Conventional Battery Energy Storage System Research Articles

Risk-averse bi-level planning model for maximizing renewable energy hosting capacity via empowering seasonal hydrogen storage

Renewables (i.e., solar and wind power) in the Nordic area have highly seasonal characteristics, which severely restrict the wide development of renewables since they can be excessive in summer but insufficient in winter with intermittent outputs. The conventional battery energy storage system (BESS) with short-term adjustment functionality cannot eliminate the seasonal imbalance of renewables. In this regard, a risk-based bi-level planning model is presented to maximize the hosting capacity (HC) of renewables through configuring seasonal hydrogen storage (SHS) and BESS. Specifically, the upper level applies a multi-objective scheme to maximize HC and minimize the investment cost simultaneously. In turn, the lower level is driven by maximizing the profits of the distribution system operator (DSO) with the implementation of price-based demand response (PBDR). Due to forecasting errors of renewables and load resulting from intermittent output and random behaviors, a stochastic programming (SP) method is developed to address and adapt multiple uncertain fluctuations. Moreover, the conditional value-at-risk (CVaR) is introduced to measure the effect of the risks raised by multiple uncertainties on system operation. Finally, numerical studies are employed to verify the effectiveness of the proposed model. Compared to the cases without considering PBDR and SHS, the total renewable energy HC in the proposed model is increased by 2.30 MW and 0.37 MW, respectively, while the yearly cost benefit of DSO is enhanced by 28063.2 US$ and 17823.7 US$, respectively. The promising results demonstrate the empowerment of SHS can promote the cross-seasonal consumption of renewables, effectively maximizing the HC and improving the economic operation of distribution systems.

An optimal configuration method for microgrid second-use battery storage system considering users allocate the cost of peak-shaving auxiliary service

The second use of retired batteries can reduce energy storage system (ESS) costs, relieve the power supply pressure of the power grid during peak hours, peak cutting and valley filling and promote energy saving and emission reduction. Power users can allocate a certain amount of peak-shaving auxiliary service costs to guide users to cut peaks and fill valleys. This paper presented an optimal configuration method for a microgrid second-use battery energy storage system (BESS) considering the users allocate peak shaving auxiliary service costs. A second-use BESS optimization configuration model was established to configure the second-use BESS with the lowest cost and the lowest peak shaving service cost allocated by users. The optimization model was solved by the particle swarm algorithm (PSO). And compared with the configured conventional BESS of residential area micro-grid. Simulation is carried out on the MATLAB platform, and the results verify the model’s and algorithm’s rationality.

Optimal Control Method and Design for Modular Battery Energy Storage System Based on Partial Power Conversion

This article addresses a bidirectional low power loss series-parallel partial-power modular converter (SPPC) suitable for series-connected high voltage large power battery energy storage system (BESS). A specific capacitor is placed on the top of the series battery packs, which voltage can be adjusted by the SPPC to compensate for the voltage fluctuation of the battery packs and the DC power line. The power loss and cost of the SPPC are relatively low since its rated power is reduced to about 22%–48% of the full-power converter. A 3 level distributed control method is proposed to achieve the fast transient response of the DC power line current and deal with the series inconsistency of battery packs during discharging and charging, further improving the total energy utilization efficiency (EUE) of the BESS. The critical design considerations for SPPC-BESS are analyzed. A bidirectional 800W phase-shift full-bridge (PSFB) converter hardware prototype along with the Gallium Nitride (GaN) devices is provided to verify the high efficiency of DC-DC sub-module. Then a simulation model of a 6.6kW SPPC-BESS with 3 sub-modules to verify the feasibility of the control method. Theoretical analysis proves that the total power loss of the SPPC is lower than the existing types of modular converters. The EUE of the SPPC-BESS is 1.7% higher than the conventional BESS when the average maximum available capacities of batteries attenuate to 80% of the initial maximum available capacity.

