caa a22 4500 606159533 CHVBK 20210128100625.0 cr unu---uuuuu 210128e20150401xx s 000 0 eng 10.1007/s00521-014-1715-9 doi (NATIONALLICENCE)springer-10.1007/s00521-014-1715-9 State of charge preventive control of storage device to stabilize VSI-based microgrid after islanding occurrence using ANN-based control [Elektronische Daten] [Hassan Khomami Pamsari, Seyed-Jalal Seyed-Shenava, Hossein Shayeghi] This paper presents an effective method to control the state of charge (SOC) of energy storage system (ESS) installed in a microgrid (MG). Considering voltage and frequency variations after islanding occurrence and based on the stability criteria, MG pre-islanding conditions are divided into secure and insecure classes. It is shown that insecure MG can become secure, if appropriate value for SOC of the ESS is chosen in different conditions of the MG. To select the most important variables of MG, which can estimate proper values of the SOC, a feature selection procedure known as RELIEF is used in this paper. Among all the MG variables, critical ones are selected. Using them, appropriate value of the SOC can be calculated for different conditions of the MG. This approach is economic because it does not change the result of optimal power flow (OPF). In some conditions, the proper control of SOC cannot solely make the MG secure. In these conditions, DGs generated power should be also changed to make the MG secure. This condition leads to a violation from OPF solution and increases the cost of operation. The results demonstrate the effectiveness of the proposed method in comparison with other methods. The Natural Computing Applications Forum, 2014 ANN-based control nationallicence Microgrid nationallicence Islanding nationallicence Khomami Pamsari Hassan Electrical Engineering Department, University of Mohaghegh Ardabili, Ardabil, Islamic Republic of Iran aut Seyed-Shenava Seyed-Jalal Electrical Engineering Department, University of Mohaghegh Ardabili, Ardabil, Islamic Republic of Iran aut Shayeghi Hossein Electrical Engineering Department, University of Mohaghegh Ardabili, Ardabil, Islamic Republic of Iran aut Neural Computing and Applications Springer London 26/3(2015-04-01), 669-677 0941-0643 26:3<669 2015 26 521 https://doi.org/10.1007/s00521-014-1715-9 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00521-014-1715-9 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Khomami Pamsari Hassan Electrical Engineering Department, University of Mohaghegh Ardabili, Ardabil, Islamic Republic of Iran aut NATIONALLICENCE 700 1- Seyed-Shenava Seyed-Jalal Electrical Engineering Department, University of Mohaghegh Ardabili, Ardabil, Islamic Republic of Iran aut NATIONALLICENCE 700 1- Shayeghi Hossein Electrical Engineering Department, University of Mohaghegh Ardabili, Ardabil, Islamic Republic of Iran aut NATIONALLICENCE 773 0- Neural Computing and Applications Springer London 26/3(2015-04-01), 669-677 0941-0643 26:3<669 2015 26 521