Flywheel Energy Storage System Research Articles

Design and Research an Axial-Flux Magnetic Coupler With Clutch for the Superconducting Flywheel Energy Storage System

Design and Research an Axial-Flux Magnetic Coupler With Clutch for the Superconducting Flywheel Energy Storage System

Economic evaluation of kinetic energy storage systems as key technology of reliable power grids.

In recent years, energy-storage systems have become increasingly important, particularly in the context of increasing efforts to mitigate the impacts of climate change associated with the use of conventional energy sources. Renewable energy sources are an environmentally friendly source of energy, but by their very nature, they are not able to supply the required amount of energy in a uniform distribution. This study evaluated the economic efficiency of short-term electrical energy storage technology based on the principle of high-speed flywheel mechanism using vacuum with the help of an innovative approach based on life cycle cost analysis (LCC). The innovative potential of high-speed flywheel energy storage systems (FESS) can be seen in increasing the reliability of the electricity transmission system with the possibility of providing control power to compensate for residual loads caused by volatile renewable power sources and power sinks. Based on the research conducted, the LCC method was selected in this study as the most appropriate method to evaluate the economic efficiency of a high-speed FESS used to compensate for short-term fluctuations in an upgraded electric transmission system. As a result, the adjusted LCC per MWh values were compared with the average intra-hour margin realisable in the Intra-Day OTE Market, while the margin calculation also considered the efficiency of the inertial storage. Under the modelled technical and economic conditions, it was found that a high-speed FESS project that can compensate for short-term fluctuations in the electricity transmission system can be economically efficient in the Czech Republic.

Energy management strategy and operation strategy of hybrid energy storage system to improve AGC performance of thermal power units

With the continuous increase of the renewable energy power generation penetration, the intermittency and fluctuation of renewable energy power generation make the traditional thermal power units (TPU) which play the main role of regulation need to undertake more frequent and more severe regulation tasks. In order to improve the automatic generation control (AGC) command response capability of TPU, an operation strategy of hybrid energy storage system (HESS) is proposed in this paper. While assisting TPU to complete the regulation tasks, it gives full play to the advantages of power-type and energy-type energy storage. Moreover, an energy management strategy of energy storage array (ESA) is proposed to improve the overall operation efficiency of ESA while making the state of charge (SOC) of all energy storage subunits consistent. Finally, the effectiveness of the proposed strategy is verified by simulation experiments. The results show that after using HESS to assist TPU operation, the comprehensive regulation performance index of TPU increased from 4.0198 to 7.8112, which significantly improved the operational flexibility of TPU. Meanwhile, the strategy proposed in this paper makes different types of energy storage systems in HESS operate in a relatively healthy SOC range, and the SOC of the flywheel energy storage system (FESS) reaches the limitation value decrease from 6 times to once, ensuring the overall charge and discharge capacity of HESS.

Artificial intelligence computational techniques of flywheel energy storage systems integrated with green energy: A comprehensive review

In recent years, the operation of the electric power grid has become more efficient and resilient due to the integration of renewable energy sources (RESs). Solar and wind energy are being incorporated aggressively into the main grid, while other RESs like biomass and geothermal energy are also on the rise. However, the intermittent nature of these RESs necessitates the use of energy storage devices (ESDs) as a backup for electricity generation such as batteries, supercapacitors, and flywheel energy storage systems (FESS). This paper provides a thorough review of the standardization, market applications, and grid integration of FESS. It examines the components of FESS, including the electric motor/generator set, power converters, bearings, and control techniques. The paper also highlights the application of modern artificial intelligence (AI) methodologies in optimizing FESS operations, referencing over 240 recent publications in reputable journals. Metaheuristic optimizers, machine learning techniques, and well-matures software's are the main AI aspects discussed in this paper. Additionally, it explores the use of FESS in commercial sectors such as marine, space, and transportation, and its integration with RESs for participating in green energy. Finally, the paper emphasizes the role of AI in enhancing the synergy between FESS and RESs to contribute to a more sustainable and secure energy future.