Cooperative control strategy for distributed wind-storage combined system based on consensus protocol

To realize real-time wind farm output power regulation with power-sharing among storage devices that have different state of charges (SoCs), this paper proposes the cooperative control of the distributed wind-storage combined systems (WSCSs). It firstly establishes the mathematical model of doubly-fed induction generator (DFIG) and hybrid energy storage system (HESS) and implements the controls for two devices, respectively. Secondly, based on the power consensus protocol, an active power cooperative control strategy of the distributed WSCSs is proposed. It ensures that the energy storage devices can cooperatively compensate for wind power according to their different capacities to regulate the output power of the wind farm (WF) in real-time. At the same time, the high- and low- frequency power fluctuations can be effectively shared by the supercapacitors (SCs) and batteries, overcoming the deficiencies of the conventional battery energy storage system (BESS). Then, considering that the SoCs of the batteries are not identical, this paper further proposes a DFIG grid-side reference power adjustment strategy based on consensus protocol. It guarantees that each HESS can effectively achieve power-sharing while regulating the output power according to the SoCs of batteries. Finally, simulations in PSCAD/EMTDC under various scenarios are conducted to demonstrate the effectiveness of the proposed control strategy.

Reliability Evaluation and Improvement of Islanded Microgrid Considering Operation Failures of Power Electronic Equipment

With the high integration of power electronic technologies in microgrids, the reliability assessment considering power electronic devices has become a hot topic. However, so far no research has considered the impact of the operation failure probability of power electronic equipment on the overall reliability of the microgrid. This paper aims to construct a holistic operation failure rate model of power electronic systems based on the overall reliability assessment of islanded microgrid with high penetration of renewable energy sources (RESs). In addition, to improve the reliability of islanded microgrid, the conventional battery energy storage system (BESS) is replaced by the hybrid energy storage system (HESS). Based on the proposed model, the operation failure models for the power electronic modules in microgrid are built and tested, and then the sensitivity analysis is performed for exploring the influence of various factors on the reliability of the microgrid.

Numerical modeling of hybrid supercapacitor battery energy storage system for electric vehicles

Electric vehicle (EV) has been steadily gaining attention and as a viable alternative to mitigate pressing global energy crisis and environmental issues caused by conventional internal combustion engine vehicles. Nonetheless, the dynamic operation of EV encompassing high charging and discharging currents generated from regenerative braking and acceleration, respectively, may adversely affect the cycle life of the conventional energy storage system. Hence, incorporation of supercapacitors into the energy storage system is recommended in view of its superior cycle efficiency and high power density, which aids in relieving the battery’s stress and thus extends its cycle life. In this study, a hybrid energy storage system (HESS) comprising Li-ion batteries and supercapacitors are modeled to evaluate its electrical and thermal performances under different driving cycles. The results obtained reveal that the dynamic stress, peak power demand and thermal performance of the battery have been significantly improved by incorporating supercapacitors into the battery pack in HESS. In comparison with the conventional battery energy storage system, the peak current demands of the battery in HESS for UDDS and US06 cycles have been reduced by 63%, 72.9% and 71.7%, respectively. This approach has shown to be effective in extending the battery’s lifespan and is able to improve the safety and reliability of the conventional battery energy storage system.

Sizing and SOC Management of a Smart-Transformer-Based Energy Storage System

A smart transformer (ST), which is a power-electronic-based transformer with control and communication functionalities, can be the optimal solution for integrating a battery energy storage system (BESS) in an electric distribution system. In fact, a comparison of energy efficiency for the conventional BESS and the ST-based BESS is carried out, which demonstrates that the ST-based BESS operation is more efficient during charging and discharging, as compared to the conventional BESS. It has been shown that by sizing the BESS appropriately for the peak load demand, the power rating of ST converters can be reduced. The ST-based BESS provides an enhanced fault ride-through capability, as compared to the conventional BESS. However, the state of charge (SOC) of the BESS shall be correctly managed to support the peak load demand when the ST converter reaches its maximum active power rating. Both simulation and experimental results clearly verify the developed SOC management.

