Optimal Active Energy Loss with Feeder Routing and Renewable Energy for Smart Grid Distribution
DOI:
https://doi.org/10.6000/1929-7092.2017.06.26Keywords:
Minimal active power loss, Backward / Forward Sweep Method, Harmony Search, Artificial Bee Colony, Particle Swarm OptimizationAbstract
Electric power is the main energy source for a modern society. Good management of electric power cycle is essential for a sustainable society. The electric power cycle is composed of Generation, Transmission, Distribution, and Consumption. Smart Grid (SG) is a system that integrated traditional grids with Information and Communication Technology (ICT). In addition, SG has the ability to integrate electrical power supply from both to main power substation and Distributed Generation (DG), which compensates for the power demand during peak times. However, SG still has a similar problem to the original grid in terms of active power loss, from electric current injecting through the transmission line. This paper solves the active power loss problem by feeder routing using the Adjusting Dijkstra's Cost Method, follow by deciding the allocation position and sizing of DG by the use of Evolutionary Computing, namely Harmony Search (HS), Artificial Bee Colony (ABC), and Particle Swarm Optimization (PSO). The experiments evaluate the performance of the algorithm using power flow analysis, Backward / Forward Sweep Method, on the IEEE 33 bus system. From the experimental results, PSO provides the best performance. The overall active power loss in the cases of 3 DGs was reduced from 202.67 to 52.29 kW, representing a reduction of 74.20%.References
Abdel-Akher M. (2013), Voltage Stability Analysis of Unbalanced Distribution Systems Using Backward / Forward Sweep Load-Flow Analysis Method with Secant Predictor, IET Generation, Transmission & Distribution, 7, 309-317.
https://doi.org/10.1049/iet-gtd.2012.0360
Alafnan H., Zhao J., Ma W. 2016. Prevention of overvoltage induced by large penetration of photovoltaics in distribution networks by electric vehicles, IEEE Transportation Electrification Conference and Expo, Asia-Pacific, 2016, pp. 525-530.
https://doi.org/10.1109/itec-ap.2016.7513010
Aswini E., Seshu M. (2016), Placement of Renewable Distributed Generation Using Harmony Search Optimization Technique,
International Journal of Innovative Research in Science Engineering and Technology, 5, 1914-1924.
Baran M. E., Wu F. F. (1989), Network Reconfiguration in Distribution Systems for Loss Reduction and Load Balancing, IEEE Transactions on Power Delivery, 4(2), 1401-1407.
https://doi.org/10.1109/61.25627
Esmaeilian H. R., Fadaeinedjad R. (2015), Energy Loss Minimization in Distribution Systems Utilizing an Enhanced Reconfiguration Method Integrating Distributed Generation, IEEE Systems Journal, 9, 1430-1439.
https://doi.org/10.1109/JSYST.2014.2341579
Fahad A., Mohamed E. (2009), Modified Artificial Bee Colony Algorithm for Optimal Distributed Generation Sizing and Allocation in Distribution Systems, Electrical Power and Energy Conference, 2009, pp. 1-9.
Farhadi P., Ghadimi N., Sojoudi T. (2013), Distributed Generation Allocation in Radial Distribution Systems Using Various Particle Swarm Optimization Techniques, Przegl?d Elektrotechniczny, 89, 261-265.
Guerriche K. R., Bouktir T. (2015), Optimal Allocation and Sizing of Distributed Generation with Particle Swarm, Revue des Sciences et de la Technologie, 6, 59-69.
Huang X., Zhang Y., Huang H. (2014), Automatic Reactive Power Control in Distribution Network Based on Feeder Power Factor Assessment, IEEE Region 10 Symposium, Indonesia, pp. 1-4.
Jena S., Chauhan S. (2016), Solving Distribution Feeder Reconfiguration and Concurrent DG Installation Problems for Power Loss Minimization by Multi Swarm Cooperative PSO Algorithm, Proceeding of the IEEE/PES Transmission and Distribution Conference and Exposition, July 2016, pp. 1-9.
https://doi.org/10.1109/tdc.2016.7520021
Jha, P., Vidyasagar, S. (2013), Dijkstra Algorithm for Feeder Routing of Radial Distribution System, IOSR Journal of Engineering, January 2013, 1-6.
Priya P. S., Reddy C. K. (2013), Optimal Placement of the DG in Radial Distribution System to Improve the Voltage Profile, International Journal of Science and Research (IJSR), 4, 2310-2315.
