This master thesis examines if a battery energy storage installed in an apartment building with PV production can be a profitable investment and how it should be used. By modelling different types of applications such as peak shaving, increasing self-consumption and primary frequency reserves, the most profitable application for the battery storage can be found. There are a lot of parameters to take into consideration when modelling a battery delivering flexibility services to the grid. Parameters linked to batteries, electricity contracts, household load, PV-production and different primary frequency reserves had to be taken into consideration when modelling. The result shows that scenario 2.6 (FCR-D (↑) + FCR-D (↓) + FFR + FCR-N) generated the highest net income of 313 629 SEK annually. The most profitable scenario over a 10-year period was scenario 2.1 (FFR) with an income of 12 529 SEK per installed kWh. This is because the frequency reserve was only active during the summer months, therefore it fits well as a combination with PV production. FFR also paid the most per average delivered energy [SEK/kWh] and did not need as high battery capacity as scenario 2.6. Another advantage with scenario 2.1 was that it did not create as high power peaks as the other primary frequency reserves did, which can affect the electricity contract of the building. With today’s wide market of different primary frequency reserves, the possibilities increase. Other applications than a battery storage can be used to deliver different primary frequency services to the electricity grid.

In 2022, Sweden faced significant challenges in its energy landscape due to a combination of factors, including Russia's invasion of Ukraine, domestic disruptions in nuclear power production, low water reservoir levels, and the increasing reliance on intermittent energy sources. Consequently, the price of electricity in Sweden soared to unprecedented levels. According to the Swedish national bank, the high energy prices were a major contributor to the country's inflation woes during that period. To address this issue, the national bank highlighted the potential of electricity consumers in reducing electricity costs and mitigating inflation by adjusting or shifting their energy usage away from peak hours. This study focuses on exploring the utilization of demand side flexibility as a means for consumers to control their electricity consumption. Specifically, it aims to investigate the effectiveness of demand side flexibility in reducing energy costs within office buildings based on energy prices from 2022. The building is assumed to have heating system consisting of a heat pump for base heat and district heating for supplementery heating. Three demand side flexibility scenarios were analyzed: 1) Adjusting the heating setpoint to a lower temperature during periods of high energy prices, 2) Switching between heat pumps and district heating based on the production cost of 1 kWh, and 3) Utilizing heat storage to minimize energy consumption during peak hours. Through an examination of the outcomes of these strategies, this research aims to enhance our understanding of how demand side flexibility can optimize energy usage and minimize costs in office buildings. Additionally, the report will analyze the impact of demand side management actions on the overall energy performance of the buildings. The building's energy consumption for heating purposes was simulated using IDA ICE to assess its annual energy usage patterns. Moreover, models were developed in IDA ICE and Excel. The results of the study demonstrate that all investigated scenarios reduces the energy cost. The combination between measure (1) and (2) is the best alternative for minimizing energy cost. This case could reduce the yearly energy cost by 28,7% which over 15 years accumulate to savings of 360000 SEK. Furthermore, measures (2) and (3) resulted in a 20% increase in energy consumption, primarily due to the higher utilization of district heating. Measure (1) has no impact on the energy consumption.

The shift towards renewable energy sources for electric production implies the need for more demand side flexibility in the use of electricity. In recent years, the spot price of electricity on the NordPool market has started to fluctuate more rapidly and with a greater magnitude than ever seen before. A key factor to this is the changes in production capabilities of cheap renewable energy due to weather changes. A second factor is that the Nordic transmission system is facing challenges in transmitting enough energy from areas with excess electricity production to areas with a shortage on electric energy. Thirdly, Russia launched an illegal invasion on the sovereign state of Ukraine in the early spring of 2022 leading to shortages on fossil fuels which are crucial for electricity production all around Europe. The new market conditions increase the economic incentives to utilize demand side flexibility as a method to decrease the operational energy costs for both small- and large-scale consumers. In this study, the opportunities of utilizing a battery storage system to minimize the cost of electricity by the implementation of Model Predictive Control (MPC) are investigated. The study consists of a case study that simulates how the power flow between the grid, a battery and a building can be optimized by MPC, as well as time scheduled operation. Different control strategies were implemented to include the different market structures that affect the limitations of the system. The simulation model for the system was constructed in MATLAB and utilized its system identification toolbox as well as its mixed integer linear programing capabilities. The results showed that by shifting the power demand by less than 9%, a 13% reduction of the cost for bought electricity can be obtained compared to the same system without an energy storage system. It was also shown that the MPC was able achieve over 40% higher economic savings compared to the time scheduled control structure. The study also propose that similar control strategies can be utilized for different energy storage systems.

