DocumentCode :
569993
Title :
Distributed ANNs in a layered architecture for energy management and maintenance scheduling of renewable energy HPS microgrids
Author :
Jaganmohan Reddy, Y. ; Pavan Kumar, Y.V. ; Sunil Kumar, V. ; Padma Raju, K.
Author_Institution :
Process Solutions-Autom. & Control Solutions, Honeywell Technol. Solutions Lab. (Pvt) Ltd., Hyderabad, India
fYear :
2012
fDate :
2-4 Aug. 2012
Firstpage :
1
Lastpage :
6
Abstract :
With increasing research on the field of alternative energy resources for sustainable development, more renewable energy sources are getting penetrated to the distributed network to form “microgrid”. This leads to more complexity in the distribution network in terms of energy management and realtime control. The objective of this paper is to design a system that forecasts the short (daily), medium (seasonal) and long term (yearly) load demand and the availability of energy resources at the microgrids. For scheduling the storage and transaction of electrical energy between neighboring microgrids, an energy management system (EMS) is designed. The EMS makes use of the forecasted data and real time data all together for managing an array of interconnected microgrids. The seasonal and yearly forecaster for a geographical boundary helps in maintenance scheduling and long term infrastructure development plan respectively. Recently, Artificial Neural Network (ANN) is found as a promising tool for statistical forecasting in real time applications. Hence, this paper makes use of ANN feature to forecast both load and availability of energy resources at microgrids in different scenarios like daily, seasonal, and yearly. The layered ANNs architecture is developed and trained with Levenberg-Marqurardt Back Propagation Algorithm. The entire design is simulated in MATLAB/Simulink. The proposed concept can be used in today´s real time energy infrastructure to prevent future energy crises with improved reliability and smooth coordination among microgrids located at different areas.
Keywords :
backpropagation; distributed power generation; energy management systems; energy storage; load forecasting; maintenance engineering; neural nets; power distribution reliability; power engineering computing; power generation scheduling; power system interconnection; power system management; renewable energy sources; sustainable development; EMS; Levenberg-Marqurardt back propagation algorithm; MATLAB-Simulink. simulation; artificial neural network; distributed network; electrical energy transaction; energy management system; geographical boundary forecasting; infrastructure development plan; layered ANN training architecture; load data forecasting; load demand; maintenance scheduling; microgrid interconnection; real-time control; reliability; renewable energy HPS microgrid; statistical forecasting; storage scheduling; sustainable development; Artificial neural networks; Energy management; Maintenance engineering; Solar radiation; Wind forecasting; Wind speed; Artificial Neural Networks (ANN); Energy Management System (EMS); Hybrid Power System (HPS); Load Forecasting; Microgrid controller (MC); Microgrids; Renewble energy sources;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Power Conversion and Energy Technologies (APCET), 2012 International Conference on
Conference_Location :
Mylavaram, Andhra Pradesh
Print_ISBN :
978-1-4673-2042-9
Type :
conf
DOI :
10.1109/APCET.2012.6302067
Filename :
6302067
Link To Document :
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