Abstract
Reliable and efficient distributed algorithms for power restoration are essential for self-healing electrical smart grids. Therefore, this paper presents a Multi-Agent System (MAS) for automatic restoration in power distribution networks. Moreover, as electrical demand fluctuates on the hourly and daily basis, an ensemble learning algorithm has been adopted for short-term forecasting of electrical energy demand. The prediction methodology is incorporated into the restoration algorithm in order to obtain a capacity-based restoration solution. Experiments carried out in two electrical networks demonstrate the importance and accuracy of the demand prediction algorithm and the feasibility of the MAS for system reconfiguration in decentralized power utilities.
Original language | English |
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Title of host publication | 2015 18th International Conference on Intelligent System Application to Power Systems, ISAP 2015 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781509001903 |
DOIs | |
State | Published - 10 11 2015 |
Externally published | Yes |
Event | 18th International Conference on Intelligent System Application to Power Systems, ISAP 2015 - Porto, Portugal Duration: 11 09 2015 → 17 09 2015 |
Publication series
Name | 2015 18th International Conference on Intelligent System Application to Power Systems, ISAP 2015 |
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Conference
Conference | 18th International Conference on Intelligent System Application to Power Systems, ISAP 2015 |
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Country/Territory | Portugal |
City | Porto |
Period | 11/09/15 → 17/09/15 |
Bibliographical note
Publisher Copyright:© 2015 IEEE.
Keywords
- Automatic Power Restoration
- Distributed Artificial Intelligence
- Ensemble Learning
- Short-Term Demand Forecasting