With an ever growing demand for electricity, it is tough to know which challenges will be the most pressing and which solutions will be appropriate to implement in different cases. This thesis utilizes simulations of three low voltage grids to see which part of the grid is most vulnerable, to which extent grid reinforcement is needed to solve voltage and load problems, and what amount of demand flexibility services would be an adequate substitute to grid reinforcement. The three grids consists of a meshed grid in a suburban area, a radial grid in the city and a radial grid in the countryside. The grids are subjected to full penetration of electric vehicle chargers in a winter setting and full solar power penetration in a summer setting. The results indicate that the transformer is overloaded in both residential grids, although even more so in the meshed grid as opposed to radial grid wherein the cables are most overloaded. The countryside grid had some voltage problems in the summer, but were overall not affected notably. The conclusions were that the increase in electric vehicle chargers will be the most impending challenge and that grid reinforcement will be necessary in the long run but that demand flexibility services are a viable option in the meantime. The transformer would also need an upgrade in both residential grids.

Today’s society already requires a great connectivity network. This need will only increase in the future, and EDGE data centres are concepts meeting this future need, where the computational power is deployed close to the end user. They are defined, in this thesis, as a concept including different nodes, or data centres, located in proximity connected and participating in the market as one entity. The electricity grid in the Nordics is also a complex system. Many types of interactions with the grid exist and depend on the type of stakeholder. One collection of such interactions is ancillary services, which refer to different types of measures that maintain a reliable grid and electricity system. Electricity consumers within the grid network have the potential to interact and participate in these different functions. In this thesis, the participation of data centres, or EDGE data centres in ancillary services market, is studied. This thesis modelled different scenarios of an EDGE data centre with the grid network. Scenario 1 looked into self-consumption; scenario 2 looked into spot trading; scenario 3 looked into the FCR-N market; scenario 4 looked into the FCR-D markets; and scenario 5 looked into the combination of self-consumption and the FCR-D markets. It is observed from the results that scenario 4 generated the most favourable economic benefits. The results in relation to the price areas (zones in Sweden) were varied for the results. The price area SE4 gave better results for scenarios 1, 2, and 5 as compared to others. The best price area for scenarios 3 and 4 was from the SE1 zone. It is observed from the results that the potential benefit of the different ancillary markets exist and are at times favourable. Hence, there lies a future potential for the participation of EDGE networks in the electricity market thereby generating benefits for the data centres as well as stability for the grid. / Dagens samhälle kräver redan ett bra nätverk för uppkoppling. Detta behov kommer bara att öka i framtiden, och EDGE:s datacenter är koncept som uppfyller detta framtida behov, där datakraften placeras nära slutanvändaren. De definieras i denna avhandling som ett koncept som omfattar olika noder, eller servrar, som är placerade i närheten av varandra och som deltar på marknaden som en enhet. Elnätet i Norden är också ett komplext system. Det finns många olika typer av interaktioner med elnätet som beror på vilken typ av aktör det är fråga om. En samling av sådana interaktioner är stödtjänster, som avser olika typer av åtgärder som upprätthåller ett tillförlitligt nät och elsystem. Elkonsumenter inom elnätet har möjlighet att interagera och delta i dessa olika funktioner. I den här avhandlingen undersöks datacentraler, eller EDGE-datacenter, som deltar. I denna avhandling har olika scenarier för EDGE-datacenter modellerats i förhållande till elnätet. I scenario 1 undersöktes självkonsumtion, i scenario 2 spothandel, i scenario 3 FCR-N-marknaden, i scenario 4 FCR-D-marknader och i scenario 5 en kombination av självkonsumtion och FCR-D-marknader. I korthet gav scenario 4 de mest gynnsamma ekonomiska fördelarna. De potentiella miljöfördelarna diskuteras och kan inte lika lätt kvantifieras. Resultaten i förhållande till prisområdena varierade för resultaten. Prisområde SE4 gav de bästa resultaten för scenario 1 och 2 samt 5. Det bästa prisområdet för scenario 3 och 4 var SE1. Det framgår tydligt av denna avhandling att de potentiella fördelarna med de olika stödmarknaderna finns och att de vid vissa tillfällen är mycket gynnsamma med tanke på de höga lagringskostnaderna. EDGE-nätverkens framtida potentiella deltagande ger positiva resultat i både ekonomiska och miljömässiga termer.

