Elyar Asadzadeh Aghdam , Sahar Moslemi , Mohammad Sadegh Nakisaee , Mahan Fakhrooeian , Ali Jawad Kadhim Al-Hassanawy , Milad Hadizadeh Masali , Abbas Zare Ghaleh Seyyedi
{"title":"基于 IGDT 的新鲁棒性模型,用于集成压缩空气储能和变压器与线路动态额定值的智能电力系统的日前调度","authors":"Elyar Asadzadeh Aghdam , Sahar Moslemi , Mohammad Sadegh Nakisaee , Mahan Fakhrooeian , Ali Jawad Kadhim Al-Hassanawy , Milad Hadizadeh Masali , Abbas Zare Ghaleh Seyyedi","doi":"10.1016/j.est.2024.114695","DOIUrl":null,"url":null,"abstract":"<div><div>Growing concerns about climate change have driven power system operators worldwide to utilize wind energy as clean and affordable energy. High penetration of wind energy along with high power consumption of consumers can cause congestion in the transmission network which in turn cause wind spillage, load shedding and high operation cost. Motivated by this challenge, compressed air energy storage (CAES), dynamic transformer rating (DTR) and dynamic line rating (DLR) are three smart technologies that are considered as ways to increase the flexibility of the electrical network and decrease wind spillage and load shedding. With DTR and DLR technologies, the real capacity of transformers and lines is determined which is dependent on weather parameters. Hence, this study proposes a day-ahead scheduling based on the AC power flow model for smart power system taking CAES, DLR and DTR into account. The aim of this model is to minimize load shedding, wind spillage, total cost and emissions. Uncertainties of wind energy (which has a great impact on day-ahead scheduling and capacity of lines with DLR) and electrical load, are handled through an improved form of the information gap decision theory (IGDT), hereafter called weighted IGDT (WIGDT)-based robust model. The effectiveness of the introduced method is evaluated by testing on IEEE 24-bus system. According to obtained results, simultaneous used of CAES, DTR and DLR can reduce wind spillage, load shedding, emission and operation cost and also improve the voltage profile.</div></div>","PeriodicalId":15942,"journal":{"name":"Journal of energy storage","volume":"105 ","pages":"Article 114695"},"PeriodicalIF":8.9000,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A new IGDT-based robust model for day-ahead scheduling of smart power system integrated with compressed air energy storage and dynamic rating of transformers and lines\",\"authors\":\"Elyar Asadzadeh Aghdam , Sahar Moslemi , Mohammad Sadegh Nakisaee , Mahan Fakhrooeian , Ali Jawad Kadhim Al-Hassanawy , Milad Hadizadeh Masali , Abbas Zare Ghaleh Seyyedi\",\"doi\":\"10.1016/j.est.2024.114695\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Growing concerns about climate change have driven power system operators worldwide to utilize wind energy as clean and affordable energy. High penetration of wind energy along with high power consumption of consumers can cause congestion in the transmission network which in turn cause wind spillage, load shedding and high operation cost. Motivated by this challenge, compressed air energy storage (CAES), dynamic transformer rating (DTR) and dynamic line rating (DLR) are three smart technologies that are considered as ways to increase the flexibility of the electrical network and decrease wind spillage and load shedding. With DTR and DLR technologies, the real capacity of transformers and lines is determined which is dependent on weather parameters. Hence, this study proposes a day-ahead scheduling based on the AC power flow model for smart power system taking CAES, DLR and DTR into account. The aim of this model is to minimize load shedding, wind spillage, total cost and emissions. Uncertainties of wind energy (which has a great impact on day-ahead scheduling and capacity of lines with DLR) and electrical load, are handled through an improved form of the information gap decision theory (IGDT), hereafter called weighted IGDT (WIGDT)-based robust model. The effectiveness of the introduced method is evaluated by testing on IEEE 24-bus system. According to obtained results, simultaneous used of CAES, DTR and DLR can reduce wind spillage, load shedding, emission and operation cost and also improve the voltage profile.</div></div>\",\"PeriodicalId\":15942,\"journal\":{\"name\":\"Journal of energy storage\",\"volume\":\"105 \",\"pages\":\"Article 114695\"},\"PeriodicalIF\":8.9000,\"publicationDate\":\"2024-11-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of energy storage\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352152X24042816\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of energy storage","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352152X24042816","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
A new IGDT-based robust model for day-ahead scheduling of smart power system integrated with compressed air energy storage and dynamic rating of transformers and lines
Growing concerns about climate change have driven power system operators worldwide to utilize wind energy as clean and affordable energy. High penetration of wind energy along with high power consumption of consumers can cause congestion in the transmission network which in turn cause wind spillage, load shedding and high operation cost. Motivated by this challenge, compressed air energy storage (CAES), dynamic transformer rating (DTR) and dynamic line rating (DLR) are three smart technologies that are considered as ways to increase the flexibility of the electrical network and decrease wind spillage and load shedding. With DTR and DLR technologies, the real capacity of transformers and lines is determined which is dependent on weather parameters. Hence, this study proposes a day-ahead scheduling based on the AC power flow model for smart power system taking CAES, DLR and DTR into account. The aim of this model is to minimize load shedding, wind spillage, total cost and emissions. Uncertainties of wind energy (which has a great impact on day-ahead scheduling and capacity of lines with DLR) and electrical load, are handled through an improved form of the information gap decision theory (IGDT), hereafter called weighted IGDT (WIGDT)-based robust model. The effectiveness of the introduced method is evaluated by testing on IEEE 24-bus system. According to obtained results, simultaneous used of CAES, DTR and DLR can reduce wind spillage, load shedding, emission and operation cost and also improve the voltage profile.
期刊介绍:
Journal of energy storage focusses on all aspects of energy storage, in particular systems integration, electric grid integration, modelling and analysis, novel energy storage technologies, sizing and management strategies, business models for operation of storage systems and energy storage developments worldwide.