Can Photovoltaic Battery Energy Storage Systems Be Self-Balancing?

Author(s):  
Partha P. Mishra ◽  
Hosam K. Fathy

This paper proposes a novel approach for integrating battery storage into photovoltaic (PV) arrays. The approach relies on the integration of PV arrays with individual batteries to form “hybrid cells” that are then assembled into series strings. We use Lyapunov analysis to show that the proposed hybrid strings are globally asymptotically self-balancing, meaning that initial variations in state of charge (SOC), no matter how large, converge to zero. The PV subsystem serves as a negative feedback path that guarantees self-balancing without requiring dedicated balancing circuits. This significantly reduces the cost of the power electronics needed for integrating batteries into PV farms, compared to typical integration topologies. The paper uses local linearization to approximate the balancing rate, thereby highlighting its independence of battery pack length and elucidating its dependence on subsystem sizing. Finally, a simulation study validates the paper’s theoretical insights regarding self-balancing, and examines its sensitivity to parameter heterogeneities.

2019 ◽  
Vol 9 (6) ◽  
pp. 1148 ◽  
Author(s):  
Yongzhu Hua ◽  
Xiangrong Shentu ◽  
Qiangqiang Xie ◽  
Yi Ding

In recent years, the installation of distributed generation (DG) of renewable energies has grown rapidly. When the penetration of grid-integrated DGs are getting high, the voltage and frequency of the power system may cause deviation. We propose an algorithm that reduces voltage and frequency deviation by coordinating the control of multiple battery energy storage systems (BESSs). The proposed algorithm reduces the total number of charging and discharging times by calculating the sensitivity coefficient of BESS at different nodes and then selecting the appropriate BESSs to operate. The algorithm is validated on a typical distribution testing system. The results show that the voltage and frequency are controlled within the permissible range, the state of charge of BESSs are controlled within the normal range, and the total number of charging and discharging cycles of BESSs are reduced.


Energies ◽  
2019 ◽  
Vol 12 (9) ◽  
pp. 1614 ◽  
Author(s):  
Jae-Won Chang ◽  
Gyu-Sub Lee ◽  
Hyeon-Jin Moon ◽  
Mark B. Glick ◽  
Seung-Il Moon

Recently, isolated microgrids have been operated using renewable energy sources (RESs), diesel generators, and battery energy storage systems (BESSs) for an economical and reliable power supply to loads. The concept of the complementary control, in which power imbalances are managed by diesel generators in the long time scale and BESSs in the short time scale, is widely adopted in isolated microgrids for efficient and stable operation. This paper proposes a new complementary control strategy for regulating the frequency and state of charge (SOC) when the system has multiple diesel generators and BESSs. In contrast to conventional complementary control, the proposed control strategy enables the parallel operation of diesel generators and BESSs, as well as SOC management. Furthermore, diesel generators regulate the equivalent SOC of BESSs with hierarchical control. Additionally, BESSs regulate the frequency of the system with hierarchical control and manage their individual SOCs. We conducted a case study by using Simulink/MATLAB to verify the effectiveness of the proposed control strategy in comparison with conventional complementary control.


2019 ◽  
Vol 16 (1) ◽  
Author(s):  
Jaime Cepeda ◽  
Santiago Chamba

Este documento propone una novedosa metodología para la estimación probabilística del modelo estocástico del estado de carga (SOC por su nombre en inglés “State of Charge”) de los sistemas de almacenamiento de energía mediante baterías (BESS por su nombre en inglés “Battery Energy Storage Systems”). La estimación apropiada del SOC es uno de los parámetros más importantes en la planificación de la expansión y operación de las microrredes. Para ello, se estructura una herramienta computacional que enlaza los programas de DIgSILENT PowerFactory y Python. Este aplicativo permite, de forma probabilística, evaluar la operación de la microrred considerando la disponibilidad del recurso primario intermitente de las fuentes de energía renovables y la variabilidad de la demanda eléctrica. Como resultado se determinan los modelos estocásticos del SOC del BESS para cada período de tiempo. La metodología propuesta se aplica a una microrred de prueba que se conecta a la “Barra 6” del sistema de prueba WSCC de tres máquinas y nueve barras, obteniéndose resultados prometedores.


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