Distributed Settlement of Frequency Regulation Based on a Battery Energy Storage System

Battery energy storage systems (BESS) have wide applicability for frequency regulation services in power systems, owing to their fast response and flexibility. In this paper, a distributed method for frequency regulation based on the BESS is proposed, where the method includes two layers. The upper layer is a communication network composed of agents, which is used to transmit and process information, whilst the bottom layer comprises the power system with the BESS, which provides a frequency regulation service for the system. Furthermore, a set of fully distributed control laws for the BESS are derived from the proposed distributed method, where economic power dispatch and frequency recovery are simultaneously achieved. Finally, simulations were conducted to evaluate the effectiveness of the proposed method. The results show that the system frequency regulation and economic power dispatch are achieved after considering the limits of the battery state of charge and communication delays.

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Battery Energy Storage Systems for Primary Frequency Regulation in Island Power Systems

2020 IEEE/IAS 56th Industrial and Commercial Power Systems Technical Conference (I&CPS) ◽

10.1109/icps48389.2020.9176784 ◽

2020 ◽

Author(s):

O. A. Betancourt ◽

Z.G. Sanchez ◽

S.A. Saleh ◽

E.F. Hill ◽

X. Zhao ◽

...

Keyword(s):

Energy Storage ◽

Power Systems ◽

Storage Systems ◽

Frequency Regulation ◽

Energy Storage Systems ◽

Battery Energy Storage ◽

Battery Energy Storage Systems ◽

Battery Energy ◽

Primary Frequency

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An Intelligent Battery Energy Storage-Based Controller for Power Quality Improvement in Microgrids

Energies ◽

10.3390/en12112112 ◽

2019 ◽

Vol 12 (11) ◽

pp. 2112 ◽

Cited By ~ 7

Author(s):

Jaber Alshehri ◽

Muhammad Khalid ◽

Ahmed Alzahrani

Keyword(s):

Energy Storage ◽

Power Systems ◽

Power Quality ◽

Renewable Energy Sources ◽

Operating Conditions ◽

Frequency Regulation ◽

Battery Energy Storage ◽

Control Approach ◽

Battery Energy

Modern power systems rely on renewable energy sources and distributed generation systems more than ever before; the combination of those two along with advanced energy storage systems contributed widely to the development of microgrids (MGs). One of the significant technical challenges in MG applications is to improve the power quality of the system subjected to unknown disturbances. Hence innovative control strategies are vital to cope with the problem. In this paper, an innovative online intelligent energy storage-based controller is proposed to improve the power quality of a MG system; in particular, voltage and frequency regulation at steady state conditions are targeted. The MG system under consideration in this paper consists of two distributed generators, a diesel synchronous generator, and a photovoltaic power system integrated with a battery energy storage system. The proposed control approach is based on hybrid differential evolution optimization (DEO) and artificial neural networks (ANNs). The controller parameters have been optimized under several operating conditions. The obtained input and output patterns are consequently used to train the ANNs in order to perform an online tuning for the controller parameters. Finally, the proposed DEO-ANN methodology has been evaluated under random disturbances, and its performance is compared with a benchmark controller.

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Life Cycle Estimation of Battery Energy Storage Systems for Primary Frequency Regulation

Energies ◽

10.3390/en11123320 ◽

2018 ◽

Vol 11 (12) ◽

pp. 3320 ◽

Cited By ~ 7

Author(s):

Natascia Andrenacci ◽

Elio Chiodo ◽

Davide Lauria ◽

Fabio Mottola

Keyword(s):

Energy Storage ◽

Power Systems ◽

Control Strategy ◽

Storage Systems ◽

The State ◽

Frequency Regulation ◽

Battery Energy Storage ◽

Battery Lifetime ◽

Battery Energy Storage Systems ◽

Battery Energy

An increasing share of renewable energy sources in power systems requires ad-hoc tools to guarantee the closeness of the system’s frequency to its rated value. At present, the use of new technologies, such as battery energy storage systems, is widely debated for its participation in the service of frequency containment. Since battery installation costs are still high, the estimation of their lifetime appears crucial in both the planning and operations of power systems’ regulation service. As the frequency response of batteries is strongly dependent on the stochastic nature of the various contingencies which can occur on power systems, the estimation of the battery lifetime is a very complex issue. In the present paper, the stochastic process which better represents the power system frequency is analyzed first; then the battery lifetime is properly estimated on the basis of realistic dynamic modeling including the state of the charge control strategy. The dynamic evolution of the state of charge is then used in combination with the celebrated rain-flow procedure with the aim of evaluating the number of charging/discharging cycles whose knowledge allows estimating the battery damage. Numerical simulations are carried out in the last part of the paper, highlighting the resulting lifetime probabilistic expectation and the impact of the state of the charge control strategy on the battery lifetime. The main findings of the present work are the proposed autoregressive model, which allows creating accurate pseudo-samples of frequency patterns and the analysis of the incidence of the control law on the battery lifetime. The numerical applications clearly show the prominent importance of this last aspect since it has an opposing impact on the economic issue by influencing the battery lifetime and technical effects by modifying the availability of the frequency regulation service.

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