Solar PV focused LFC studies utilizing an SFS-optimized PID with fractional derivative (PIDDμ), and incorporating BESS and FESS applications

This study investigates the application of a PID controller with a fractional derivative component (PIDDμ), optimized using the stochastic fractional search (SFS) technique, for load frequency control (LFC) in power systems. Additionally, solar PV and battery energy storage systems (BESS) and flywheel energy storage systems (FESS) are integrated as backup sources to enhance the LFC performance. To assess the effectiveness of the proposed approach, three error metrics—Integral Time Absolute Error (ITAE), Integral Time Multiplied Square Error (ITSE), and Integral of Absolute Error (IAE)—are evaluated. The results are compared with recent optimization-based LFC techniques across various scenarios. It is found that the SFS-PIDDμ achieves IAE=0.006786, ITSE=1.07e-05, and ITAE=0.01853, which are significantly lower than the error values produced by other LFC techniques. Furthermore, integrating solar PV, along with BESS and FESS, further reduces these error values. The graphical LFC responses of the SFS-PIDDμ outperform other optimization-based LFC techniques. The robustness of the approach is also validated against random load changes of varying magnitudes and for broader parametric variations.

Design and Analysis of a Highly Reliable Permanent Magnet Synchronous Machine for Flywheel Energy Storage

This article aims to propose a highly reliable permanent magnet synchronous machine (PMSM) for flywheel energy-storage systems. Flywheel energy-storage systems are large-capacity energy storage technologies suitable for the short-term storage of electrical energy. PMSMs have been used in the flywheel energy-storage systems due to their advantages. One of the key requirements for PMSMs in flywheel energy-storage systems is high reliability. A double redundant winding structure is adopted to ensure fault-tolerant operation of the PMSM. The stator is designed with auxiliary teeth to reduce the short-circuit current. Moreover, the number of slots and poles is determined to ensure the winding factor, heat dissipation, and reduce losses. Moreover, the dual three-phase stator winding structure and auxiliary teeth are adopted on the PMSM to improve reliability. Afterward, the electromagnetic performance is analyzed, and the mechanical stress is investigated to ensure mechanical strength. Finally, a prototype is built and tested to verify the theoretical analysis and performance of the PMSM.

FOPDT model and CHR method based control of flywheel energy storage integrated microgrid

The main causes of frequency instability or oscillations in islanded microgrids are unstable load and varying power output from distributed generating units (DGUs). An important challenge for islanded microgrid systems powered by renewable energy is maintaining frequency stability. To address this issue, a proportional integral derivative (PID) controller is designed in this article. Firstly, islanded microgrid model is constructed by incorporating various DGUs and flywheel energy storage system (FESS). Further, considering first order transfer function of FESS and DGUs, a linearized transfer function is obtained. This transfer function is further approximated into first order plus time delay (FOPTD) form to design PID control strategy, which is efficient and easy to analyze. PID parameters are evaluated using the Chien-Hrones-Reswick (CHR) method for set point tracking and load disturbance rejection for 0% and 20% overshoot. The CHR method for load disturbance rejection for 20% overshoot emerges as the preferred choice over other discussed tuning methods. The effectiveness of the discussed method is demonstrated through frequency analysis and transient responses and also validated through real time simulations. Moreover, tabulated data presenting tuning parameters, time domain specifications and comparative frequency plots, support the validity of the proposed tuning method for PID control design of the presented islanded model.

Hardware-in-the-Loop Simulation of Flywheel Energy Storage Systems for Power Control in Wind Farms

Hardware-in-the-Loop Simulation of Flywheel Energy Storage Systems for Power Control in Wind Farms

Optimising Flywheel Energy Storage Systems: The Critical Role of Taylor–Couette Flow in Reducing Windage Losses and Enhancing Heat Transfer

Amidst the growing demand for efficient and sustainable energy storage solutions, Flywheel Energy Storage Systems (FESSs) have garnered attention for their potential to meet modern energy needs. This study uses Computational Fluid Dynamics (CFD) simulations to investigate and optimise the aerodynamic performance of FESSs. Key parameters such as radius ratio, aspect ratio, and rotational velocity were analysed to understand their impact on windage losses and heat transfer. This study reveals the critical role of Taylor–Couette flow on the aerodynamic performance of FESSs. The formation of Taylor vortices within the airgap was examined, demonstrating their effect on temperature distribution and overall system performance. Through a detailed examination of the skin friction coefficient and Nusselt number under different conditions, this study identified a nonlinear relationship between rotor temperature and rotational speed, highlighting the accelerated temperature rise at higher speeds. The findings indicate that optimising these parameters can significantly enhance the efficiency of FESSs, reducing windage losses and improving heat transfer. This research provides valuable insights into the aerodynamic and thermal optimisation of FESSs, offering pathways to improve their design and performance. The results contribute to advancing guidelines for the effective implementation of FESSs in the energy sector, promoting more sustainable energy storage solutions.

