Drivers of price volatility in Romania’s electricity markets
DOI: https://doi.org/10.3846/jbem.2025.24709Abstract
The paper examines the price volatility, key determinants, and autoregressive distributed lag (ARDL) framework of Romania’s Intraday Continuous Market (IDC) during the summer months. The stability of the ARDL-ECM coefficients is assessed using the cumulative sum (CUSUM) test. We explore the interaction between IDC and Day-Ahead Market (DAM) prices, alongside the influence of economic and environmental variables, including traded volumes, consumption, export/import and the generation mix. Using hourly data and econometric techniques, we identify significant short- and long-run relationships between IDC prices and their drivers. DAM prices exhibit a strong positive impact on IDC prices, reflecting tight market integration. Higher shares of Renewable Energy Sources (RES) such as wind and solar are associated with increased IDC prices, highlighting challenges in integrating intermittent resources. Conventional sources, particularly coal and oil/gas, also elevate prices due to higher marginal costs. Conversely, electricity consumption is negatively related to IDC prices, suggesting that anticipated demand patterns may contribute to system stability. The findings carry implications for policymakers, indicating a need for enhanced forecasting, flexible resources and improved inter-market coordination to ensure price stability and efficient integration of RES.
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electricity markets, generation breakdown, renewables, total consumption, ARDL-ECM, CUSUMHow to Cite
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References
Akono, E. B., & Kemezang, V. C. (2024). Balancing short-term costs and long-term benefits: An analysis of the impact of hydroelectric power generation on electricity prices volatility in Cameroon. Sustainable Energy Research, 11, Article 7. https://doi.org/10.1186/s40807-024-00099-y
Bâra, A., Oprea, S.-V., & Georgescu, I. A. (2023a). Understanding electricity price evolution – day-ahead market competitiveness in Romania. Journal of Business Economics and Management, 24(2), 221–244. https://doi.org/10.3846/jbem.2023.19050
Bâra, A., Oprea, S.-V., & Oprea, N. (2023b). How fast to avoid carbon emissions: A holistic view on the RES, storage and non-RES replacement in Romania. International Journal of Environmental Research and Public Health, 20(6), Article 5115. https://doi.org/10.3390/ijerph20065115
Bâra, A., Oprea, S. -V., & Ciurea, C.-E. (2024). Improving the strategies of the market players using an AI-powered price forecast for electricity market. Technological and Economic Development of Economy, 30(1), 312–337. https://doi.org/10.3846/tede.2023.20251
Baule, R., & Naumann, M. (2021). Volatility and dispersion of hourly electricity contracts on the German continuous intraday market. Energies, 14(22), Article 7531. https://doi.org/10.3390/en14227531
Burlăcioiu, C., Boboc, C., Mirea, B., & Dragne, I. (2023). Text mining in business. A study of Romanian client’s perception with respect to using telecommunication and energy APPS. Economic Computation and Economic Cybernetics Studies and Research, 57, 221–234. https://doi.org/10.24818/18423264/57.1.23.14
Cevik, S., & Ninomiya, K. (2022). Chasing the sun and catching the wind: Energy transition and electricity prices in Europe (IMF Working Papers, 220). International Monetary Fund. https://doi.org/10.5089/9798400224362.001
Ciarreta, A., Pizarro-Irizar, C., & Zarraga, A. (2020). Renewable energy regulation and structural breaks: An empirical analysis of Spanish electricity price volatility. Energy Economics, 88, Article 104749. https://doi.org/10.1016/j.eneco.2020.104749
da Silva Leite, A. L., & Andrade de Lima, M. V. (2023). A GARCH Model to understand the volatility of the electricity spot price in Brazil. International Journal of Energy Economics and Policy, 13(5), 332–338. https://doi.org/10.32479/ijeep.14226
Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366), 427–431. https://doi.org/10.2307/2286348
Dong, S., Li, H., Wallin, F., Avelin, A., Zhang, Q., & Yu, Z. (2019). Volatility of electricity price in Denmark and Sweden. Energy Procedia, 158, 4331–4337. https://doi.org/10.1016/j.egypro.2019.01.788
Dzhalladova, I., Novotná, V., & Půža, B. (2023). Model of optimal control of labour reproduction and saving energy in undefined conditions of the current situation. Economic Computation and Economic Cybernetics Studies and Research, 57, 283–298. https://doi.org/10.24818/18423264/57.1.23.18
Gudkov, N., & Ignatieva, K. (2021). Electricity price modelling with stochastic volatility and jumps: An empirical investigation. Energy Economics, 98, Article 105260. https://doi.org/10.1016/j.eneco.2021.105260
Haugom, E., Lyócsa, Š., & Halousková, M. (2024). The tipping point of electricity price attention: When a problem becomes a problem. Economics Letters, 235, Article 111547. https://doi.org/10.1016/j.econlet.2024.111547
Heijden, T. V. D., Lago, J., Palensky, P., & Abraham, E. (2021). Electricity price forecasting in european day ahead markets: A greedy consideration of market integration. IEEE Access, 9, 119954–119966. https://doi.org/10.1109/access.2021.3108629
