{"title":"REliable energy supply and voltage control for hybrid microgrid by pid controlled with integrating of an EV charging station","authors":"Elmehdi Nasri, Tarik Jarou, Salma Benchikh, Younes Elkoudia","doi":"10.29354/diag/174145","DOIUrl":null,"url":null,"abstract":"The integration of an electric vehicle (EV) charging station into the DC-microgrid requires management control of the energy supply and the voltage variation. The hybrid energy sources of the microgrid consist of battery storage, wind energy, and photovoltaic (PV) energy sources. To optimize power generation from renewable energy sources such as wind and PV, the source-side converters (SSCs) are regulated by the leading edge intelligent PID technique. This strategy enhances the quality of power delivered to the DC-microgrid. The microgrid comprises AC/DC loads, battery storage, EV charging stations, backup power from the main grid, and renewable energy supplies comprising wind and solar energy. The proposed control system relies on monitoring the state of charge of the battery and utilizing renewable energy sources to supply loads efficiently. The final results of the simulation obtained from the simulation software MATLAB and Simulink are used to validate the effectiveness of the suggested energy control technique, which performs well in terms of accurate control and maintaining a stable energy supply even under various load and weather conditions.","PeriodicalId":52164,"journal":{"name":"Diagnostyka","volume":"303 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Diagnostyka","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.29354/diag/174145","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 0
Abstract
The integration of an electric vehicle (EV) charging station into the DC-microgrid requires management control of the energy supply and the voltage variation. The hybrid energy sources of the microgrid consist of battery storage, wind energy, and photovoltaic (PV) energy sources. To optimize power generation from renewable energy sources such as wind and PV, the source-side converters (SSCs) are regulated by the leading edge intelligent PID technique. This strategy enhances the quality of power delivered to the DC-microgrid. The microgrid comprises AC/DC loads, battery storage, EV charging stations, backup power from the main grid, and renewable energy supplies comprising wind and solar energy. The proposed control system relies on monitoring the state of charge of the battery and utilizing renewable energy sources to supply loads efficiently. The final results of the simulation obtained from the simulation software MATLAB and Simulink are used to validate the effectiveness of the suggested energy control technique, which performs well in terms of accurate control and maintaining a stable energy supply even under various load and weather conditions.
期刊介绍:
Diagnostyka – is a quarterly published by the Polish Society of Technical Diagnostics (PSTD). The journal “Diagnostyka” was established by the decision of the Presidium of Main Board of the Polish Society of Technical Diagnostics on August, 21st 2000 and replaced published since 1990 reference book of the PSTD named “Diagnosta”. In the years 2000-2003 there were issued annually two numbers of the journal, since 2004 “Diagnostyka” is issued as a quarterly. Research areas covered include: -theory of the technical diagnostics, -experimental diagnostic research of processes, objects and systems, -analytical, symptom and simulation models of technical objects, -algorithms, methods and devices for diagnosing, prognosis and genesis of condition of technical objects, -methods for detection, localization and identification of damages of technical objects, -artificial intelligence in diagnostics, neural nets, fuzzy systems, genetic algorithms, expert systems, -application of technical diagnostics, -diagnostic issues in mechanical and civil engineering, -medical and biological diagnostics with signal processing application, -structural health monitoring, -machines, -noise and vibration, -analysis of technical and civil systems.