Optimizing Daily Operation of Battery Energy Storage Systems Under Real-Time Pricing Schemes

Modernization of electricity networks is currently being carried out using the concept of the smart grid; hence, the active participation of end-user consumers and distributed generators will be allowed in order to increase system efficiency and renewable power accommodation. In this context, this p...

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Bibliographic Details
Published inIEEE transactions on smart grid Vol. 8; no. 1; pp. 316 - 330
Main Authors Lujano-Rojas, Juan M., Dufo-Lopez, Rodolfo, Bernal-Agustin, Jose L., Catalao, Joao P. S.
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 01.01.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Batteries
battery energy storage system
Distributed generation
Efficiency
Electric power systems
Electricity
electricity price forecasting
Energy conversion efficiency
Energy storage
Forecasting
Genetic algorithms
Indexes
Lead acid batteries
lead-acid battery
Modernization
Optimization
Power converters
Pricing
Real time
real-time pricing
Real-time systems
Smart grid
State of charge
Storage systems
Time of use electricity pricing
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Summary:Modernization of electricity networks is currently being carried out using the concept of the smart grid; hence, the active participation of end-user consumers and distributed generators will be allowed in order to increase system efficiency and renewable power accommodation. In this context, this paper proposes a comprehensive methodology to optimally control lead-acid batteries operating under dynamic pricing schemes in both independent and aggregated ways, taking into account the effects of the charge controller operation, the variable efficiency of the power converter, and the maximum capacity of the electricity network. A genetic algorithm is used to solve the optimization problem in which the daily net cost is minimized. The effectiveness and computational efficiency of the proposed methodology is illustrated using real data from the Spanish electricity market during 2014 and 2015 in order to evaluate the effects of forecasting error of energy prices, observing an important reduction in the estimated benefit as a result of both factors: 1) forecasting error and 2) power system limitations.
ISSN:1949-3053
1949-3061
DOI:10.1109/TSG.2016.2602268