Energy Storage Power Station Research Articles

Research on monitoring and energy management systems for energy storage stations on the power generation side

Abstract Addressing the challenges of limited operational efficiency, inadequate battery safety, inflexible system scalability, inadequate AGC/AVC functionality, and low levels of intelligent operation and maintenance encountered by energy storage power stations integrated with new energy generation sources, this article delves into the pivotal role of these power stations on the generation side. It meticulously examines the network architecture, functional framework, and pivotal technologies underpinning the system. Furthermore, the article proposes a comprehensive monitoring and energy management system tailored specifically for energy storage on the generation side. The system uses micro-service architecture and container technology to realize the processing and storage of massive data. Through complete isolation of the information network and control network and millisecond communication with GOOSE, the charging and discharging response speed of the energy storage station is greatly improved. The power allocation algorithm based on device status recognition completes the system’s high-precision power control of PCS, and this system uses big data analysis and data mining technology to conduct a comprehensive statistical analysis of battery health status, power station operation efficiency, and equipment operation status and energy consumption. The design of the system has favorable technical and application guidance for the subsequent energy management design and engineering application of the energy storage power station.

Research on reliable data communication optimization strategy for energy storage power stations considering link-service importance

Research on reliable data communication optimization strategy for energy storage power stations considering link-service importance

Fault diagnosis technology overview for lithium‐ion battery energy storage station

AbstractWith an increasing number of lithium‐ion battery (LIB) energy storage station being built globally, safety accidents occur frequently. Diagnosing faults accurately and quickly can effectively avoid safe accidents. However, few studies have provided a detailed summary of lithium‐ion battery energy storage station fault diagnosis methods. In this paper, an overview of topologies, protection equipment, data acquisition and data transmission systems is firstly presented, which is related to the safety of the LIB energy storage power station. Then, existing fault diagnosis technologies are reviewed in detail. Finally, the future developing trends of fault diagnosis technology are discussed.

Design of hundred mw level shared BESSs and “Clean Energy + Energy Storage” joint operation mode

Abstract This paper presents the background of the construction of the Fujian Xiapu shared energy storage power station project. It also establishes the structure of the dispatching energy management system (EMS) for a large-scale Battery Energy Storage System (BESS) based on the energy storage station’s topology. The design and implementation method of the monitoring module for the energy storage power station is introduced, along with the proposition of the joint operation mode of “clean energy + energy storage”. Additionally, the technical requirements and feasibility of this mode are discussed. The shared energy storage operation mode can effectively enhance the energy conversion efficiency of the battery system while significantly reducing costs.

Suppression effects of different extinguishing agents on vent gases fires from lithium-ion batteries after thermal runaway: A comprehensive experimental and numerical study

Suppression effects of different extinguishing agents on vent gases fires from lithium-ion batteries after thermal runaway: A comprehensive experimental and numerical study

Coordinated control strategy of photovoltaic energy storage power station based on adaptive dynamic programming

In order to solve the problem of variable steady-state operation nodes and poor coordination control effect in photovoltaic energy storage plants, the coordination control strategy of photovoltaic energy storage plants based on ADP is studied. Establish the photovoltaic energy storage power station model including photovoltaic system model, super capacitor system model and battery system model; Set the maximum limit of active power change as the power constraint condition for coordinated control of photovoltaic energy storage station; The optimal control problem of multi voltage and reactive power resource coordination is fully considered, the optimal voltage control model is established by using ADP algorithm, and the optimal coordinated control strategy is obtained by online learning the collected dynamic operation information. The experimental results show that this strategy can improve the coordinated control effect of the photovoltaic energy storage station, ensure the photovoltaic energy storage station in a stable operation state, improve the service life of the energy storage device in the photovoltaic energy storage station, and stabilize the steady-state operating node voltage within the ideal fluctuation range.

KWH Cost Analysis of Energy Storage Power Station Based on Changing Trend of Battery Cost

Energy storage plays a vital role in enhancing the resilience of the power grid. Utilizing typical capacity and power energy storage application scenarios, coupled with industry research data and technical analysis of energy storage, this study calculates the cost of energy storage per kilowatt-hour and the associated mileage cost. The findings indicate that the current cost per kilowatt-hour of electrochemical energy storage ranges from approximately 0.6 to 0.9 yuan/(kW⋅h), revealing a considerable gap between the target cost for widespread application and the range of 0.3 to 0.4 yuan/(kW⋅h). Therefore, the development of energy storage technologies (EST) should prioritize achieving “low cost, long life, high safety, and easy recycling,” taking into account a comprehensive assessment of system manufacturing, system lifespan, system safety, and recycling. This paper delves into the changing trend of battery costs and their impact on kilowatt-hours, presenting strategic suggestions to reduce the kilowatt-hour cost of ESP stations. The research underscores that a continuous reduction in battery costs will contribute to enhancing the economic benefits of ESP stations and provide robust support for the future development of the energy storage industry.

