive analysis and decision-making increases the vulnerability of planned and optimised future urban energy systems. Investigating the Swedish municipality Malmö, the study focused on achieving a future energy transition in its electricity network and then considering potential climate change impacts. Current urban energy plans and capacity were used to forecast the renewable energy potential for 2030 in Malmö’s geographical area. This formed the basis for modelling an optimised hybrid renewable energy system for the municipality using HOMER Grid. Based on future climate data and Malmö’s climate adaptation plans, this system was then evaluated in terms of impacts from climate hazards. The results indicated that Malmö’s current energy plans would expose a large share of their energy infrastructure to risk of damage from climate hazards. Thus, the vulnerability of the optimised energy system is indeed heightened when disregarding climate change impacts in the planning phase. If climate change and energy transition strategies are developed conjointly, urban energy system resilience could likely be increased significantly.

The world is progressing towards a more sustainable society, where renewable energy sources, including solar energy, play a crucial role. This study aims to address the conflict between agriculture and energy production by exploring the installation of solar panels on farmland. Four scenarios are considered, with varying parameters such as latitude, azimuth, slope, and row distance between photovoltaic (PV) modules. The study focuses on two different crops, lettuce and potato, which have varying tolerances to shading. The objective is to understand how the shadows cast by solar panels affect the growth of these crops. To analyze the impact of shading, the PVsyst software program is utilized to obtain PAR values for each scenario. The calculations are performed using Excel equations. The literature review encompasses scientific sources that provide insights into both PV technology and agriculture, bolstering the research findings. To ensure realism and manage simulation time, certain delimitations were made. These include limiting the study to two cities in Sweden, comparing only two crops, and conducting simulations during the summer period. The results reveal a significant potential for growing potatoes under PV modules. However, lettuce faces difficulties due to its high requirement for solar intensity (PAR), making it less adaptable to shade. The findings of this study indicate that crops like potatoes, which have a lower requirement for PAR, can be successfully cultivated in conjunction with photovoltaic (PV) systems. However, it is not advisable to implement AV systems in areas where sensitive crops like lettuce, which necessitate a significant number of sun hours with high solar intensity.

As the world becomes more focused on sustainability, there is increasing pressure on steel-bearing companies to improve their energy efficiency and reduce their carbon footprint. The heat treatment process accounts for about 25% of SKF's energy consumption, and it aims to achieve decarbonized operations by 2030 and the supply chain by 2050. Therefore, improving the energy efficiency of the heat treatment process can have significant economic and environmental benefits for the company. This thesis project aimed to conduct an energy mapping of different heat treatment processes at SKF to develop a methodology and standard key performance indicator for establishing energy performance and ensuring comparability between installations and processes. Three heat treatment processes were studied: through hardening, location A; case carburizing, location B; and surface induction hardening, location C. A detailed methodology and guidelines for carrying out energy mapping were developed. A standard key performance indicator known as Specific Energy consumption in kWh/kg at a particular utilization in % was set for comparisons among different heat treatment processes. Regression analysis was used to normalize the results. On the same utilization level, case carburizing, location B consumes more energy than through hardening, location A. Surface induction hardening, location C consumes 90% less than others and is less dependent on utilization. The carbon intensity in g CO2-eq/kg for greenhouse gas scopes 1, 2 and 3 were also studied. Case carburizing, location B had the highest climate impact due to the coal-based electricity mix of the country. Hence, the future availability of renewable electricity is critical when switching from gas to electricity across factories in SKF.

The Candy Factory area is located at Brynäs district, and its history is known as Gävle's most important industrial area in the 1870’s. The area is under construction and plans to tie Gävle Strand with Brynäs and make the area more attractive. In the Candy Factory area in Gävle there is a building, Läkerol building that is owned by AB Gavlegårdarna, and is a part the areas renovation process. It’s exterior must be preserved but must be made more energy efficient since the building is to be used as a residential building and other activities. It is part of a cultural environment, such as national interests. The retention of its characters is particularly important, making changes to the building more complex. The starting point for this study was to investigate the effects of energy efficiency methods and costs with a focus on windows in view of conservation needs of the Läkerol building. In the implementation, characteristics of the building have been assessed along with literature research, previous research, books studied in support of the work and energy balances and cost calculations for window changes have been made. The results for this study shows what is most profitable among different efficiency methods and how different building envelope components leak heat. The windows cause great thermal losses and cost savings can be reduced by choosing the efficiency measure window with extra glass with low investment cost compared to brand new windows.

