The Impact of Renewable Electricity on the Czech Electricity Balancing Market

• Název práce v češtině: Vliv obnovitelných zdrojů na systémovou odchylku v České republice
• Název v anglickém jazyce: The Impact of Renewable Electricity on the Czech Electricity Balancing Market
• Klíčová slova: obnovitelné zdroje, vyrovnávací trh, volatilita
• Klíčová slova anglicky: renewable sources, balancing market, imbalance volumes, volatility
• Akademický rok vypsání: 2019/2020
• Typ práce: diplomová práce
• Jazyk práce: angličtina
• Ústav: Institut ekonomických studií (23-IES)
• Vedoucí / školitel: Mgr. Luboš Hanus, Ph.D.
• Řešitel: skrytý - zadáno vedoucím/školitelem
• Datum přihlášení: 27.07.2020
• Datum zadání: 27.07.2020
• Datum a čas obhajoby: 16.06.2021 09:00
• Místo konání obhajoby: Výuka probíhá online
• Datum odevzdání elektronické podoby: 04.05.2021
• Datum proběhlé obhajoby: 16.06.2021
• Oponenti: prof. Ing. Karel Janda, Dr., Ph.D., M.A.

Seznam odborné literatury

Kiviluoma, J., Meibom, P., Tuohy, A., Troy, N., Milligan, M., Lange, B., ... & O'Malley, M. (2012). Short-term energy balancing with increasing levels of wind energy. IEEE Transactions on Sustainable Energy, 3(4), 769-776.

Goodarzi, S., Perera, H. N., & Bunn, D. (2019). The impact of renewable energy forecast errors on imbalance volumes and electricity spot prices. Energy Policy, 134, 110827.

Bueno-Lorenzo, M., Moreno, M. Á., & Usaola, J. (2013). Analysis of the imbalance price scheme in the Spanish electricity market: A wind power test case. Energy policy, 62, 1010-1019.

Aïd, R., Gruet, P., & Pham, H. (2016). An optimal trading problem in intraday electricity markets. Mathematics and Financial Economics, 10(1), 49-85.

Kiesel, R., & Paraschiv, F. (2017). Econometric analysis of 15-minute intraday electricity prices. Energy Economics, 64, 77-90.

Pape, C., Hagemann, S., & Weber, C. (2016). Are fundamentals enough? Explaining price variations in the German day-ahead and intraday power market. Energy Economics, 54, 376-387.

Koenker, R., & Bassett Jr, G. (1978). Regression quantiles. Econometrica: journal of the Econometric Society, 33-50.

Koenker, R., & Hallock, K. F. (2001). Quantile regression. Journal of economic perspectives, 15(4), 143-156.

Perez-Mora, N., Martinez-Moll, V., & Canals, V. (2015). Spanish Renewable Energy Generation Short-Term Forecast. In Proceedings of the ISES Solar World Congress.

Cui, H., & Peng, X. (2015). Short-term city electric load forecasting with considering temperature effects: an improved ARIMAX model. Mathematical Problems in Engineering, 2015.

Conejo, A. J., Plazas, M. A., Espinola, R., & Molina, A. B. (2005). Day-ahead electricity price forecasting using the wavelet transform and ARIMA models. IEEE transactions on power systems, 20(2), 1035-1042.

Tashpulatov, S. N. (2013). Estimating the volatility of electricity prices: The case of the England and Wales wholesale electricity market. Energy Policy, 60, 81-90.

Pham, T., & Lemoine, K. (2015). Impacts of subsidized renewable electricity generation on spot market prices in Germany: evidence from a garch model with panel data.

Ketterer, J. C. (2014). The impact of wind power generation on the electricity price in Germany. Energy Economics, 44, 270-280.

Předběžná náplň práce v anglickém jazyce

Motivation:
Over the last decade, a strong emphasis has been put on the promotion of green electricity in the European energy sector. The increasing levels of renewable energy add the uncertainty and variability inherent in electricity grids and impose additional costs for balancing and reserve requirements (Kiviluoma et al., 2012). With greater intra-day uncertainties, the costs from real-time supply-demand imbalances rise for the market participants, creating financial difficulties. It leads to market exits for retailers who fail to hedge effectively, and the operational complexity adds to the costs of transmission system operators (TSOs) (Goodarzi et al., 2019).