Design of Underwater Compressed Air Flexible Airbag Energy Storage Device and Experimental Study of Physical Model in Pool

Renewable energy is a prominent area of research within the energy sector, and the storage of renewable energy represents an efficient method for its utilization. There are various energy storage methods available, among which compressed air energy storage stands out due to its large capacity and cost-effective working medium. While land-based compressed air energy storage power stations have been constructed worldwide, their efficiency remains low. Underwater compressed air energy storage has the potential to significantly enhance efficiency, although no such device currently exists. This paper presents the design of an UWCA-FABESD utilizing five flexible air bags for underwater gas storage and discharge. Additionally, it introduces the working principle of the adiabatic underwater compressed air energy storage system and device. Furthermore, a small-scale physical model with similar functionality was designed and manufactured to simulate the charging process of the air bag in onshore charging and discharging tests as well as posture adjustment and lifting arrangement tests, along with underwater charging and discharging tests. These experiments validated the related functions of the designed underwater compressed air flexible bag energy storage device while proposing methods for its improvement. This research provides a new approach to underwater compressed air energy storage.

Optimal Power Model Predictive Control for Electrochemical Energy Storage Power Station

Aiming at the current power control problems of grid-side electrochemical energy storage power station in multiple scenarios, this paper proposes an optimal power model prediction control (MPC) strategy for electrochemical energy storage power station. This method is based on the power conversion system (PCS) grid-connected voltage and current to establish a power prediction model for energy storage power stations, achieving a one-step prediction of the power of the power station. The power prediction error is used as a power regulation feedback quantity to correct the reference power input. Considering the state of charge (SOC) constraint of the battery, partition the SOC into different states. Using SOC as the power regulation feedback, the power of the battery compartment can be adjusted according to the range of the battery SOC to prevent SOC from exceeding the limit value, simultaneously calculating the power loss of the energy storage power station to improve the energy efficiency. The objective function is to minimize the power deviation and power loss of the power station. By solving the objective function, the optimal switching voltage vector of the converter output is achieved to achieve optimal power control of the energy storage power station. The simulation results in various application scenarios of the energy storage power station show that the proposed control strategy enables the power of the storage station to quickly and accurately track the demand of grid scheduling, achieving the optimal power control of the electrochemical energy storage power station.

Off-Stoichiometry of Sodium Iron Pyrophosphate as Cathode Materials for Sodium-Ion Batteries with Superior Cycling Stability.

As one of the important devices for large-scale electrochemical energy storage, sodium-ion batteries have received much attention due to the abundant resources of raw materials. However, whether it is a base station power source, an energy storage power station, or a start-stop power supply, long energy cycle life (more than 5000 cycles), high stability, and safety performance are application prerequisites. Regrettably, currently, few sodium-ion batteries can meet this requirement, mainly due to shortcomings in positive electrode performance. We report a sufficiently stable sodium-ion battery cathode material, Na2Fe0.95P2O7, that retains 97.5% capacity after 5000 charge/discharge cycles. The use of nonstoichiometry in the lattice enables simultaneous modification of the crystal and electronic structure, promoting Na2Fe0.95P2O7 to be extremely stable while still being able to achieve a capacity of 92 mAh g-1 and stable cycling at high temperatures up to 60 °C. Our results confirm the positive effect of nonstoichiometric ratios on the performance of Na2Fe0.95P2O7 and provide a reliable idea to promote the practical application of sodium-ion batteries.

Indium-nickel oxide nanocomposite for room temperature H2 gas detection and its sensing mechanism

Indium-nickel oxide nanocomposite for room temperature H2 gas detection and its sensing mechanism

Risk assessment of zero-carbon salt cavern compressed air energy storage power station

Risk assessment of zero-carbon salt cavern compressed air energy storage power station

Renewable energy utilization and stability through dynamic grid connection strategy and AI-driven solution approach

Renewable energy utilization and stability through dynamic grid connection strategy and AI-driven solution approach

Multi-level anomaly detection of lithium battery energy storage system

Abstract The energy storage technology route represented by lithium battery energy storage strongly supports China’s energy structure transformation. The widespread use of lithium batteries also poses a significant safety risk that is often overlooked. Energy storage system security is facing severe challenges. It is very beneficial for the safety of energy storage systems to predict the potential faults of lithium batteries before they are used and find anomaly batteries in time. This paper proposes a three-stage anomaly detection method based on statistics and density concepts to provide real-time potential fault prediction of lithium battery energy storage systems. Considering both efficiency and accuracy, this method can detect anomaly samples from shallow to deep. Finally, the battery condition of a large energy storage plant was studied, and 11 anomaly batteries were detected. The proposed method is significant for safely operating large energy storage power stations.

