This report seeks to evaluate the flexibility in a number of Fortum’s hydropower stations. The deregulation of the Nordic electricity market has put an emphasis on revenue maximizing rather than cost minimizing and there are good indications that flexible assets will be even more valuable in the future when more wind power has been introduced into the system. Through interviews with people involved in the hydropower planning and operation process a number of factors with the potential of affecting the flexibility or causing deviations between planned and realized operation have been identified and explained. These interviews have also been used to identify main flexibility limitations in studied stations, and what potentially could be done to improve the flexibility. A data analysis has been performed where historical data from planned and realized operation and results from a model developed in Matlab has been studied. The developed linear programming model is used as a reference level of an idealized theoretical potential for flexibility. Volume weighted average prices have been used to measure and compare the flexibility of studied stations. The analysis shows that the studied stations can be divided into two groups with regards to their flexibility compared to the modeled flexibility. This result is somewhat confirmed by the interview findings. Factors related to constraints imposed by water rights seem to have the biggest single impact on the flexibility of hydropower stations. The potential for flexible operation varies with season and the planned and realized operation is closer to the modeled results during the winter. It is a general opinion within the organization that there is a potential for a more flexible utilization of many hydropower stations. Experience, resources, understanding in how to fully utilize the reservoirs, and how multiple stations in a river reach can be coordinated are keys to improving the flexibility.

In the present electrical market there is an increasing penetration of intermittent energy sources. Several studies have examined its effect on the planning of hydropower operation and the conclusion is that an increasing intermittent production is likely to result in a more variable hydropower operation, utilising a wider span of operational set points. The wear of a hydropower unit is generally at a minimum when operated close to best efficiency and increases when operating at higher or lower set points. This study introduces a method to calculate an operation dependent cost (ODC) function for an arbitrary hydropower unit or unit combination based on vibration measurements and operational data. The method is tested in a case study where an ODC is implemented in Akkats, located in the Small Lule River in order to evaluate its effect on operational pattern, profitability and balancing contribution. The results show that the implemented ODC mainly affects Akkats. For an increasing ODC, Akkats is operated closer to the best point of efficiency and the operational pattern gets less variable and the effect gets more apparent the lower the spot price. Akkats ability to follow the spot price is reduced, decreasing the earning per produced energy with a few percent­ages. Akkats balancing contribution decreases significantly more, due to a less variable operational pattern. The study compares the reduced ODC to the reduced spot income and concludes that the wear cost in Akkats has to be above 1,21 €/MWh in order to be economically feasible to include in the planning. The operational pattern for the simulated river is close to unchanged at highest price hours but during lower price hours an increasing ODC results in an increased production, due to an increasing mean flow and changed operational pattern in Akkats. More production during low prices hours results in a decreasing profitability for all plants along the river. The balancing contribution is close to unchanged in all plants except Akkats, since the production still follows the same pattern.

As more and more renewable energy sources like wind and solar power are added to the electricgrid, reliable sources of power like hydropower become more important. Hydropower isabundant in Scandinavia, and helps to maintain a stable and reliable grid with added irregularitiesfrom wind and solar power, as well as more fluctuations in demand. Aside from the reliabilityaspect of hydropower, power producers want to maximize their profit from sold electricity. InSweden, power is bid to the spot market at Nord Pool every day, and a final spot price is decidedwithin the electricity market. There is a different electricity price each hour of the day, so it ismore profitable to generate power during some hours than others.There are many other factors that can change when it is most profitable for a hydropower plant tooperate, like how much local inflow of water there is. Hydropower production is an ideal case forusing optimisation models, and they are widely used throughout industry