engleski

Data driven approach for analyzing and correlating energy market products: Case studies of Denmark and Croatia

Electricity price forecasting plays a vital role in the strategy decision making for almost all power market participants. This article investigates statistical background and potential relations between different power market products (e.g. day-ahead prices, intraday prices, etc.). Danish and Croatian power markets are used for a purpose of the case study to present the methods used in this article. Firstly, Danish and Croatian power market structure are shortly explained so the reader has a clear view on the context of the whole problem. Further, the data gathering and editing process is described and explained, after which the main topic of the article — statistical analysis, follows. In addition to the presented histograms of respective power market components, their mutual relationships are observed too. Results of the statistical analysis prove correlations between some of them and they are both numerically and graphically demonstrated and elaborated. Furthermore, price spreads are investigated as a logical next step of the noticed correlations. A comparison between peculiarities in Danish and Croatian markets are analyzed and the results have i) proved relationship between specific market components, ii) demonstrated patterns of observed factors and iii) the developed tool and data is made freely available for authors for further research. Finally, the findings of this article present to the market participants an efficient tool to adjust their business strategies and increase their profit.

statistical analysis , prices , day-ahead , intraday , distribution , spread

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