Study on voltage consistency characteristics of lithium-ion battery energy storage system

Abstract In the long-term operation of lithium-ion battery energy storage power stations, the consistency of batteries, as an important indicator representing the operation condition of the system, needs to be focused. In practice, the parameters of voltage, capacity, and internal resistance are most commonly used for the consistency evaluation of batteries, and voltage is the most intuitive one. In this paper, a real lithium-ion battery energy storage power station is studied, and the consistency of voltages is calculated. The results show that, with the decline of the battery capacity during discharge, the consistency of the battery presents a strong nonlinear characteristic. At the beginning of discharge, the max-min and standard deviation of voltage are only 0.04 and 0.01 V, while at the end of discharge, the max-min and standard deviation of voltage are up to 0.25 V and 0.045 V, respectively. At about 40-50 minutes of the discharge, i.e., when the corresponding voltages are about 3.132 V to 3.176 V, the voltage consistency deteriorates rapidly. Then, this period of discharge is considered as a threshold interval of consistency deterioration of batteries. The results are helpful for system condition evaluation and operation optimization.

Intelligent Learning Method for Capacity Estimation of Lithium-Ion Batteries Based on Partial Charging Curves

Lithium-ion batteries are widely used in electric vehicles, energy storage power stations, and many other applications. Accurate and reliable monitoring of battery health status and remaining capacity is the key to establish a lithium-ion cell management system. In this paper, based on a Bayesian optimization algorithm, a deep neural network is structured to evaluate the whole charging curve of the battery using partial charging curve data as input. A 0.74 Ah battery is used for experiments, and the effect of different input data lengths is also investigated to check the high flexibility of the approach. The consequences show that using only 20 points of partial charging data as input, the whole charging profile of a cell can be exactly predicted with a root-mean-square error (RMSE) of less than 19.16 mAh (2.59% of the nominal capacity of 0.74 Ah), and its mean absolute percentage error (MAPE) is less than 1.84%. In addition, critical information including battery state-of-charge (SOC) and state-of-health (SOH) can be extracted in this way to provide a basis for safe and long-lasting battery operation.

The application effect of the optimized scheduling model of virtual power plant participation in the new electric power system

The application effect of the optimized scheduling model of virtual power plant participation in the new electric power system

Reliability analysis method of energy storage stations considering the correlation of battery clusters

In the context of dual carbon, in order to address the volatility of new energy output, energy storage power stations (ESPSs) are thriving. However, it is challenging to assess the dependability of ESPS operation because of the steady functioning of individual battery clusters (BCs), which will have an impact on how safely and steadily the power system is evaluated. Therefore, a reliability model for energy storage BC units based on the structural analysis of battery structure modules is constructed in this manuscript. Then, a method for constructing a correlation model of energy storage units based on the Copula function was proposed. Finally, a simulation analysis based on the ESPSs of pertinent demonstrative application projects in Fujian Province is used as an example to confirm the viability and efficacy of the proposed reliability analysis approach.

Optimal scheduling of multi-regional energy system considering demand response union and shared energy storage

Optimal scheduling of multi-regional energy system considering demand response union and shared energy storage

A performance evaluation method for energy storage systems adapted to new power system interaction requirements

In recent years, China’s new energy storage application on a large scale has shown a good development trend; a variety of energy storage technologies are widely used in renewable energy development, consumption, integrated intelligent energy systems, distribution grids, and microgrids; and substantial progress has been made in the research and development of technology and equipment, construction of demonstration projects, exploration of business models, and construction of standard systems. Up to now, a unified statistical index system and evaluation method standard for new energy storage has not yet been formed domestically or even internationally. The work takes the status quo of the new power system construction of the Hebei South Network as the research object and carries out research on the new energy storage statistical index system and evaluation method. It constructs a new energy storage power station statistical index system centered on five primary indexes: energy efficiency index, reliability index, regulation index, economic index, and environmental protection index; proposes Analytic Hierarchy Process (AHP)–coefficient of variation combination assignment method; and evaluates the development level of the new energy storage power station by adopting a comprehensive evaluation model based on the object element topology method. The new energy storage statistical index system and evaluation method are designed to provide a scientific index system and evaluation method for comprehensively monitoring, assessing and measuring the comprehensive performance and effect of new energy storage power plants in the process of operation and development, and optimizing the operation strategy of new energy storage power plants as well as the development and promotion of energy storage technology.