Microgrid bss scheduling using teaching learning based optimization algorithm (Record no. 20891)
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| fixed length control field | a |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240419150955.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 240419b xxu||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | AIKTC-KRRC |
| Transcribing agency | AIKTC-KRRC |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| 9 (RLIN) | 23228 |
| Author | Sravani, Yendru |
| 245 ## - TITLE STATEMENT | |
| Title | Microgrid bss scheduling using teaching learning based optimization algorithm |
| 250 ## - EDITION STATEMENT | |
| Volume, Issue number | Vol.12(2), Dec |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Chennai |
| Name of publisher, distributor, etc. | IASET : International Academy of Science, Engineering and Technology |
| Year | 2023 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Pagination | 1-10p. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Energy storage serves as a crucial hub for the entire grid, supplementing resources such as wind, solar, and hydropower, as well as nuclear and fossil fuels, demand side resources, and system efficiency assets. It can function as a generation, transmission, or distribution asset — all in one unit. Storage is, in the end, an enabling technology. It has the potential to save consumers money while also improving reliability and resilience, integrating power sources, and reducing environmental impacts. Battery storage system design is now important for microgrids to prepare a day-ahead schedule for steady operation. This article discusses the scheduling of BSS, which helps to reduce the average cost imposed on microgrid consumers in the context of dynamic pricing. For minimizing, a cost function is created and subjected to optimization based on the restrictions. The search space magnification is 50*(DC– DD + 1), where DC and DD are the maximum charge and discharge depths in an hour in percentage for a specific BSS, respectively. The programming is done by combining daily load, generated energy, and grid price forecasts with a microgrid size as specified in the article and implementing Teaching Learning Based Optimization (TLBO) for achieving an average cost reduction when compared to Net Power Based Algorithm and Particle Swarm Optimization for a planned BSS. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| 9 (RLIN) | 4623 |
| Topical term or geographic name entry element | Electrical Engineering |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| 9 (RLIN) | 23250 |
| Co-Author | Kumrai, M. Veera |
| 773 0# - HOST ITEM ENTRY | |
| International Standard Serial Number | 2278-9944 |
| Place, publisher, and date of publication | Chennai International Academy of Science , Engineering and Technology (IASET) |
| Title | International journal of electrical and electronics engineering (IJEEE) |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| URL | https://www.iaset.us/journals/international-journals/international-journal-of-electrical-and-electronics-engineering |
| Link text | Click here |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | |
| Koha item type | Articles Abstract Database |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Permanent Location | Current Location | Shelving location | Date acquired | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| School of Engineering & Technology | School of Engineering & Technology | Archieval Section | 2024-04-19 | 2024-0449 | 2024-04-19 | 2024-04-19 | Articles Abstract Database |