already. Though theoptimisation calculations are done by a computer, there is a lot of manual work from the spottraders that goes into specifying the inputs to the model, such as local inflow, price forecasts, andperhaps most importantly, market strategy. Due to the large amount of work that needs to be donefor each hydropower plant, many of the smaller power plants are not optimised at all, but are leftto run on an automatic control that typically tries to maintain a constant water level. In Fortum,this is called, VNR, or vattennivåreglering (water level regulation).The purpose of this thesis is to develop an optimisation algorithm for a small hydropower plant,using Fortum owned and operated Båthusströmmen as a test case. An optimisation model is builtin Fortum’s current modelling system and is tested for 2016. In addition, a mathematical model isalso built and tested using GAMS. It is found that by optimising the plant instead of running it onVNR, an increase of about 15-16% in profit could be seen for the year 2016. This is a significantimprovement, and is a strong motivator to being optimising the small hydropower plants.Since the main reason many small hydropower plants are not optimised is because it takes toomuch of employees time, a second phase of this thesis was conducted in conjunction with twoother students, Jenny Möller and Johan Wiklund. The focus of this portion was to develop acentralized controller to automatically optimise the production schedule and communicate withthe central database. This would completely remove the workload from the spot traders, as wellas increase the overall profit of the plant. This thesis describes the results from both the Fortummodel and the GAMS model, as well as the mathematical formulation of the GAMS model. Thebasic structure of the automatic controller is also presented, and more can be read in the thesis byMöller and Wiklund (Möller & Wiklund, 2018). / Tillförlitliga energikällor som vattenkraft blir allt viktigare vart eftersom elkraftsystemet utökasmed fler förnybara energikällor som vindkraft och solenergi. I Norden finns det rikligt medvattenkraft, vilket bidrar till att upprätthålla ett stabilt och pålitligt elnät även med ökadeoregelbundenheter från vindkraft och solkraft samt större variationer i efterfrågan. Bortsett frånvattenkraftens tillförlitlighetsaspekter vill kraftproducenter maximera sin vinst från såld el. ISverige läggs dagligen bud på effektvolym till spotmarknaden Nord Pool och ett slutgiltigtmarknadspris bestäms därefter av elmarknaden. Varje timme under dygnet motsvarar ett enskiltelpris, därmed är det mer lönsamt att generera effekt under de timmar där priset är som högst.Det finns många andra faktorer som påverkar när det är mest lönsamt för ett vattenkraftverk attproducera el, exempelvis hur stort det lokala inflödet av vatten är. Vattenkraftproduktion är idealtför tillämpning av optimeringsmodeller, vilka är vanligt förekommande inom verksamhetsområdet.Även om optimeringsberäkningarna utförs av en dator innebär optimeringen mycket manuelltarbete för Fortums elhandlare som specificerar indata till modellen. Exempel på indata är lokaltinflöde, prisprognoser och kanske viktigast av allt marknadsstrategi. På grund av den storamängden arbete som fordras för varje vattenkraftverk, optimeras inte produktionen för många avde småskaliga kraftverken utan de regleras automatiskt med mål att upprätthålla en konstantvattennivå. Denna typ av reglering kallas vattennivåreglering, VNR.Syftet med examensarbetet var att utveckla en optimeringsalgoritm för ett småskaligtvattenkraftverk, där Fortumägda vattenkraftverket Båthusströmmen används som testobjekt. Enoptimeringsmodell utvecklades i Fortums befintliga system och testades för 2016. Dessutom haren matematisk modell utvecklats och testades med GAMS. Det konstaterades att genom attoptimera produktionen från vattenkraftverket istället för att reglera den via VNR kan envinstökning med cirka 15-16 % för noteras år 2016. Detta är en väsentlig förbättring och är ettstarkt argument för att optimera produktionen från småskaliga vattenkraftverk.Eftersom den främsta orsaken till att många småskaliga vattenkraftverk inte optimeras är denutökade arbetsbelastningen det skulle innebära för de anställda, genomfördes en andra fas iexamensarbetet i samverkan med två andra studenter, Jenny Möller och Johan Wiklund. Fokus fördenna del var att utveckla en centraliserad styrenhet för att automatiskt optimera produktionsplaneroch kommunicera med det befintliga centrala systemet. Detta innebär att utökad arbetsbelastningenfrån elhandlarna undviks, samt öka vattenkraftverkets totala vinst. Denna rapport beskriverresultaten från både Fortum-modellen och GAMS-modellen, liksom den matematiskaformuleringen av GAMS-modellen. Även grundstrukturen för det självreglerandeoptimeringsverktyget presenteras, mer kan läsas i rapporten av Möller och Wiklund (Möller &Wiklund, 2018).Nyckelord: Optimering, vattenkraftplanering, självreglerande, automatisk styrning, optimalplanering