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Data-driven analysis of the real-time electricity price considering wind power effect
The electricity price is the sensitive signal of the supply-demand balance and some other market incidents. The analysis of the price data can provide plenty of the market information. It is helpful for the participants to understand the market and improve future strategies. However, most of the for...
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Published in: | Energy reports 2020-02, Vol.6 (2), p.452-459 |
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creator | Yang, Shengjie Xu, Xuesong Liu, Jiangang Jiang, Weijin |
description | The electricity price is the sensitive signal of the supply-demand balance and some other market incidents. The analysis of the price data can provide plenty of the market information. It is helpful for the participants to understand the market and improve future strategies. However, most of the forecast models eliminate the details to reduce the structural risk for generality. In this paper, the data-driven analysis is proposed to explore the PJM electricity price in detail. The price time series is decomposed into different components. Each component is modeled and tested by the statistical method to illustrate the hidden pattern of the fluctuation, so that there can be reasonable interpretation about the market. The relationship between the price and the wind power is numerically detected through the heterogeneity of the price time series. The paper demonstrates the data-driven method to mine information and achieve the analysis of electricity market. |
doi_str_mv | 10.1016/j.egyr.2019.11.102 |
format | article |
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The analysis of the price data can provide plenty of the market information. It is helpful for the participants to understand the market and improve future strategies. However, most of the forecast models eliminate the details to reduce the structural risk for generality. In this paper, the data-driven analysis is proposed to explore the PJM electricity price in detail. The price time series is decomposed into different components. Each component is modeled and tested by the statistical method to illustrate the hidden pattern of the fluctuation, so that there can be reasonable interpretation about the market. The relationship between the price and the wind power is numerically detected through the heterogeneity of the price time series. 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The analysis of the price data can provide plenty of the market information. It is helpful for the participants to understand the market and improve future strategies. However, most of the forecast models eliminate the details to reduce the structural risk for generality. In this paper, the data-driven analysis is proposed to explore the PJM electricity price in detail. The price time series is decomposed into different components. Each component is modeled and tested by the statistical method to illustrate the hidden pattern of the fluctuation, so that there can be reasonable interpretation about the market. The relationship between the price and the wind power is numerically detected through the heterogeneity of the price time series. The paper demonstrates the data-driven method to mine information and achieve the analysis of electricity market.</description><subject>Electricity market</subject><subject>Heterogeneous volatility</subject><subject>Real-time price</subject><subject>Time series</subject><subject>Wind power</subject><issn>2352-4847</issn><issn>2352-4847</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNp9kF1LwzAYhYsoOOb-gCDkD3Tmq20C3sj8Ggy8cdchS97OlK4dSdnov_edE_HKqxMO5xzePFl2y-icUVbeN3PYjnHOKdNzxtDjF9mEi4LnUsnq8s_7Opul1FCKSU5lKSbZ-skONvcxHKAjtrPtmEIifU2GTyARbJsPYQcEWnBDDC4MI9mjAnF9l4KHGLotOYbOk31_hEigrjF5k13Vtk0w-9Fptn55_li85av31-XicZU7qfSQC68YowoE5czJSgjPVMlKQS3jslLealFIrnnlZc1xuFDgOEa0FMKWXopptjzv-t42Bg_b2Tia3gbzbfRxa2wcgmvBOMuoLilSUJXkIJTWm4oCVAXdaEsFbvHzlot9ShHq3z1GzYmzacyJszlxNoyhx7H0cC4B_vIQIJrkAnQOfIjIAc8I_9fvfuqIMyRzkjT0GJJCI4gvBUOOmQ</recordid><startdate>20200201</startdate><enddate>20200201</enddate><creator>Yang, Shengjie</creator><creator>Xu, Xuesong</creator><creator>Liu, Jiangang</creator><creator>Jiang, Weijin</creator><general>Elsevier</general><general>Elsevier Ltd</general><scope>OT2</scope><scope>6I.</scope><scope>AAFTH</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>DOA</scope></search><sort><creationdate>20200201</creationdate><title>Data-driven analysis of the real-time electricity price considering wind power effect</title><author>Yang, Shengjie ; Xu, Xuesong ; Liu, Jiangang ; Jiang, Weijin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c489t-3d81108e3021c4733d1861630a12478da93542927d4f2ffe58ec21869433a6d43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Electricity market</topic><topic>Heterogeneous volatility</topic><topic>Real-time price</topic><topic>Time series</topic><topic>Wind power</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yang, Shengjie</creatorcontrib><creatorcontrib>Xu, Xuesong</creatorcontrib><creatorcontrib>Liu, Jiangang</creatorcontrib><creatorcontrib>Jiang, Weijin</creatorcontrib><collection>EconStor</collection><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>CrossRef</collection><collection>Directory of Open Access Journals</collection><jtitle>Energy reports</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yang, Shengjie</au><au>Xu, Xuesong</au><au>Liu, Jiangang</au><au>Jiang, Weijin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Data-driven analysis of the real-time electricity price considering wind power effect</atitle><jtitle>Energy reports</jtitle><date>2020-02-01</date><risdate>2020</risdate><volume>6</volume><issue>2</issue><spage>452</spage><epage>459</epage><pages>452-459</pages><issn>2352-4847</issn><eissn>2352-4847</eissn><abstract>The electricity price is the sensitive signal of the supply-demand balance and some other market incidents. 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subjects | Electricity market Heterogeneous volatility Real-time price Time series Wind power |
title | Data-driven analysis of the real-time electricity price considering wind power effect |
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