{"title":"俄罗斯电力市场日前电价预测","authors":"A. Maksimov, Daria V. Shchurupova","doi":"10.2139/ssrn.2877697","DOIUrl":null,"url":null,"abstract":"Abstract After analyzing the characteristics and pricing models on the Russian wholesale electricity market, some important features for econometric modeling are introduced. This paper suggests econometric forecasting models developed to predict daily and hourly electricity prices on the day-ahead market for two price zones in Russia: European and Siberian ones. A set of 24 models, which are similar in nature but different in included regressors, are introduced. On the basis of the actual database for 2014, different modifications of price formation are offered and analyzed with the help of the Eviews econometric package. Dynamic forecasts on various distances (day, week, and month) are conducted and the most suitable models from the point of minimizing the norms of the vectors residuals are chosen. Constructed ARMA models have high predictive power and are able to reflect the price trend on the base of exogenous factors and the previous price values.","PeriodicalId":43050,"journal":{"name":"Cogent Physics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Forecasting of the electricity price on the day-ahead electricity market in Russia\",\"authors\":\"A. Maksimov, Daria V. Shchurupova\",\"doi\":\"10.2139/ssrn.2877697\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract After analyzing the characteristics and pricing models on the Russian wholesale electricity market, some important features for econometric modeling are introduced. This paper suggests econometric forecasting models developed to predict daily and hourly electricity prices on the day-ahead market for two price zones in Russia: European and Siberian ones. A set of 24 models, which are similar in nature but different in included regressors, are introduced. On the basis of the actual database for 2014, different modifications of price formation are offered and analyzed with the help of the Eviews econometric package. Dynamic forecasts on various distances (day, week, and month) are conducted and the most suitable models from the point of minimizing the norms of the vectors residuals are chosen. Constructed ARMA models have high predictive power and are able to reflect the price trend on the base of exogenous factors and the previous price values.\",\"PeriodicalId\":43050,\"journal\":{\"name\":\"Cogent Physics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-11-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cogent Physics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.2877697\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cogent Physics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.2877697","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Forecasting of the electricity price on the day-ahead electricity market in Russia
Abstract After analyzing the characteristics and pricing models on the Russian wholesale electricity market, some important features for econometric modeling are introduced. This paper suggests econometric forecasting models developed to predict daily and hourly electricity prices on the day-ahead market for two price zones in Russia: European and Siberian ones. A set of 24 models, which are similar in nature but different in included regressors, are introduced. On the basis of the actual database for 2014, different modifications of price formation are offered and analyzed with the help of the Eviews econometric package. Dynamic forecasts on various distances (day, week, and month) are conducted and the most suitable models from the point of minimizing the norms of the vectors residuals are chosen. Constructed ARMA models have high predictive power and are able to reflect the price trend on the base of exogenous factors and the previous price values.