Electric vehicles, which have both energy storage capability and mobility capability, can provide a new solution for electricity sharing between different building communities (i.e., a group of buildings connected with a microgrid). This comes to the community-to-community (C2C) energy sharing network. The C2C energy sharing networks have the potential to not only minimize the effects of electric vehicle integration into the energy grid, but also improve the electricity grid efficiency as a whole. In this thesis, a coordinated smart charging method of electric vehicles (EVs) is proposed for the C2C model. The proposed method considers the power regulation needs in both the present parking community and the next destination community. Then, based on the needs of both communities, the control method will decide the optimal amount of electricity that can be delivered by EV, so that the energy performances in both communities can be the best. The developed coordinated control has been compared with a base case (without any smart charging) and an uncoordinated control case under two control strategies: minimizing the peak energy exchanges with the grid and maximizing the renewable self-utilization. The genetic algorithm tools in MATLAB software are used for the optimization of the model. Meanwhile, to test the robustness of this C2C model, different combinations of building communities have been studied, namely residential-workplace, residential-university, and residential-workshop communities. The case study reveals that the C2C model is effective in improving energy performance under both control strategies. Peak reduction control strategies work most effectively for smaller systems with lower electricity demand and production. With C2C energy sharing, the annual mean peak reduction ranged from 39 % at the smallest community and 20 % at the largest community. Self-consumption maximization strategies work best for systems with a larger surplus of electricity production. With C2C energy sharing, the annual self-consumption increase ranged from 50 % at the community with the largest production surplus, to 7 % at the community with the smallest production surplus. The residential-workshop community studied in this thesis benefited the most from C2C charging control due to its production surplus and the relatively low electricity demands of the communities.

This master thesis examines the economical profitability of integrating a battery storage system with the commercial property Pyramiden 19. The model is developed in Matlab and analyses three different profitability strategies for utilizing the battery storage: peak shaving, time of use arbritage and the grid supporting service FCR-D up. The modeling of these scenarios involves numerous parameters, with uncertainties surrounding factors such as battery price and characteristics, electricity prices, and the actual activation of grid-supporting services. Results indicate that only minor savings can be modeled through the electricity contracts, leading to both peak shaving and time-of-use arbitrage generating additional costs than previously when factoring in battery investment expenses. Although peak shaving and time of use arbritage are innovating strategies to redistribute consumption with, they are not suitable to reduce costs with all types of electricity contracts and cannot cover largely added investment costs. Looking at the third strategy, the flexibility market appears to hold a significant potential for economical profitability. The model shows that the grid supporting service FCR-D up, with a 2000 kW battery, reduces the initial annual electricity costs by 36%. This can mainly be explained by the fact that, in the model, the battery is activated for only 2% of the total hours in a year, and the fact that the service is compensated based on called bids rather than activated bids. Connection to the balance market would therefore not only generate revenues for the property but would also result in relief for the local electricity grid. Due to the uncertain future regarding compensation levels in the flexibility market, an early connection is recommended to ensure timely reimbursement for the battery.

Introduction: The global demand for renewable energy is expected to grow annually due to rising electricity consumption and economic and regulatory incentives. Efficient consumption and management of electricity consumption can support this trend (shifting from fossil resources to renewable resources) and benefit companies economically by reducing peak loads, reducing subscription costs, and protecting companies' power systems and networks. For effective and efficient electricity management that can help reduce peak electricity demand, resulting in lower demand charges and further reducing operational costs, it is necessary to understand the amount of electricity consumption and its influencing factors. Seasonal and daily variations and social behaviors influence changes in electricity consumption. Electric load variation management is essential for electricity consumers to control costs related to maximum load capacity and building electrical network equipment protection. This research presents an assessment method for describing daily electric load variations. It is applied to electricity consumption systems, but the technique is generic and can be applied to all activities where daily variations occur.Purpose: This thesis aims to show when and why peak load occurs in an office building and also to provide methods to improve the efficiency of electricity consumption during peak load.Method: This method implemented parameters like temperature, electricity consumption, and hours. It assessed a year's hourly electricity consumption in an office building to understand how load changes daily, weekly, and monthly. The case study was the AirSon office building. Data-driven from the efergy online portal was based on the hourly consumption every year.Results: The results show that the outdoor temperature, working hours, and consumption behavior can affect the overall electricity consumption and peak loads. Efficient building strategies are crucial for reducing peak loads by smartly controlling indoor temperature and managing electricity demand. The analysis offers insights into office building electricity consumption patterns and recommends strategies such as prioritizing car charging, optimizing the heat pump's operation of the HVAC system, improving the electricity management system, and using energy storage systems to reduce peak load.Discussion: The findings from this analysis carry implications for electricity consumption. It can provide some insights for reducing electricity consumption and enhancing efficiency in office buildings and similar facilities and also prioritization and rescheduling car chargers. In conclusion, it has interpreted and discussed the various electricity-saving strategies and their potential impact on electricity management.

