Refine your search
Collections
Co-Authors
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Gan, Chin Kim
- Optimum Feeder Routing and Distribution Substation Placement and Sizing Using PSO and MST
Abstract Views :171 |
PDF Views:0
Authors
Affiliations
1 Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, 76100 Durian Tunggal, MY
2 Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, MY
1 Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, 76100 Durian Tunggal, MY
2 Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, MY
Source
Indian Journal of Science and Technology, Vol 7, No 10 (2014), Pagination: 1682-1689Abstract
A long term distribution network planning consists of several complexity aspects due to the multiple decision variables in objective functions. Optimum placement of distribution substations and determination of their sizing and feeder routing is one of major issues of distribution network planning. This paper proposes an algorithm to find the optimum distribution substation placement and sizing by utilizing the PSO algorithm and optimum feeder routing using modified MST. The proposed algorithm has been evaluated on the distribution network case with 500 consumers which are consisting of residential and commercial loads. The test network is generated by fractal based distribution network generation model software tool. The results indicate the proposed algorithm has been succeeded to find the reasonable placement and sizing of distributed generation with adequate feeder path.Keywords
Distribution Substation Placement, MST, MV & LV Feeder Routing, OpenDSS, PSO- Probabilistic Impact Assessment of Electric Vehicle Charging on Malaysia Low-Voltage Distribution Networks
Abstract Views :213 |
PDF Views:0
Authors
Affiliations
1 Universiti Teknikal Malaysia Melaka (UTeM), Melaka, MY
1 Universiti Teknikal Malaysia Melaka (UTeM), Melaka, MY
Source
Indian Journal of Science and Technology, Vol 8, No 3 (2015), Pagination: 199-207Abstract
The increasing number of Electric Vehicles (EV) charging on electricity distribution network could have a significant impact on the planning and operation of a power system network. This paper presents a case study investigating the impact of EV charging on a typical Malaysia residential Low-Voltage (LV) network by using OpenDSS as well as Monte-Carlo simulation approach. The residential LV network sample is provided by the local power utility (namely TNB). Some rearrangement of consumer load connection to feeders was made to comply with the utility requirement. In addition, the LV network has been modelled in detail to take into account the neutral wire and the self and mutual impedance of the cable. The impact of the EV charging on both newly developed residential areas and mature residential areas were evaluated in terms of voltage profile, voltage unbalance, feeders and transformer thermal limit as well as network losses. Results from the presented studies indicate that the LV network in Malaysia can safely accommodate up to 20% and 30% of EV penetration level for a mature residential area and newly developed residential area, respectively. Voltage unbalance and feeder's thermal loading overload are the main issues due to EV penetration. Furthermore, it is important to mention that the impact of EV is very locational and network dependent.Keywords
Artificial Feeding, Bakhazr County, Qanat, Migration Motivation.- Modelling and Analysis Fuel Cell with Battery Storage Microgrid System Based on Green Energy
Abstract Views :204 |
PDF Views:0
Authors
Alias Khamis
1,
Mohd Ruddin Ab. Ghani
1,
Chin Kim Gan
1,
Hairol Nizam Mohd Shah
1,
Mohd Zamzuri Ab. Rashid
1,
Mohd Khairi Mohd Zambri
1
Affiliations
1 Univerisiti Teknikal Malaysia Melaka, MY
1 Univerisiti Teknikal Malaysia Melaka, MY
Source
Indian Journal of Science and Technology, Vol 11, No 30 (2018), Pagination: 1-15Abstract
Objectives: This study is aimed at analyzing the characteristics of an 11 kV microgrid system when connected to a combination source of fuel cell and battery storage. Methods/Statistical Analysis: To do so, Matlab Simulink software was used as simulation platform. Three types of connection were simulated which are first; fuel cell to grid, second; battery storage to grid and lastly; combination of fuel cell and battery storage to grid1. Findings: For each connection type, parameters such voltage, current, active power and reactive power are recorded when the grid is either in connected or disconnected mode. Simulation results have shown positive values of active power and reactive power which flows from the source to the grid side in both modes. Application/Improvements: This implies that the combination of fuel cell and battery storage is a reliable source for a particular constructed microgrid system to be successful. If implemented in real application, the suggested microgrid system will be a dependable alternative to supply electricity to rural areas which are too remote and unfeasible to be connected to a conventional grid system.References
- Malhotra DP. Modelling and simulation of fuel cell based dc microgrid; 2014. p. 1–51.
- Ahmed M, Amin U, Aftab S, Ahmed Z. Integration of renewable energy resources in microgrid. Energy and Power Engineering. 2015; 7(1):12–29. https://doi.org/10.4236/ epe.2015.71002
- Chowdhury R, Boruah T. Design of a microgrid system in Matlab/Simulink. International Journal of Innovative Research in Science, Engineering and Technology. 2015; 4(7):1–8.
- Singh A, Surjan BS. Microgrid: A review. International Journal of Research in Engineering and Technology. 2014; 3(2):1–14.
- Krishna SV, Suman T. A new PV/fuel cell based bidirectional converter for microgrid applications. International Journal of Emerging Engineering Research and Technology. 2014; 2(5):121–9.
- Jaim R, Singh D, Kumar V. Design and modeling of fuel cell using Matlab Simulink. 2015; 2(8):19–22
- Feroldi D, Basualdo M. Description of PEM fuel cells system. Springer-Verlag London Limited; 2012. p. 1–25. https://doi.org/10.1007/978-1-84996-184-4_2
- Bahmani-Firouzi B. Optimal sizing of battery energy storage for microgrid operation management using a new improved Bat Algorithm. Electrical Power and Energy Systems. 2014; 56:42–54. https://doi.org/10.1016/j.ijepes.2013.10.019
- Aravindan P, Subbulakshmi G. Uninterrupted supply and frequency support for local load in Microgrid by Battery Energy Storage System (BESS). International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering. 2015; 4(2):1–7.
- Joseph A, Shahidehpour M. Battery storage systems in electric power systems. IEEE Power Engineering Society General Meeting; 2006. p. 1–8. https://doi.org/10.1109/ PES.2006.1709235
- Wu G, Sun H, Pan L. Lithium-ion battery. BYD Co Ltd Shenzhen BYD Auto R&D Co Ltd; 2014.