Data-Driven Approach for Analyzing and Correlating Energy Market Products: Case Studies of Denmark and Croatia  

作　　者：Domagoj Badanjak Ivan Pavić Tomislav Capuder 

机构地区：[1]Faculty of Electrical Engineering and Computing,University of Zagreb,Zagreb,Croatia

出　　处：《CSEE Journal of Power and Energy Systems》2025年第2期503-520,共18页中国电机工程学会电力与能源系统学报(英文)

基　　金：supported in part by the Croatian Science Foundation and the European Union through the European Social Fund under the Project of Flexibility of Converter-based Micro-grids—FLEXIBASE(PZS-2019-02-7747);in part by the European Structural and Investment Funds under KK.01.2.1.02.0066 Electric Vehicle Charging Station with Integrated Battery Storage.

摘　　要：Electricity price forecasting plays a vital role inthe strategy decision making for almost all power marketparticipants. This article investigates statistical background andpotential relations between different power market products (e.g.day-ahead prices, intraday prices, etc.). Danish and Croatianpower markets are used for the purpose of the case studyto present the methods used in this article. First, Danish andCroatian power market structures are shortly explained to clarifythe context of the problem. The data collection and preprocessingmethods are described, followed by the core focus of the study:statistical analysis. In addition to the presented histograms ofrespective power market components, we examine interrelationships through statistical analysis, demonstrating significantcorrelations both numerically and graphically. Furthermore,price spreads are investigated as a logical next step of the noticedcorrelations. Our comparative analysis of Danish and Croatianmarket peculiarities reveals three key findings: i) statisticallysignificant relationships between specific market components,ii) distinct behavioral patterns among observed factors, and iii) anopen-access analytical tool with accompanying dataset for futureresearch. Finally, the findings of this article present to marketparticipants an efficient tool to adjust business strategies andincrease profit.

关 键 词：Day-ahead distribution intraday PRICES SPREAD statistical analysis. 

分 类 号：F416.2[经济管理—产业经济]