Two-Stage Battery Energy Storage System (BESS) in AC Microgrids with Balanced State-of-Charge and Guaranteed Small-Signal Stability

In this paper, a two-stage battery energy storage system (BESS) is implemented to enhance the operation condition of conventional battery storage systems in a microgrid. Particularly, the designed BESS is composed of two stages, i.e., Stage I: integration of dispersed energy storage units (ESUs) using parallel DC/DC converters, and Stage II: aggregated ESUs in grid-connected operation. Different from a conventional BESS consisting of a battery management system (BMS) and power conditioning system (PCS), the developed two-stage architecture enables additional operation and control flexibility in balancing the state-of-charge (SoC) of each ESU and ensures the guaranteed small-signal stability, especially in extremely weak grid conditions. The above benefits are achieved by separating the control functions between the two stages. In Stage I, a localized power sharing scheme based on the SoC of each particular ESU is developed to manage the SoC and avoid over-charge or over-discharge issues; on the other hand, in Stage II, an additional virtual impedance loop is implemented in the grid-interactive DC/AC inverters to enhance the stability margin with multiple parallel-connected inverters integrating at the point of common coupling (PCC) simultaneously. A simulation model based on MATLAB/Simulink is established, and simulation results verify the effectiveness of the proposed BESS architecture and the corresponding control diagram.

A Comparison of Grid-Connected Battery Energy Storage System Designs

This paper presents a method for evaluating grid-connected battery energy storage system (BESS) designs. The steady-state power losses of the grid interface converter, the battery pack, and the balancing circuit are calculated. The reliability of each complete system is calculated using a Markov-based modeling approach that takes into account the built-in redundancy of the system as well as performance degradation caused by faults. Finally, a simple economic analysis based on capital cost and efficiency is used to provide a basis for direct comparison between competing system designs. Three design options for a 1-MW 1-MWh BESS connected at 11 kV are compared: a conventional BESS using parallel low voltage power blocks, a BESS using a high-voltage intelligent battery pack, and a BESS using a cascaded H-bridge converter. The results of the analysis indicate that additional power electronics included in the battery pack as part of the intelligent battery pack and H-bridge designs can enhance the reliability of the BESS by an order of magnitude under typical conditions, without increasing the overall cost of the system.

Optimum battery energy storage system using PSO considering dynamic demand response for microgrids

This article proposes a novel optimum sizing of battery energy storage system (BESS) using particle swarm optimization (PSO) incorporating dynamic demand response (DR) to improve a fast, smooth and secure system stability and performance, avoiding a microgrid from instability and system collapse during an emergency situation. An optimum size of BESS integrating DR can play an important role in frequency control of the microgrid in order to rapidly improve the system stability, restore the power equilibrium and prevent system collapse in the microgrid. The optimum size of BESS is evaluated by PSO incorporating DR based on frequency control of the microgrid. The results show that the optimum size of BESS-based PSO with DR can improve a fast, smooth and safe system performance and dynamic stability compared with the optimum size of BESS-based simulated annealing (SA) with DR and the conventional size. Nevertheless, the proposed sizing methods also determined the impact of BESS specified costs between modern and conventional BESS technologies. The capital cost, operating and maintenance cost of BESS were then investigated and compared in terms of economical performance for microgrid operations.

Minimization and control of battery energy storage for wind power smoothing: Aggregated, distributed and semi-distributed storage

A battery energy storage system (BESS) is usually integrated with a wind farm to smooth out its intermittent power in order to make it more dispatchable. This paper focuses on the development of a scheme to minimize the capacity of BESS in a distributed configuration using model predictive control theory and wind power prediction. The purpose to minimize the BESS capacity is to reduce the overall cost of the system as the capacity of BESS is the main cost driver. A new semi-distributed BESS scheme is proposed and the strategy is analyzed as a way of improving the suppression of the fluctuations in the wind farm power output. The scheme is tested for similar and dissimilar wind power profiles, where the turbines are geographically located closer and further from each other, respectively. These two power profiles are assessed under a variety of hard system constraints for both the proposed and conventional BESS configurations. Based on the simulation results validated with real-world wind farm data, it has been observed that the proposed semi-distributed BESS scheme results in the improved performance as compared with conventional configurations such as aggregated and distributed storage.