The electricity grids have become a key player in the society. An increased usage of electricity is both a result from the more electrified society, but also as a main solver in reaching the climate goals by reducing emissions. This thesis work explores some of the new features for the electricity grid from integration of electrification from renewable energy resources (RES) and from strategies for energy optimization related to the loads and specifically from thermal heat pumps. These strategies lie in the field of demand response, which takes advantage of the flexibility of loads in terms of willingness to switch or decrease their consumption at a particular moment of the day. This research proposes a three-step framework to harness the flexibility of Thermo-Statically controlled loads (TCLs) based on a simulated grey-box building model that uses historical outside temperature and prices data and learns the thermal parameters such as Thermal Resistance, Thermal Capacitance, but also price responsiveness (pth ) through a Differential Evolution (DE) based optimization algorithm. The price responsiveness is used to provide further insight into the flexibility of the loads and is employed in the last step to propose a price policy estimation algorithm also based on DE that minimizes the gap between supply and demand while preserving supplier and customer profitability. The proposed approach has proven to be accurate for a large number of parameters but also effective with reduced training data (prediction errors around 2.5% on the power average and standard deviation), as well as to be successful in providing a Day-Ahead Real-Time Price policy that maximizes supplier and customer utility. The price policy provides a lower total price for the customer compared with a tariff without demand response (reduction up to 53.63 %), reduces the gap between RES-based energy sources and heating demand, and respects grid technical constraints. / Elnätet har blivit en nyckelaktör i samhället. En ökad elanvändning är både ett resultat av det mer elektrifierade samhället, men också som en huvudlösare för att nå klimatmålen genom att minska utsläpp. Detta examensarbete undersöker några av de nya funktionerna för elnätet från integration av elektrifiering från förnybara energiresurser (RES) och från strategier för energioptimering relaterade till ellaster och specifikt från termiska värmepumpar. Dessa strategier ligger inom området för efterfrågerespons, som drar fördel av lasternas flexibilitet när det gäller viljan att byta eller minska sin konsumtion vid en viss tidpunkt på dagen. Den här forskningen föreslår ett ramverk i tre steg för att utnyttja flexibiliteten hos termostatiskt kontrollerade laster (TCL) baserat på en simulerad gråbox-byggnadsmodell som använder historisk utomhustemperatur och prisdata och lär sig de termiska parametrarna som termisk motstånd, termisk kapacitans , men också priskänslighet (pth) genom en Differential Evolution (DE) baserad optimeringsalgoritm. Priskänsligheten används för att ge ytterligare insikt om lasternas flexibilitet och används i det sista steget för att föreslå en prispolitisk uppskattningsalgoritm också baserad på DE som minimerar klyftan mellan utbud och efterfrågan samtidigt som leverantörs- och kundlönsamheten bevaras. Det föreslagna tillvägagångssättet har visat sig vara korrekt för ett stort antal parametrar men också effektivt med reducerad träningsdata (förutsägelsefel runt 2,5% på effektmedelvärde och standardavvikelse), samt vara framgångsrik i att tillhandahålla en Day-Ahead Real -Tidsprispolicy som maximerar leverantörs- och kundnyttan. Prispolicyn ger ett lägre totalpris för kunden jämfört med en tariff utan efterfrågerespons (reduktion upp till 53, 63 %), minskar gapet mellan RES-baserade energikällor och värmebehov samt följer nättekniska begränsningar.