Abstract
In this research work, we have developed an intelligent power management system using Artificial Neural Network (ANN) which will control load shedding automatically in a local distribution area and utilize different types of power generation units like conventional and non-conventional energy sources. If generation is not sufficient to meet the load demand, then ANN network will anticipate and predict when the load demand is greater than generation and will suggest specifically the area where load shedding would be appropriate. Utilizing and manipulating different types of seasonal and occasional load data (which is actually divided into different areas such as residential-load, industrial-load, commercial-load and VIP-load), we have designed the artificial neural network so that it will automatically show us the area where load-shedding would be preferable on the basis of priority. Hence, the priority is given by the area where maximum load-shedding is desired.
Original language | English |
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Title of host publication | Proceedings - 7th International Conference on Intelligent Systems, Modelling and Simulation, ISMS 2016 |
Editors | David Al-Dabass, Tiranee Achalakul, Rajchawit Sarochawikasit, Santitham Prom-On |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 25-30 |
Number of pages | 6 |
ISBN (Electronic) | 9781509006649 |
DOIs | |
Publication status | Published - 2017 |
Externally published | Yes |
Event | International Conference on Intelligent Systems, Modelling and Simulation 2016 - Bangkok, Thailand Duration: 25 Jan 2016 → 27 Jan 2016 Conference number: 7th https://ieeexplore.ieee.org/xpl/conhome/7875353/proceeding (Proceedings) |
Publication series
Name | Proceedings - International Conference on Intelligent Systems, Modelling and Simulation, ISMS |
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Volume | 0 |
ISSN (Print) | 2166-0662 |
ISSN (Electronic) | 2166-0670 |
Conference
Conference | International Conference on Intelligent Systems, Modelling and Simulation 2016 |
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Abbreviated title | ISMS 2016 |
Country/Territory | Thailand |
City | Bangkok |
Period | 25/01/16 → 27/01/16 |
Internet address |
Keywords
- Artificial Neural Network
- Error histogram
- Power System
- Regression Plot
- Solar Radiation
- Supervised Learning