Paper Info
Title
Optimization of Operation and Control Strategies for Battery Energy Storage Systems by Evolutionary Algorithms.
Abstract
To support the utilization of renewable energies, an optimized operation of energy systems is important. Often, the use of battery energy storage systems is stated as one of the most important measures to support the integration of intermittent renewable energy sources into the energy system. Additionally, the complexity of the energy system with its many interdependent entities as well as the economic efficiency call for an elaborate dimensioning and control of these storage systems. In this paper, we present an approach that combines the forward-looking nature of optimization and prediction with the feedback control of closed-loop controllers. An evolutionary algorithm is used to determine the parameters for a closed-loop controller that controls the charging and discharging control strategy of a battery in a smart building. The simulation and evaluation of a smart residential building scenario demonstrates the ability to improve the operation and control of a battery energy storage system. The optimization of the control strategy allows for the optimization with respect to variable tariffs while being conducive for the integration of renewable energy sources into the energy system.
Year
DOI
Venue
2016
10.1007/978-3-319-31204-0_33
Lecture Notes in Computer Science
Keywords
Field
DocType
Energy management system,Smart building,Evolutionary algorithm,Battery energy storage system,Closed-loop control
Economic efficiency,Control theory,Mathematical optimization,Renewable energy,Evolutionary algorithm,Computer science,Control engineering,Building automation,Energy management system,Battery (electricity),Dimensioning
Conference
Volume
ISSN
Citations 
9597
0302-9743
1
PageRank 
References 
Authors
0.43
8
4
Name
Order
Citations
PageRank
Jan Müller151.34
Matthias März210.43
Ingo Mauser3175.81
Hartmut Schmeck41034120.58