{"title":"Policies and Economic Efficiency for Distributed Photovoltaic and Energy Storage Industry","authors":"Xiuming Niu, Xu-feng Luo","doi":"10.13052/dgaej2156-3306.3846","DOIUrl":null,"url":null,"abstract":"The technique of directly converting solar energy into electricity using PV modules is distributed photovoltaic (PV) power generation. It is frequently used in a system and is referred to as a distributed PV power system. The system generates power in the surrounding areas and connects to the neighbouring utility grid. A distributed energy storage (DES) system is a bundled solution that stores energy for future use. In the short term, one of the most significant problems with solar power storage is that the batteries utilized for the application are still costly and giant. The more power requires the bigger battery must be. Further research revealed that maximizing solar and wind energies minimizes greenhouse gas emissions and lower the total cost of energy. The ability to store energy is crucial in balancing because it makes the grid more adaptable and stable. The mission of energy conservation and energy storage (ECES) aims to help integrate energy-storage technology research, production, deployment, and integration to improve the energy efficiency of all energy systems and enable the increased use of renewable energy in place of fossil fuels. Storage benefits are examined in terms of distribution transformer loads and storage support during energy fluctuations from renewable energy. However, the results show that the methodology’s recommended framework is successful and obtained with enhanced performance with a reliability of 95.6%. The proposed technique improves the Reliability analysis ratio of 95.4%, Performance analysis comparison ratio of 98.6%, accuracy analysis ratio of 91.3%, ECES model’s efficiency is estimated at 95.6%.","PeriodicalId":11205,"journal":{"name":"Distributed Generation & Alternative Energy Journal","volume":"22 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Distributed Generation & Alternative Energy Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.13052/dgaej2156-3306.3846","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The technique of directly converting solar energy into electricity using PV modules is distributed photovoltaic (PV) power generation. It is frequently used in a system and is referred to as a distributed PV power system. The system generates power in the surrounding areas and connects to the neighbouring utility grid. A distributed energy storage (DES) system is a bundled solution that stores energy for future use. In the short term, one of the most significant problems with solar power storage is that the batteries utilized for the application are still costly and giant. The more power requires the bigger battery must be. Further research revealed that maximizing solar and wind energies minimizes greenhouse gas emissions and lower the total cost of energy. The ability to store energy is crucial in balancing because it makes the grid more adaptable and stable. The mission of energy conservation and energy storage (ECES) aims to help integrate energy-storage technology research, production, deployment, and integration to improve the energy efficiency of all energy systems and enable the increased use of renewable energy in place of fossil fuels. Storage benefits are examined in terms of distribution transformer loads and storage support during energy fluctuations from renewable energy. However, the results show that the methodology’s recommended framework is successful and obtained with enhanced performance with a reliability of 95.6%. The proposed technique improves the Reliability analysis ratio of 95.4%, Performance analysis comparison ratio of 98.6%, accuracy analysis ratio of 91.3%, ECES model’s efficiency is estimated at 95.6%.