{"title":"利用电力市场分析降低成本和环境影响","authors":"Conor Kelly, A. Ruzzelli, E. Mangina","doi":"10.1109/GREENTECH.2013.70","DOIUrl":null,"url":null,"abstract":"In recent years, energy consumption has become a major issue in terms of cost, infrastructure requirements and emissions. In deregulated markets electricity prices, renewable energy contribution and emissions can vary substantially from hour to hour. These temporal variations introduce significant opportunities for any flexible energy consumer. A granular analysis of the Irish electricity market for the first four months of 2012 showed the large variations characteristic of deregulated electricity markets - the spot price spiked up to 985% of the average price, marginal emissions varied by up to 55% and renewable energy generation had a standard deviation of 11.78%. Strong correlations are observed between renewable generation and market prices - market prices reduced significantly with increased wind generation. Utilising intelligence and awareness of these market and grid fluctuations allows the delivery of products/services at much more favorable conditions - reducing costs, reducing emissions and increasing renewable energy content are all possible. The aim of the research described in this paper is the development of algorithms which take advantage of variability observed in electricity markets to reduce the costs and emissions of services, and provide a way for service operators to insulate themselves against turbulent market conditions.","PeriodicalId":311325,"journal":{"name":"2013 IEEE Green Technologies Conference (GreenTech)","volume":"7 3","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Using Electricity Market Analytics to Reduce Cost and Environmental Impact\",\"authors\":\"Conor Kelly, A. Ruzzelli, E. Mangina\",\"doi\":\"10.1109/GREENTECH.2013.70\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In recent years, energy consumption has become a major issue in terms of cost, infrastructure requirements and emissions. In deregulated markets electricity prices, renewable energy contribution and emissions can vary substantially from hour to hour. These temporal variations introduce significant opportunities for any flexible energy consumer. A granular analysis of the Irish electricity market for the first four months of 2012 showed the large variations characteristic of deregulated electricity markets - the spot price spiked up to 985% of the average price, marginal emissions varied by up to 55% and renewable energy generation had a standard deviation of 11.78%. Strong correlations are observed between renewable generation and market prices - market prices reduced significantly with increased wind generation. Utilising intelligence and awareness of these market and grid fluctuations allows the delivery of products/services at much more favorable conditions - reducing costs, reducing emissions and increasing renewable energy content are all possible. The aim of the research described in this paper is the development of algorithms which take advantage of variability observed in electricity markets to reduce the costs and emissions of services, and provide a way for service operators to insulate themselves against turbulent market conditions.\",\"PeriodicalId\":311325,\"journal\":{\"name\":\"2013 IEEE Green Technologies Conference (GreenTech)\",\"volume\":\"7 3\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-04-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE Green Technologies Conference (GreenTech)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GREENTECH.2013.70\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE Green Technologies Conference (GreenTech)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GREENTECH.2013.70","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Using Electricity Market Analytics to Reduce Cost and Environmental Impact
In recent years, energy consumption has become a major issue in terms of cost, infrastructure requirements and emissions. In deregulated markets electricity prices, renewable energy contribution and emissions can vary substantially from hour to hour. These temporal variations introduce significant opportunities for any flexible energy consumer. A granular analysis of the Irish electricity market for the first four months of 2012 showed the large variations characteristic of deregulated electricity markets - the spot price spiked up to 985% of the average price, marginal emissions varied by up to 55% and renewable energy generation had a standard deviation of 11.78%. Strong correlations are observed between renewable generation and market prices - market prices reduced significantly with increased wind generation. Utilising intelligence and awareness of these market and grid fluctuations allows the delivery of products/services at much more favorable conditions - reducing costs, reducing emissions and increasing renewable energy content are all possible. The aim of the research described in this paper is the development of algorithms which take advantage of variability observed in electricity markets to reduce the costs and emissions of services, and provide a way for service operators to insulate themselves against turbulent market conditions.