The world is right now in a global transition from a fossil fuel dependency towards an electrified society based on green and renewable energy. Investments in power grid capacity are therefore needed to meet the increased future demand which this transition implicates. One part of this is the expansion of intermittent energy sources, such as wind and solar power. Even though these sources have benefits in form of cheap and green energy, they have other characteristics that need to be addressed. Per definition, intermittent power sources cannot produce energy on demand since they are dependent on weather conditions such as wind and sun. This induces a second problem which is that it can be hard to predict the production from intermittent power sources, especially wind, which increases the volatility in the power market. Because of these characteristics, the expansion of wind power has increased the volume traded on the intraday power market. The intermittent energy surge, emphasizes the need of a good trading strategy for balance responsible parties to handle the increased trading volume and volatility. The prupose of this report is to introduce the elements which affect intraday power trading, formulate the fundamentals of a power trading strategy and thereafter explore how predictive models can be used in such a strategy. This includes predicting regulating and intraday market prices using linear regression models, neural networks and LSTM-models. Furthermore, the report highlights underlying properties which affects the predictive power of a prediction model used to forecast wind power production. Regulating prices can be predicted well using both linear regression models and more complex deep learning models based on weather and market data. Both approaches are better than using a simple model based on the latest regulating and market price, since the simple model tends to fall short in a volatile market. Overall, the deep learning models performs the best.  The difference in result when predicting the volume weighted average price on the intraday market, using linear regression and machine learning, are not as substantial. In fact, the linear models tends to outperform the machine learning models in some instaces. The conclusion when analyzing how underlying properties affect wind power prediction models is that how far ahead the model predicts is not the key factor affecting predictive power. Instead, the production volume predicted has a larger effect.

Sverige och Europa genomgår en omställning till högre andel förnybar el, samtidigt har Europas elpriser varit rekordhöga de senaste åren och den sammankopplade elhandeln i EU har bidragit till höga elpriser i Sverige. Litteraturstudien har avsett att redogöra för hur strategier som begränsar elhandeln mellan Sverige och EU påverkar Sveriges försörjningstrygghet, elpriser och konkurrenskraft samt hur miljön påverkas av dessa strategier. Studien kartlägger elhandeln i Sverige och Europa, både den fysiska och marknadsmässiga samt de legala faktorer som påverkar den. Balansen mellan försörjningstrygghet, miljö, ekonomiska faktorer och internationell elhandel undersöks. Dessutom introduceras några strategier för att begränsa och kontrollera den internationella elhandeln, de främsta var fysisk begränsning av elöverföringen samt olika prissättningsstrategier. Resultaten visar att en fysisk begränsning av gränsöverskridande elhandel inte är möjlig givet de regelverk som finns på plats men skulle drabba försörjningstryggheten samt medföra osäkerheter på lång sikt i ekonomiska faktorer som konkurrenskraft och elpriser i Sverige. Dessutom skulle en fysisk begränsning försvåra övergången till mer förnybar energi i Sverige och Europa och på så vis påverka miljön negativt. Det framstår därför som mer gynnsamt på kort sikt att istället kontrollera elhandeln med olika prissättningsstrategier såsom lägre priser för inhemska konsumenter, för att på så sätt dra nytta av inkomsterna och miljönyttan som internationell elhandel innebär utan att de nationella elpriserna drabbas i samma utsträckning. Beroende på prissättningsstrategi innebär det att den negativa påverkan på antingen hushållens eller industriernas elpriser reduceras, varav framför allt det senare innebär att konkurrenskraften inte påverkas lika negativt. Dock visar studien att en sådan modell kräver ytterligare forskning för att utvärdera dess genomförbarhet och potentiella effekter. Slutsatsen av studien indikerar att både bibehålla den nuvarande situationen och implementera alternativa strategier medför olika för- och nackdelar avseende försörjningstrygghet, elpriser, den svenska industrins konkurrenskraft och miljöpåverkan. För att identifiera den mest optimala strategin krävs ytterligare forskning samt en noggrann avvägning av de potentiella konsekvenserna. / Sweden and Europe are increasingly shifting towards renewable electricity. However, Europe has recently seen record-high electricity prices, with the interconnected electricity trade within EU contributing to high prices in Sweden. This literature review aims to elucidate the impacts of strategies restricting electricity trade between Sweden and the EU on Sweden’s energy security, electricity prices, competitiveness, and the environment. The study maps the physical and market dynamics of electricity trade in Sweden and Europe and examines the legal factors influencing it. It also explores the balance between energy security, environmental considerations, economic factors, and international electricity trade. Various strategies for limiting and controlling international electricity trade are introduced, focusing on physical restrictions on electricity transmission and different pricing strategies. The findings suggest that physically restricting cross-border electricity trade is not feasible under current regulations and would harm energy security, leading to long-term uncertainties in economic factors such as competitiveness and electricity prices in Sweden. Additionally, such restrictions would impede the transition to renewable energy in Sweden and Europe, adversely affecting the environment. Therefore, controlling electricity trade through various pricing strategies, such as lower prices for domestic consumers, seems more advantageous in the short run. This approach allows for leveraging the economic and environmental benefits of international electricity trade without significantly impacting national electricity prices. Depending on the pricing strategy, the negative impact on either household or industrial electricity prices is mitigated, with the latter primarily ensuring competitiveness remains less affected. However, further research is needed to evaluate the feasibility and potential effects of this model. The study concludes that both maintaining the current situation and implementing alternative strategies entail various advantages and disadvantages concerning energy security, electricity prices, the competitiveness of Swedish industry, and environmental impact. To identify the most optimal strategy, further research and a careful assessment of the potential consequences are required.