Title
Adaptive Dynamic Programming Algorithm for Renewable Energy Scheduling and Battery Management.
Abstract
The employment of intelligent energy management systems likely allows reducing consumptions and thus saving money for consumers. The residential load demand must be met, and some advantages can be obtained if specific optimization policies are taken. With an efficient use of renewable sources and power imported from the grid, an intelligent and adaptive system which manages the battery is able to satisfy the load demand and minimize the entire energy cost related to the scenario under study. In this paper, an adaptive dynamic programming-based algorithm is presented to face dynamic situations, in which some conditions of the environment or habits of customer may vary with time, especially using renewable energy. Based on the idea of smart grid, we propose an intelligent management scheme for renewable resources combined with battery implemented with a faster and simpler scheme of dynamic programming, by considering only one critic network and some optimization policies in order to satisfy the load demand. Since this kind of problem is suitable to avoid the training of an action network, the training loop among the two neural networks is deleted and the training process is greatly simplified. Computer simulations confirm the effectiveness of this self-learning design in a typical residential scenario. © 2012 Springer Science+Business Media, LLC.
Year
DOI
Venue
2013
10.1007/s12559-012-9191-y
Cognitive Computation
Keywords
Field
DocType
Adaptive dynamic programming,Approximate dynamic programming,Neural networks,Energy scheduling,Battery management
Renewable energy,Scheduling (computing),Computer science,Real-time computing,Artificial intelligence,Artificial neural network,Distributed computing,Energy management,Dynamic programming,Smart grid,Adaptive system,Grid,Machine learning
Journal
Volume
Issue
ISSN
5
2
18669964
Citations 
PageRank 
References 
21
1.05
14
Authors
6
Name
Order
Citations
PageRank
Matteo Boaro1906.00
Danilo Fuselli2906.00
Francesco De Angelis316018.09
Derong Liu45457286.88
Qinglai Wei52494110.44
Francesco Piazza6673100.48