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

Socpus ID

84893168457 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84893168457

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