An energy supervision for distributed storage systems to optimize the provision of multiple services

This paper presents an innovative supervisory control for distributed energy storage systems that is able to 1) perform day-ahead scheduling of storage services to maximize profitability while satisfying material and grid constraints and 2) identify the intraday schedule changes that are required in order to take various contingencies into account. Several case studies have been carried out to test this advanced energy supervision. The considered storage system is connected to a rural medium-voltage distribution feeder with a high penetration of wind turbines. This work has made possible to identify several technical, economic and regulatory issues that seem critical to the emergence of distributed energy storage systems.

[1]  J. S. Christensen,et al.  Probabilistic load flow calculation using Monte Carlo techniques for distribution network with wind turbines , 1998, 8th International Conference on Harmonics and Quality of Power. Proceedings (Cat. No.98EX227).

[2]  Joshua Stein,et al.  Technology development needs for integrated grid-connected PV systems and electric energy storage , 2009, 2009 34th IEEE Photovoltaic Specialists Conference (PVSC).

[3]  The Natural Duration of Lung Cancer. , 1955, Canadian Medical Association journal.

[4]  Georgianne Huff Peek,et al.  NAS battery demonstration at American Electric Power:a study for the DOE energy storage program. , 2006 .

[5]  KyungMann Kim,et al.  Contrasting treatment‐specific survival using double‐robust estimators , 2012 .

[6]  Gilles Malarange,et al.  Energy storage systems in distribution grids: New assets to upgrade distribution network abilities , 2009 .

[7]  P. Rodriguez,et al.  Overview of the energy storage systems for wind power integration enhancement , 2010, 2010 IEEE International Symposium on Industrial Electronics.

[8]  G. Delille,et al.  Contribution du Stockage à la Gestion Avancée des Systèmes Électriques : approches Organisationnelles et Technico-économiques dans les Réseaux de Distribution , 2010 .

[9]  E. Kaplan,et al.  Nonparametric Estimation from Incomplete Observations , 1958 .

[10]  Juan Carlos Balda,et al.  Smart grid applications of selected energy storage technologies , 2012, 2012 IEEE PES Innovative Smart Grid Technologies (ISGT).