The goal of achieving carbon neutrality for year 2045 puts Sweden on a road towards further implementation of renewable energy into their energy system. The goal of this degree project is to investigate how the implementation of renewable energy in Sweden is worked towards on a regional level but also to explore how this expansion might look for the Norra Småland Region. By conducting several semi-structured interviews with the energy agencies of Sweden as well as creating a model for the potential solar and wind power expansion in the Norra Småland Region, the authors aim to answer the questions of how the current work with expanding the renewable energy share in the Swedish energy system is conducted; what bottlenecks, problems and challenges exist and what tools, data, information and incentives might help further facilitate this work. Through the interviews conducted, this degree project encapsulates the different projects related to the subject of renewable energy which the various regions of Sweden work with. The degree project also provides a compilation of various challenges related to the projects as well as an insight into what tools and incentives are asked for by the regions with the goal of helping facilitate the work conducted. The degree project also provides a projection for how the future expansion of wind power and solar power might look in the Norra Småland Region based on the previous expansion trends, resulting in three individual projections with individual growth rates.

World energy systems are going through a continuous change. The focus has been shifted from large thermal or hydal power generation to small distributed generation, mainly based upon renewable energy systems. This transition is also backed by some governments. There have also been significant improvements in grid technology, and modern-day smart grid can provide real time bi-directional flow of data i.e. “real time energy deficit and surplus, and also real time prices to both producers and consumers. Smart grid can also accommodate intermittent small suppliers of electricity. This shift in energy generation policy and improvement in grid technology has opened ways for small scale energy producers and consumers to share energy with each other. It has also opened ways to purchase or sale energy to unknown peers over a smart grid. Need has been felt to store these transactions among peers in a secure, non-alterable yet quickly accessible way. Blockchain technology offers to provide this secure, unalterable yet quickly accessible ledger. In this study this transition process and role of blockchain technology for future energy systems has been historically reviewed. It has been found out that on top of keeping record of Peer to Peer transactions, blockchain technology can fill many other purposes. However, technology is still not matured for large scale projects, Research projects are underway to decrease the large time and energy consumption for block building computational processes yet keeping them safe and reliable.

Introducing more intermittent renewable energy sources in the energy system makes the role of balancing power more important. Furthermore, an increased infeed from intermittent renewable energy sources also has the effect of creating lower and more volatile electricity prices. Hence, investing in balancing power is prone to high risks with respect to expected profits, which is why a good representation of electricity prices is vital in order to motivate future investments. We propose a stochastic multi-factor model to be used for simulating the long-run dynamics of electricity prices as input to investment valuation of power generation assets. In particular, the proposed model is used to assess the impact of electricity price dynamics on investment decisions with respect to balancing power generation, where a combined heat and power plant is studied in detail. Since the main goal of the framework is to create a long-term representation of electricity prices so that the distributional characteristics of electricity prices are maintained, commonly cited as seasonality, mean reversion and spikes, the model is evaluated in terms of yearly duration which describes the distribution of electricity prices over time. The core aspects of the framework are derived from the mean-reverting Pilipovic model of commodity prices, but where we extend the assumptions in a multi-factor framework by adding a functional link to the supply- and demand for power as well as outdoor temperature. On average, using the proposed model as a way to represent future prices yields a maximum 9 percent overand underprediction of duration respectively, a result far better than those obtained by simpler models such as a seasonal profile or mean estimates which do not incorporate the full characteristics of electricity prices. Using the different aspects of the model, we show that variations of electricity prices have a large impact on the investment decision with respect to balancing power. The realized value of the flexibility to produce electricity in a combined heat and power plant is calculated, which yields a valuation close to historical realized values. Compared with simpler models, this is a significant improvement. Finally, we show that by including characteristics such as non-constant volatility and spiky behavior in investment decisions, the expected value of balancing power generators, such as combined heat and power plants, increases. / I takt med att fler intermittenta förnyelsebara energikällor tillför el i dagens energisystem, blir också balanskraftens roll i dessa system allt viktigare. Vidare så har en ökning av andelen intermittenta förnyelsebara energikällor även effekten att de bidrar till lägre men också mer volatila elpriser. Därmed är även investeringar i balanskraft kopplade till stora risker med avseende på förväntade vinster, vilket gör att en god representation av elpriser är central vid investeringsbeslut. Vi föreslår en stokastisk flerfaktormodell för att simulera den långsiktiga dynamiken i elpriser som bas för värdering av generatortillgångar. Mer specifikt används modellen till att utvärdera effekten av elprisers dynamik på investeringsbeslut med avseende på balanskraft, där ett kraftvärmeverk studeras i detalj. Eftersom huvudmålet med ramverket är att skapa en långsiktig representation av elpriser så att deras fördelningsmässiga karakteristika bevaras, vilket i litteraturen citeras som regression mot medelvärde, säsongsvariationer, hög volatilitet och spikar, så utvärderas modellen i termer av årlig prisvaraktighet som beskriver fördelningen av elpriser över tid. Kärnan i ramverket utgår från Pilipovic-modellen av råvarupriser, men där vi utvecklar antaganden i ett flerfaktorramverk genom att lägga till en länkfunktion till tillgång- och efterfrågan på el samt utomhustemperatur. Vid användande av modellen som ett sätt att representera framtida priser, fås en maximal över- och underprediktion av prisvaraktighet om 9 procent, ett resultat som är bättre än det som ges av enklare modellering såsom säsongsprofiler eller enkla medelvärdesestimat som inte tar hänsyn till elprisernas fulla karakteristika. Till sist visar vi med modellens olika komponenter att variationer i elpriser, och därmed antaganden som används i långsiktig modellering, har stor betydelse med avseende på investeringsbeslut i balanskraft. Det realiserade värdet av flexibiliteten att producera el för ett kraftvärmeverk beräknas, vilket ger en värdering nära faktiska realiserade värden baserade på historiska priser och som enklare modeller inte kan konkurrera med. Slutligen visar detta också att inkluderandet av icke-konstant volatilitet och spikkarakteristika i investeringsbeslut ger ett högre förväntat värde av tillgångar som kan producera balanskraft, såsom kraftvärmeverk.