Power flow management of hybrid system in smart grid requirements using ITSA-MOAT approach. (1st August 2022)
- Record Type:
- Journal Article
- Title:
- Power flow management of hybrid system in smart grid requirements using ITSA-MOAT approach. (1st August 2022)
- Main Title:
- Power flow management of hybrid system in smart grid requirements using ITSA-MOAT approach
- Authors:
- Logeswaran, T.
Senthil Raja, M.
Beevi Sahul Hameed, Jennathu
Abdulrahim, Mahabuba - Abstract:
- Highlights: A power flow management (PFM) concept of photovoltaic/fuel cell/battery/super capacitor in smart grid (SG) system is proposed in this paper. The proposed system controls the photovoltaic (PV) system, battery storage, fuel cell (FC) and super capacitor (SC). The proposed control system is the combination of Improved Tunicate Swarm Optimization (ITSA) and Multi Objective Artificial Tree (MOAT), hence it is called ITSA-MOAT method. Abstract: A power flow management (PFM) concept of Photovoltaic/Fuel Cell/Battery/Super capacitor in smart grid (SG) system is proposed in this paper. The proposed system controls the photovoltaic (PV) system, battery storage, fuel cell (FC) and super capacitor (SC). The proposed control system is the combination of Improved Tunicate Swarm Optimization (ITSA) and Multi Objective Artificial Tree (MOAT), hence it is called ITSA-MOAT method. Here, ITSA is building up the control pulses of the inverter using the energy exchange assortment between the source and load side. Here, the composition of multi-objective function is considered according to the obtainable source power and several specified grid produced by the active power and reactive power. To acquire the online control pulses, MOAT is utilized based on the variants of power. Moreover, the global state of charge (SoC) of energy storages and load demand are considered. The ITSA-MOAT method is implemented in MATLAB/Simulink platform. By then, the experimental results of the proposedHighlights: A power flow management (PFM) concept of photovoltaic/fuel cell/battery/super capacitor in smart grid (SG) system is proposed in this paper. The proposed system controls the photovoltaic (PV) system, battery storage, fuel cell (FC) and super capacitor (SC). The proposed control system is the combination of Improved Tunicate Swarm Optimization (ITSA) and Multi Objective Artificial Tree (MOAT), hence it is called ITSA-MOAT method. Abstract: A power flow management (PFM) concept of Photovoltaic/Fuel Cell/Battery/Super capacitor in smart grid (SG) system is proposed in this paper. The proposed system controls the photovoltaic (PV) system, battery storage, fuel cell (FC) and super capacitor (SC). The proposed control system is the combination of Improved Tunicate Swarm Optimization (ITSA) and Multi Objective Artificial Tree (MOAT), hence it is called ITSA-MOAT method. Here, ITSA is building up the control pulses of the inverter using the energy exchange assortment between the source and load side. Here, the composition of multi-objective function is considered according to the obtainable source power and several specified grid produced by the active power and reactive power. To acquire the online control pulses, MOAT is utilized based on the variants of power. Moreover, the global state of charge (SoC) of energy storages and load demand are considered. The ITSA-MOAT method is implemented in MATLAB/Simulink platform. By then, the experimental results of the proposed method are analyzed with the existing methods. … (more)
- Is Part Of:
- Applied energy. Volume 319(2022)
- Journal:
- Applied energy
- Issue:
- Volume 319(2022)
- Issue Display:
- Volume 319, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 319
- Issue:
- 2022
- Issue Sort Value:
- 2022-0319-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-08-01
- Subjects:
- Power flow management -- Smart grid -- Control signals -- Active power and reactive power varieties -- Multi-objective function
Power (Mechanics) -- Periodicals
Energy conservation -- Periodicals
Energy conversion -- Periodicals
621.042 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03062619 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.apenergy.2022.119228 ↗
- Languages:
- English
- ISSNs:
- 0306-2619
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1572.300000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 21600.xml