Title
Energy Management For A Grid-Tied Photovoltaic-Wind-Storage System - Part Ii: Operation Strategy
Keywords
Artificial neural networks (ANNs); distributed generation (DG); energy storage system (ESS); load forecasting model; photovoltaic (PV); solar radiation forecasting model
Abstract
Renewable energy has unique characteristics such as it is sustainable, clean and free. However, renewable generation systems have two major limitations: they are strongly dependent on the weather conditions; and they have unsynchronized generation peaks with the demand peaks, in general. In a series of two papers, an energy management strategy for a distributed photovoltaic (PV)-wind-storage system is proposed. This second paper proposes a strategy to control the operation of the energy storage to overcome the limitations of renewable sources and forecasting models uncertainty. The proposed operation strategy is advantageous in terms of it allows a highly efficient and profitable operation of the system especially in an electricity spot market. Simulation results that shows the effectiveness of the proposed control strategy are provided. © 2013 IEEE.
Publication Date
12-1-2013
Publication Title
IEEE Power and Energy Society General Meeting
Number of Pages
-
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/PESMG.2013.6672414
Copyright Status
Unknown
Socpus ID
84893168457 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84893168457
STARS Citation
Hussein, Ala A. and Batarseh, Issa, "Energy Management For A Grid-Tied Photovoltaic-Wind-Storage System - Part Ii: Operation Strategy" (2013). Scopus Export 2010-2014. 5844.
https://stars.library.ucf.edu/scopus2010/5844