<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>

COPY SCRIPT

For further information contact us at helpdesk@openaire.eu

Optimal Energy Storage System Control in a Smart Grid including Renewable Generation Units

descriptionPublicationkeyboard_double_arrow_right Article , Journal 17 Jan 2024 Italy Publisher:UK Zhende Publishing Limited CompanyJournal:RE&PQJ, volume 9 (issn: 2172-038X, eissn: 2172-038X,

Authors: ANDREOTTI, AMEDEO; CARPINELLI, GUIDO; MOTTOLA, FABIO;

doi: 10.24084/repqj09.388

handle: 11588/391038

Optimal Energy Storage System Control in a Smart Grid including Renewable Generation Units

- Summary
- Metrics

Abstract

The paper deals with energy storage systems applications in Smart Grids. Several services can be performed thanks to the energy storage systems use, with objectives aimed at meeting needs internal or external to the Smart Grid. Optimal nonlinear constrained problems can be formulated and properly solved in order to perform the services in the best economical and technical way. In this paper, optimal control strategies are proposed in order to allow the Smart Grid to minimize internal losses and to sell energy and ancillary services during high power prices periods. The procedure involves the formulation of optimal power flow problems; proper objective functions and constraints are imposed to satisfying the services that have to be carried out. A numerical application on a 30-bus low voltage Smart Grid shows the effectiveness of the proposed procedure.

Country

Italy

Related Organizations

University Federico II of Naples
Italy

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	5
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%