Energianvändningen i världen växer för varje år, vilket i sin tur bidrar med ökade mängder utsläpp av växthusgaser till atmosfären. På grund av den ökade energianvändningen blir intresset för energisnåla byggnader allt högre med tiden. I detta projekt har en nordligt placerad fastighet med en Atemp på 716 m2 i Gnarp simulerats med hjälp av IDA Indoor Climate and Energy (IDA ICE) samt WINSUN. Fastigheten har två våningar med åtta lägenheter totalt och är uppvärmd med bergvärme då fjärrvärmenätet ligger för långt ifrån området. Tanken med byggnaden är att den ska uppnå kriterierna för ett plusenergihus, vilket innebär att fastigheten ska generera mer energi än vad den gör av med via en solcellsanläggning som monteras på taket. Enligt de teoretiska resultat som simuleringen visar så kan fastigheten klassas som ett plusenergihus, då solcellsanläggningen på taket producerar mer energi än vad som används årligen. Det innebär att möjligheterna för byggnation av ett plusenergihus i nordligare områden i Sverige finns, där temperaturer varierar kraftigt under årets gång och kan gå lägre än -30°C under vintertid. Den årliga elproduktionen ligger över 26 700 kWh/år och elanvändningen hamnar på 16 400 kWh/år, där tappvarmvattnet står för den största delen använt el. Det innebär att den genererar ungefär 10 300 kWh/år i överskott relativt till inköpt el-energi. Huset är välisolerat och har smart placerade glasytor för värmeinsläpp. Det inkluderar en effektiv värmepump, ett FTX-System för värmeåtervinning via ventilationssystemet samt ett solcellssystem på taket som i sin tur bidrar till möjligheten för en energiproducering som är högre än energianvändningen, därav en plusenergihus-klassning. Under energianvändningsprocessen så har den årliga uppvärmningen, tappvarmvattnet samt fastighetselen tagits till godo i beräkningarna för bedömning av byggnadens energiprestanda. Eftersom solcellerna producerar mer energi under sommaren, vilket medföljer att överskott på elproduktionen uppstår under vissa perioder av året, så innebär det att el kan säljas via elnätet till en elhandlare. / The interest in low-energy-houses has risen in recent years as the energy usage around the globe is constantly increasing, resulting in ever-increasing amounts of greenhouse gases in the atmosphere. In this project, the energy consumption of a building in a northern area of Sweden, Gnarp, with an Atemp of 716m2 was simulated using IDA indoor Climate and Energy (IDA ICE) and WINSUN. The building has two floors and is comprised of eight apartments. It is heated using geothermal heating since it is not located close enough to a district heating area. The goal of the simulation was to determine if this building is an energy-plus-house, whereby a PV-system mounted on the rooftop allows for the energy production-value of the building to be higher than the energy-usage. The theoretical results of the simulation show that this building is indeed an energy-plus-house since the PV-system is generating more energy than the yearly usage of the building. This simulation shows that it is possible to build an energy-plus-house in northern areas of Sweden where temperatures are highly variable and can go below -30°C during winter season. It indicates a yearly electricity-production of over 26 700 kWh/year and a usage of approximately 16 400 kWh/year, where the domestic hot water accounts for the highest usage of electricity. This means that the building generates an electricity surplus of approximately 10 300 kWh/year. The building is well isolated and has well placed windows for heat generation via the sun. It includes an effective heat pump, an FTX-system, and solar panels on the roof which gives the opportunity for an energy-production that is larger than the energy-usage, which in turn gives the opportunity for an energy-plus-house classification. The heating, domestic hot water, and the building electricity were all considered when calculating the estimation of the energy-quality of the property. The PV-system generates more energy during the summer, which results in an overproduction of electricity at certain times of the year. The extra electricity produced can be sold to the electric utility.