Modelling of prices using the volume in the Norwegian regulating power market

Jaehnert, Stefan; Farahmand, Hossein; Doorman, Gerard

doi:10.1109/ptc.2009.5281972

Cited by 22 publications

(45 citation statements)

References 7 publications

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“…NO2 covers the southern and western part of Norway, with connections to price areas NO1, NO5 and DK1. Earlier, NO2 was a part of the NO1 area analyzed by [19] and [12].…”

Section: Datamentioning

confidence: 99%

“…Therefore the data was log transformed and mean differenced in some of the models, but not in others. The only deviation from the original formulation is the EXO model, inspired by Jaehnert et al [12]. We opted to log-transform the prices and exogenous inputs in order to compress the variance and obtain better fit.…”

Section: Datamentioning

confidence: 99%

“…When it comes to balancing market prices, no survey exists to our knowledge. However, case studies exist, including Skytte [19], Fleten and Pettersen [9],Olsson and Söder [17], Jaehnert et al [12], Brolin and Söder [2] and Boomsma et al [1] -all of them from the Nordic market. The contribution of this article is a systematic review and benchmarking of time series based methods for balancing market price forecasting.…”

mentioning

confidence: 99%

“…This study will focus on only one balancing market -the Nord Pool price zone NO2 in Norway. Price models for this area have previously been built by Skytte [19] and Jaehnert et al [12].…”

mentioning

confidence: 99%

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Benchmarking time series based forecasting models for electricity balancing market prices

2013

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In the trade-off between bidding in the day-ahead electricity market and the real time balancing market, producers need good forecasts for balancing market prices to make informed decisions. A range of earlier published models for forecasting of balancing market prices, including a few extensions, is benchmarked. The models are benchmarked both for one hour-ahead and dayahead forecast, and both point and interval forecasts are compared. None of the benchmarked models produce informative day-ahead point forecasts, suggesting that information available before the closing of the day-ahead market is efficiently reflected in the day-ahead market price rather than the balancing market price. Evaluation of the interval forecasts reveals that models without balancing state information overestimate variance, making them unsuitable for scenario generation.

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“…NO2 covers the southern and western part of Norway, with connections to price areas NO1, NO5 and DK1. Earlier, NO2 was a part of the NO1 area analyzed by [19] and [12].…”

Section: Datamentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

mentioning

confidence: 99%

“…This study will focus on only one balancing market -the Nord Pool price zone NO2 in Norway. Price models for this area have previously been built by Skytte [19] and Jaehnert et al [12].…”

mentioning

confidence: 99%

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Benchmarking time series based forecasting models for electricity balancing market prices

2013

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“…Therefore, there will be no model that suits all balancing price processes. This explains why Skytte [39] finds that the balancing price can be explained by the dayahead market price, while Jaehnert et al [40] results indicate no correlation between the spot and balancing prices. Jaehnert et al [40] model the balancing price as the difference to the day-ahead market price, while both Olsson and Soder [41] and Klaeboe et al [42] model it directly including correlation with the spot price.…”

Section: Balancing Pricementioning

confidence: 97%

Investment in electric energy storage under uncertainty: a real options approach

et al. 2016

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Problem descriptionThe growing portion of renewables in the generation mix has led to an increasing need for ancillary services in the electricity grid. As a part of this green shift, the role of storage in the electricity market has changed. Traditionally, the motivation for investing in storage was based on time arbitrage of the spot price. Today, the investments in storage are being linked with the need for improving the power quality and balancing the grid.Recent research papers point out that investments in small storage facilities are not profitable today without public support. This thesis will apply the real options framework, and investigate the profitability of energy storage under uncertain electricity prices, balancing prices and investment cost. It will further consider how policy makers can trigger investments in electric energy storage. PrefaceThis is a master thesis written within the field of Financial Engineering at the Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology (NTNU). We would like to thank our supervisors, Verena Hagspiel and Stein-Erik Fleten, for professional guidance throughout the project. We also wish to thank Professor Sonja Wogrin at Universidad Pontificia Comillas de Madrid for technical assistance, PhD candidate Lars Ivar Hagfors at NTNU for valuable input and Statkraft for providing market data. Trondheim, 8th of June 2015Ida BakkeBeate Norheim AbstractThe transition from conventional power sources to renewable energy sources is taking place in a number of European countries. Electric energy storage has been proposed as an environmentally friendly solution to make this transition possible. This thesis analyzes the profitability of investing in a battery bank in Germany and the UK, using a real options model. The model determines the option value and the optimal investment time, under the conditions of uncertain revenues and investment cost. The results show that it is profitable to invest in both countries, given that the battery banks can participate in both the spot and balancing market. The valuation also gives insight into how the battery bank should be operated between the two markets to maximize its expected profits and discovers that the battery earns over 70 % of its profit from ancillary services. This finding underlines the importance for investors to not only consider revenues from the spot market. The thesis further analyzes how uncertainty affects investor behavior and explains why there is a reluctance to invest in storage technology under the current market conditions; the investor is favoring the option to wait for more information. SammendragOvergangen fra konvensjonelle energikilder til fornybare energikilder finner sted i en rekke europeiske land. Elektrisk energilagring har blitt foreslått som en miljøvennlig løsning forå gjøre denne overgangen mulig. I denne masteroppgaven utvikler vi en realopsjonsmodel for a analysere lønnsomheten vedå investere i batteribanker i Storbritannia og Tyskland. Mode...

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Coordinated production planning of risk-averse hydropower producer in sequential markets

Vardanyan

Hesamzadeh

2015

Int. Trans. Electr. Energ. Syst.

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SUMMARYThis paper proposes a quadratic programming (QP) model for optimal coordinated production of a risk-averse hydropower producer. The day-ahead, intra-day and real-time markets are considered. A rolling planning approach is used to take advantage of sequential clearing of mentioned markets. The multi-period risk of trading in different markets is modelled as quadratic terms in the objective function. To cope with uncertain prices, three price forecasting techniques are used. The best forecasting technique is selected based on a designed Markov switch. The discrete behaviour of intra-day and real-time market prices are modelled as different Markov states. The proposed QP model is coded in GAMS (GAMS Development Corporation, Washington, DC, USA) platform and solved using the MOSEK (Mosek ApS, Copenhagen, Denmark) solver. An example of a three-reservoir system from a Swedish hydropower producer is used to examine the proposed QP model. The results show the economic gains from coordinated production planning in sequential markets.

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Modelling of prices using the volume in the Norwegian regulating power market

Cited by 22 publications

References 7 publications

Benchmarking time series based forecasting models for electricity balancing market prices

Benchmarking time series based forecasting models for electricity balancing market prices

Investment in electric energy storage under uncertainty: a real options approach

Coordinated production planning of risk-averse hydropower producer in sequential markets

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