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Balancing Contributions in the Nordic Electricity System : Who bears the brunt of electricity production and consumption patterns?Overmaat, Eduard January 2019 (has links)
The share of intermittent weather-based renewable electricity sources has risen and will keep on rising in the Nordic electricity system, which will increase the need of balancing power in the Nordics. The previously developed concept of balancing contributions is used to look at the historic contribution of different power sources to the balancing on the grid. Three different time scales are taken into account: Daily variations, (bi-)weekly variations, and seasonal/yearly variations. This will aid in the understanding of the synergy of different sources on the grid, which, together with a deeper knowledge of the electricity market, might make it possible in the future to quantify the potential for balancing of sources within the Nordic grid. As a method to analyse the balancing contributions, a previously set-up online visualisation tool was used as an example, and this existing tool was revamped with a new software back-end using a database and automatic data collection. This allows one to be able to use a larger dataset, and for more functionality in the future, such as real-time updates and easier implementation of additional visualisations. Production and consumption data was gathered from Entso-e and SvK: the former has issues with data quality and the latter publishes data with a three-week delay which can only be obtained manually. The results from the previous research have been replicated, and a bigger dataset has been used to do the calculations, encompassing the years 2015-2018. The overall results show great similarity to that of the previous work. For the first time it was possible to plot the intrayear balancing contributions as a time series, which showed especially that the contributions of hydro power and electricity trade have changed over the period 2015-2018. There is a difference in hydro power balancing contributions based on geographical location, where Finnish hydro power is mainly a daily and—to a lesser extent—weekly regulator, Swedish hydro and especially Norwegian hydro have larger contributions on a yearly basis as well. There are even differences within countries, as the balancing contribution of hydro in bidding area SE2 has changed much more over time than hydro in SE1, for example. Other examples of interesting situations on the grid have also been highlighted using the online visualisation tool.
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How closely does electricity production follow price signals?Sa Cunha, Théo January 2021 (has links)
This thesis investigates the relation between the day-ahead electricity market prices and the electricity production in the Nordic synchronous area of the European electric power system by looking into the market data ranging from 2015 to the current time. The increasing penetration of variable renewable energy sources, coupled with the deeper electrification in various sectors of the economy, has led to a higher volatility in the market, e.g. in the market prices. Since all power plant owners plan their production depending on prices, price forecasts, availability, it is necessary to better understand the relation between price signals and the production variations. Firstly, balancing contributions, considered as a suitable tool, are found unfit to apply to this research. Secondly, spectral analysis is used to highlight frequencies in the signals, leading to the determination of three time scales of variations: daily, two-weekly and yearly. It is used to define three timehorizons which are used to apply different mathematical tools on the market data. Thirdly, the correlation coefficient between a type of production and the day-ahead prices assesses the linearity of their respective variations. Lastly, the relative market value of the production gives insight into the , e.g. with regard to flexibility. Results of this research show that the correlation between the day-ahead prices and the production depends on the time-horizon, the production type, as well as the area. E.g., if SE2’s and SE1’s hydro production are highly correlated to prices in the daily and two-weekly patterns, the former has not enough storage to follow prices on the yearly horizon, while the latter can, due to its bigger reservoirs. Results also show that wind power is one of the drivers of the day-ahead prices, especially in the two-weekly time horizon. The increasing share of wind power will hence lead in more price variations as well as lower average price levels.. This study aims to provide insights to the plant owners with flexibility possibility on how to face those future challenges. / Detta examensarbete undersöker sambandet mellan day-ahead-priser på elmarknaden och elproduktion i den nordiska synkrona delen av det europeiska elsystemet. Analysen bygger på data mellan 2015 och maj 2021. I och med att andelen väderberoende förnybara energikällor ökar samtidigt som olika sektorer elektrifieras har elmarknaden och elpriserna blivit mer volatila. Den volatiliteten behöver elproducenter förhålla sig till när de planerar sin produktion beroende på elpriser, elprisprognoser, tillgänglighet m.m. och därför är det avgörande att belysa förhållandet mellan prissignaler och anpassning av produktionsnivåer. Arbetet inkluderar olika steg: Först undersöktes balansbidrag och det kunde visas att detta mått inte lämpar sig för att beskriva sambandet mellan produktion och elpriser. Sedan gjordes en spektralanalys för att identifiera de grundläggande variationerna: dygns-, tvåveckors- och årsvariationer. Baserad på dem specificerades tre tidshorisonter som olika matematiska mått utvärderas på. Ett sådant mått är korrelationskoefficienter som användes för att beskriva sambandet mellan produktionsdata per kraftslag och elpriser på ett linjärt sätt. Slutligen användes relativa marknadsvärden på samma sätt för att kunna undersöka olika kraftslags karakteristik och få inblick i deras flexibilitet samt körsättet. Resultaten visar att korrelationen mellan day-ahead-priser och produktion beror påtidshorisonten, kraftslag och prisområde. Till exempel är vattenkraften i norra Sverige (SE1 och SE2) starkt korrelerad med elpriserna på dyngs- och tvåveckorsnivå medan korrelationen på årsnivå är starkare för SE1 eftersom vattenmagasin i SE1 har större reglerutrymme på den långa tidshorisonten än magasinen i SE2. Resultaten visar dessutom att vindkraften är den drivande faktorn för elprisvariationerna, särskilt när det gäller tvåveckorshorisonten. Vindkraften kommer öka prisvariationerna och samtidigt sänka prisnivån. Målet med examensarbetet är att få mer inblick i kraftslagens flexibilitet och därmed öka förståelsen för framtida utmaningar.
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