SMA-based optimal energy management study in a connected PV/MT/ DG/V2G/BESS/WT on IEEE-33 bus considering network losses and voltage deviations. Issue 3 (3rd April 2022)
- Record Type:
- Journal Article
- Title:
- SMA-based optimal energy management study in a connected PV/MT/ DG/V2G/BESS/WT on IEEE-33 bus considering network losses and voltage deviations. Issue 3 (3rd April 2022)
- Main Title:
- SMA-based optimal energy management study in a connected PV/MT/ DG/V2G/BESS/WT on IEEE-33 bus considering network losses and voltage deviations
- Authors:
- Behera, Sadasiva
Dev Choudhury, Nalin B. - Abstract:
- Abstract: The unpredictable nature of renewable energy resources (RERs) makes obtaining optimum operation and grid integration in today's smart power distribution networks challenging. Thus, to mitigate the fluctuations in RERs, the penetration of diesel generators, batteries, and electric vehicles (EV) must be considered for an effective energy management study (EMS) in the IEEE-33 bus system. This paper addresses the energy management of a microgrid linked to the main power system under deterministic and probabilistic circumstances. Apart from economic considerations, modern distribution networks must maintain an acceptable range of system reliability indexes. Failure of reliability in the distribution network may result in irreversible harm to the distribution network. For multi-objective functions such as cost reduction, voltage profile improvement, and voltage stability improvement are the main objectives of this article. An efficient method known as a novel slime mould algorithm (SMA) is used to solve these issues and validate the performance with the existing evolutionary algorithms. However, the SMA can optimally address the grid-connected various types of RERs installed, which can significantly compensate network losses, voltage deviations and improve the system performance. Finally, the algorithm's effectiveness on the EMS approach is verified under different algorithms through 2021a MATLAB/Simulink and the proposed methods prove the best results with theAbstract: The unpredictable nature of renewable energy resources (RERs) makes obtaining optimum operation and grid integration in today's smart power distribution networks challenging. Thus, to mitigate the fluctuations in RERs, the penetration of diesel generators, batteries, and electric vehicles (EV) must be considered for an effective energy management study (EMS) in the IEEE-33 bus system. This paper addresses the energy management of a microgrid linked to the main power system under deterministic and probabilistic circumstances. Apart from economic considerations, modern distribution networks must maintain an acceptable range of system reliability indexes. Failure of reliability in the distribution network may result in irreversible harm to the distribution network. For multi-objective functions such as cost reduction, voltage profile improvement, and voltage stability improvement are the main objectives of this article. An efficient method known as a novel slime mould algorithm (SMA) is used to solve these issues and validate the performance with the existing evolutionary algorithms. However, the SMA can optimally address the grid-connected various types of RERs installed, which can significantly compensate network losses, voltage deviations and improve the system performance. Finally, the algorithm's effectiveness on the EMS approach is verified under different algorithms through 2021a MATLAB/Simulink and the proposed methods prove the best results with the convergence of other algorithms also. … (more)
- Is Part Of:
- Journal of information & optimization sciences. Volume 43:Issue 3(2022)
- Journal:
- Journal of information & optimization sciences
- Issue:
- Volume 43:Issue 3(2022)
- Issue Display:
- Volume 43, Issue 3 (2022)
- Year:
- 2022
- Volume:
- 43
- Issue:
- 3
- Issue Sort Value:
- 2022-0043-0003-0000
- Page Start:
- 513
- Page End:
- 532
- Publication Date:
- 2022-04-03
- Subjects:
- 00xx
Energy management system -- Demand response -- Microgrid -- Renewable energy integration -- Slime mould algorithm -- HL-II reliability
Electronic data processing -- Periodicals
Information science -- Periodicals
Mathematical optimization -- Periodicals
519.6 - Journal URLs:
- http://www.tandfonline.com/toc/tios20/current ↗
http://www.tandfonline.com/action/journalInformation?show=aimsScope&journalCode=tios20 ↗ - DOI:
- 10.1080/02522667.2022.2042089 ↗
- Languages:
- English
- ISSNs:
- 0252-2667
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5006.745000
British Library STI - ELD Digital store - Ingest File:
- 22121.xml