Rao R. S., Ravindra K., Satish K., Narasimham S.V.L. (2013), Power Loss Minimization in Distribution System Using Network Reconfiguration in the Presence of Distributed Generation, IEEE Transactions on Power Systems, 28, 317-325.
https://doi.org/10.1109/TPWRS.2012.2197227
Tolabi H, B., Ali M. H., Rizwan M. (2015), Simultaneous Reconfiguration, Optimal Placement f DSTATCOM, and Photovoltaic Array in a Distribution System Based on Fuzzy-ACO Approach, IEEE Transactions on Sustainable Energy, 6, 210-218.
https://doi.org/10.1109/TSTE.2014.2364230
https://doi.org/10.1049/iet-gtd.2012.0360
Alafnan H., Zhao J., Ma W. 2016. Prevention of overvoltage induced by large penetration of photovoltaics in distribution networks by electric vehicles, IEEE Transportation Electrification Conference and Expo, Asia-Pacific, 2016, pp. 525-530.
https://doi.org/10.1109/itec-ap.2016.7513010
Aswini E., Seshu M. (2016), Placement of Renewable Distributed Generation Using Harmony Search Optimization Technique,
International Journal of Innovative Research in Science Engineering and Technology, 5, 1914-1924.
Baran M. E., Wu F. F. (1989), Network Reconfiguration in Distribution Systems for Loss Reduction and Load Balancing, IEEE Transactions on Power Delivery, 4(2), 1401-1407.
https://doi.org/10.1109/61.25627
Esmaeilian H. R., Fadaeinedjad R. (2015), Energy Loss Minimization in Distribution Systems Utilizing an Enhanced Reconfiguration Method Integrating Distributed Generation, IEEE Systems Journal, 9, 1430-1439.
https://doi.org/10.1109/JSYST.2014.2341579
Fahad A., Mohamed E. (2009), Modified Artificial Bee Colony Algorithm for Optimal Distributed Generation Sizing and Allocation in Distribution Systems, Electrical Power and Energy Conference, 2009, pp. 1-9.
Farhadi P., Ghadimi N., Sojoudi T. (2013), Distributed Generation Allocation in Radial Distribution Systems Using Various Particle Swarm Optimization Techniques, Przegl?d Elektrotechniczny, 89, 261-265.
Guerriche K. R., Bouktir T. (2015), Optimal Allocation and Sizing of Distributed Generation with Particle Swarm, Revue des Sciences et de la Technologie, 6, 59-69.
Huang X., Zhang Y., Huang H. (2014), Automatic Reactive Power Control in Distribution Network Based on Feeder Power Factor Assessment, IEEE Region 10 Symposium, Indonesia, pp. 1-4.
Jena S., Chauhan S. (2016), Solving Distribution Feeder Reconfiguration and Concurrent DG Installation Problems for Power Loss Minimization by Multi Swarm Cooperative PSO Algorithm, Proceeding of the IEEE/PES Transmission and Distribution Conference and Exposition, July 2016, pp. 1-9.
https://doi.org/10.1109/tdc.2016.7520021
Jha, P., Vidyasagar, S. (2013), Dijkstra Algorithm for Feeder Routing of Radial Distribution System, IOSR Journal of Engineering, January 2013, 1-6.
Priya P. S., Reddy C. K. (2013), Optimal Placement of the DG in Radial Distribution System to Improve the Voltage Profile, International Journal of Science and Research (IJSR), 4, 2310-2315.
Rao R. S., Ravindra K., Satish K., Narasimham S.V.L. (2013), Power Loss Minimization in Distribution System Using Network Reconfiguration in the Presence of Distributed Generation, IEEE Transactions on Power Systems, 28, 317-325.
https://doi.org/10.1109/TPWRS.2012.2197227
Tolabi H, B., Ali M. H., Rizwan M. (2015), Simultaneous Reconfiguration, Optimal Placement f DSTATCOM, and Photovoltaic Array in a Distribution System Based on Fuzzy-ACO Approach, IEEE Transactions on Sustainable Energy, 6, 210-218.
https://doi.org/10.1109/TSTE.2014.2364230
Downloads
Published
2017-06-09
How to Cite
Phawanaphinyo, P., Keeratipranon, N., & Khemapatapan, C. (2017). Optimal Active Energy Loss with Feeder Routing and Renewable Energy for Smart Grid Distribution. Journal of Reviews on Global Economics, 6, 269–278. https://doi.org/10.6000/1929-7092.2017.06.26
Issue
Section
Special Issue - Recent Topical Research on Global, Energy, Health & Medical, and Tourism Economics, and Global Software
License
Policy for Journals/Articles with Open Access
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are permitted and encouraged to post links to their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work
Policy for Journals / Manuscript with Paid Access
Authors who publish with this journal agree to the following terms:
- Publisher retain copyright .
- Authors are permitted and encouraged to post links to their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work .