Due to the European transition to low carbon energy supply, significant energy surpluses flow into the Czech transmission system, potentially affecting the imbalance volumes and price of electricity in the local market. The source of these surpluses is mainly German wind farms. To what extent German renewable electricity affects Czech imbalance volumes and prices are interesting and important information for government and local electricity providers. The Czech national TSO ČEPS has to buy reserved capacity on balancing market. Thus, the knowing key drives of imbalances is of great importance. Further, with the rise of Internet of Things (IoT) and progress in processing real-time data new business on energy markets has emerged, specifically on balancing market. These new market participants try to make profits and optimise their portfolio on balancing market by forecasting imbalance volumes and prices. Such businesses could profit on the knowledge what is the driver of the imbalance volumes.

Whilst a number of empirical studies were conducted on the topic of renewable electricity and its impact on spot prices, focus on electricity’s real-time imbalances has been relatively scant. Bueno-Lorenzo et al., (2013) investigate the relationship between wind energy and imbalance volumes in the Spanish energy market, focusing on developing new pricing scheme to create more efficient electricity market. Other studies primarily focus on thermal power generation in order to mitigate fluctuations in wind energy generations (e.g. Aïd et al, 2016). Next, many researchers such as Kiesel and Paraschiv (2017) and Pape et al., (2016) seek to develop superior forecasting models for electricity imbalance volumes and electricity prices. Both studies use regression methods to forecast imbalance and electricity prices for German intraday market. However, we would like to show the impact of renewable energy on the imbalance volumes. A paper close to our field of interest written by Goodarzi et al. (2019) studies, how renewable energy (wind and solar) forecast errors affect the imbalance volumes.

Hypotheses:
1. Hypothesis #1: The Czech renewable power generation increase imbalance volumes on the Czech electricity balancing market.
2. Hypothesis #2: The German wind and solar power generation increase imbalance volumes on the Czech electricity balancing market.
3. Hypothesis #3: Renewable power generation increase volatility of imbalance volumes on the Czech electricity balancing market

Methodology:
I will use data of day-ahead forecast for wind and solar production in Germany and the Czech Republic and data of actual wind and solar production in Germany and Czech Republic from European Network of Transmission System Operators for Electricity (ENTSO-E). Further, I will employ Load (CZ) from the same platform. These data show instantaneous electricity demand. While data from the Czech market has hourly granularity, German production volumes are given in 15 minutes timestamps. Thus, I will compute and work with hour averages.

To analyse imbalance volumes of electricity, there is a large variety of models that can be used. As in Goodarzi et al. (2019), we can use quantile regression to estimate imbalance volumes, which is an extension of ordinary least squares regression that aims to estimate the median and quantiles of the response variables (Koenker and Bassett, 1978; Koenker and Hallock, 2001). Another popular family of models used in energy market analyses are autoregressive models with external variables (ARIMAX). Such a model takes into account autocorrelation which is usually present in energy markets data while allowing to estimate the effect of other variables on a response variable (Perez-Mora et al., 2015; Cui and Peng, 2015).

Further, to analyse the volatility of imbalance volumes, we can use similar methods as Tashpulatov (2013), Pham & Lemoine (2015), Conejo et. al (2005) who analyse price volatility using autoregressive conditional heteroskedasticity models. Another approach that can also help to estimate the volatility of imbalance volumes is described in Haximusa (2018), where the author estimates cross-border effects of German wind and solar electricity on French spot price volatility. As dependent variable Haximusa (2018) chooses the absolute value of the deviation of the actual hourly French spot price from its daily mean and not standard measure of price variance (e.g. Ketterer, 2014).

Expected Contribution:
As the levels renewable energy accelerates, it is important to know to what extent is the Czech market, specifically balancing market, affected. The thesis should analyse whether Czech and German electricity produced by renewable resources increases the imbalance volumes on Czech electricity balancing market. Further, the volatility of the Czech imbalance volumes concerning renewable power generation will be analysed. The estimates can be used by both the Czech government and Czech local electricity providers for strategy optimisation.

Outline:
1. Motivation: Introduction to the topic and description of the electricity market.
2. Literature Review: Description of estimation techniques used in recent studies of the electricity market.
3. Data: I will describe the data used for analysis.
4. Methods: A detailed summary of methods I will use in the thesis.
5. Results: I will discuss my findings based on estimated models.
6. Conclusion: Summary of regression results and possible implications for the Czech policy decision-maker.