Hu, T., & Wang, C. (2022). The impact of optimally dispatched energy storage devices on electricity price volatility. International Journal of Electrical Power and Energy Systems, 137, Article 107810. https://doi.org/10.1016/j.ijepes.2021.107810
Krečar, N., & Gubina, A. F. (2020). Risk mitigation in the electricity market driven by new renewable energy sources. Wiley Interdisciplinary Reviews: Energy and Environment, 9(1), Article e362. https://doi.org/10.1002/wene.362
Lin, C., Schmid, T., & Weisbach, M. S. (2021). Product price risk and liquidity management: Evidence from the electricity industry. Management Science, 67(4), 1993–2656. https://doi.org/10.1287/mnsc.2020.3579
Maddala, G. S., & Wu, S. (1999). A comparative study of unit root tests with panel data and a new simple test. Oxford Bulletin of Economics and Statistics, 61(S1), 631–652. https://doi.org/10.1111/1468-0084.0610s1631
Maniatis, G. I., & Milonas, N. T. (2022). The impact of wind and solar power generation on the level and volatility of wholesale electricity prices in Greece. Energy Policy, 170, Article 113243. https://doi.org/10.1016/j.enpol.2022.113243
Masoumzadeh, A., Nekouei, E., Alpcan, T., & Chattopadhyay, D. (2018). Impact of optimal storage allocation on price volatility in energy-only electricity markets. IEEE Transactions on Power Systems, 33(2), 1903–1914. https://doi.org/10.1109/TPWRS.2017.2727075
Mosquera-López, S., & Nursimulu, A. (2019). Drivers of electricity price dynamics: Comparative analysis of spot and futures markets. Energy Policy, 126, 76–87. https://doi.org/10.1016/j.enpol.2018.11.020
Mwampashi, M. M., Nikitopoulos, C. S., Konstandatos, O., & Rai, A. (2021). Wind generation and the dynamics of electricity prices in Australia. Energy Economics, 103, Article 105547. https://doi.org/10.1016/j.eneco.2021.105547
Oprea, S. V., & Bâra, A. (2025). Analyzing shock transmission and spillover effect in the day-ahead and intraday markets: Key implications for price forecasting. Journal of the Knowledge Economy. https://doi.org/10.1007/s13132-025-02603-1
Owolabi, O. O., Lawson, K., Sengupta, S., Huang, Y., Wang, L., Shen, C., Getmansky Sherman, M., & Sunter, D. A. (2022). A robust statistical analysis of the role of hydropower on the system electricity price and price volatility. Environmental Research Communications, 4(7), Article 075003. https://doi.org/10.1088/2515-7620/ac7b74
Pereira da Silva, P., & Horta, P. (2019). The effect of variable renewable energy sources on electricity price volatility: The case of the Iberian market. International Journal of Sustainable Energy, 38(8), 794–813. https://doi.org/10.1080/14786451.2019.1602126
Pesaran, M. H., & Shin, Y. (1999). An autoregressive distributed lag modelling approach to cointegration analysis. In S. Strøm (Ed.), Econometrics and economic theory in the 20th century: The Ragnar Frisch Centennial Symposium (pp. 371–413). Cambridge University Press. https://doi.org/10.1017/CCOL521633230.011
Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346. https://doi.org/10.1093/biomet/75.2.335
Rintamäki, T., Siddiqui, A. S., & Salo, A. (2017). Does renewable energy generation decrease the volatility of electricity prices? An analysis of Denmark and Germany. Energy Economics, 62, 270–282. https://doi.org/10.1016/j.eneco.2016.12.019
Segnon, M., Lau, C. K., Wilfling, B., & Gupta, R. (2022). Are multifractal processes suited to forecasting electricity price volatility? Evidence from Australian intraday data. Studies in Nonlinear Dynamics and Econometrics, 26, 73–98. https://doi.org/10.1515/snde-2019-0009
Shah, D., & Chatterjee, S. (2020). A comprehensive review on day-ahead electricity market and important features of world’s major electric power exchanges. International Transactions on Electrical Energy Systems, 30, Article 12360. https://doi.org/10.1002/2050-7038.12360
Sikorska-Pastuszka, M., & Papież, M. (2023). Dynamic volatility connectedness in the European electricity market. Energy Economics, 127, Article 107045. https://doi.org/10.1016/j.eneco.2023.107045
Spiru, P. (2023). Assessment of renewable energy generated by a hybrid system based on wind, hydro, solar, and biomass sources for decarbonizing the energy sector and achieving a sustainable energy transition. Energy Reports, 9(S8), 167–174. https://doi.org/10.1016/j.egyr.2023.04.316
Wang, C., Zhou, H., Dinçer, H., Yüksel, S., Ubay, G. G., & Uluer, G. S. (2020). Analysis of electricity pricing in emerging economies with hybrid multi-criteria decision-making technique based on interval-valued intuitionistic hesitant fuzzy Sets. IEEE Access, 8, 190882–190896. https://doi.org/10.1109/ACCESS.2020.3031761
Wang, D., Gryshova, I., Kyzym, M., Salashenko, T., Khaustova, V., & Shcherbata, M. (2022). Electricity price instability over time: Time series analysis and forecasting. Sustainability, 14(15), Article 9081. https://doi.org/10.3390/su14159081
Zlateva, P., Yordanov, K., Tudorache, A., & Cirtina, L. M. (2020, June 3–6). An analysis of energy resources in Bulgaria and Romania. In Proceedings of the 2020 21st International Symposium on Electrical Apparatus and Technologies (SIELA) (pp. 1–4). Bourgas, Bulgaria. IEEE. https://doi.org/10.1109/SIELA49118.2020.9167132
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