Dual‐inertia flywheel energy storage system for electric vehicles

AbstractManaging the high‐rate‐power transients of Electric Vehicles (EVs) in a drive cycle is of great importance from the battery health and drive range aspects. This can be achieved by high power‐density storage, such as a high‐speed Flywheel Energy Storage System (FESS). It is shown that a variable‐mass flywheel can effectively utilise the FESS useable capacity in most transients close to optimal. Novel variable capacities FESS is proposed by introducing Dual‐Inertia FESS (DIFESS) for EVs. The feasibility of the proposed concept is evaluated by deriving the size of a Single‐Inertia FESS (SIFESS) for a battery EV, which runs the well‐known Urban Dynamometer Driving Schedule. The sizing framework consists of an Energy Management System using the constrained Pontryagin's minimum principle and a proposed sizing algorithm. Then, by splitting the derived SIFESS inertia into two separate inertias, the appropriate engaging control of inertias is determined for some driving cycles including, the Artemis Urban, Braunschweig City, and Worldwide Harmonised Light‐duty Vehicles Test Cycle. The dual inertias suitable sizes are derived using a proposed algorithm, which targets maximising the FESS useable capacity. The results show that compared to the SIFESS, the DIFESS can employ the FESS's useable capacity more effectively.

Dual-layer control strategy based on economic characterization of lifetime state and frequency regulation limit partition of hybrid energy storage

Compared with a single type of energy storage, hybrid energy storage system (HESS) has a better performance in improving the frequency safety of the grid. However, the combination of hybrid energy storage with different resource characteristics and thermal power units will significantly increase the difficulty of coordinated control. In view of the life decay of battery energy storage system (BESS) and the insufficient frequency regulation capability of the system, this paper proposes a dual-layer control strategy based on the economic characterization of hybrid energy storage life state and the frequency regulation limit partition. Real-time state of charge (SOC) is used to establish dynamic equilibrium quotation and energy storage performance characterization as the upper-layer model. Meanwhile, the optimal life evaluation of energy storage is proposed, and the charging and discharging switching model of energy storage is constructed to limit the frequent switching of energy storage and extend its life. The lower-layer model constructs the limit standard of frequency regulation of flywheel energy storage system (FESS), introduces multi-objective constraints, proposes a hybrid energy storage operation scheme suitable for the whole scene, and uses “two rules” as the evaluation index to evaluate the frequency regulation effect of the proposed frequency regulation control model from the regulation rate, accuracy and response time. Finally, taking the actual data of a local thermal power unit as an example, the validity and economy of the frequency regulation effect of the proposed model are verified.

Design, modeling, and validation of a 0.5 kWh flywheel energy storage system using magnetic levitation system

The flywheel energy storage system (FESS) has excellent power capacity and high conversion efficiency. It could be used as a mechanical battery in the uninterruptible power supply (UPS). The magnetic suspension technology is used in the FESS to reduce the standby loss and improve the power capacity. First, the whole system of the FESS with the magnetic levitation system is introduced, and the control diagrams of the charging/discharging processes are developed. Moreover, the force modeling of the magnetic levitation system, including the axial thrust-force permanent magnet bearing (PMB) and the active magnetic bearing (AMB), is conducted, and results indicate that the magnetic forces could stably levitate the flywheel (FW) rotor. The stator part and the FW rotor are analyzed using the FEM model, and the results could satisfy the requirements on stress and strength of the FESS at the rated speed. Then, the control models are established to accomplish the rapid charging/discharging functions of the FESS. Finally, experiments are performed to test the charging/discharging ability, and the results show that an excellent control current could enhance the charging/discharging efficiency so the stable DC link voltage could be outputted at the discharge process. Therefore, the test results prove that the designed FESS could be used as an auxiliary power supply for the UPS when the grid power fails.

Study of Magnetic Coupler With Clutch for Superconducting Flywheel Energy Storage System

Study of Magnetic Coupler With Clutch for Superconducting Flywheel Energy Storage System

Windage loss characterisation for flywheel energy storage system: Model and experimental validation

In this paper, a windage loss characterisation strategy for Flywheel Energy Storage Systems (FESS) is presented. An effective windage loss modelling in FESS is essential for feasible and competitive design. Unlike generic aerodynamic loss models, FESS require particular attention to their unique characteristics i.e., vacuum, small airgaps, high angular speed, and presence of low friction rotor supports.The proposed model is based on several analytical and semi-empirical windage loss solutions for cylindrical and planar surface interactions, harmonised to manage the transition between laminar and turbulent flows. Also, the model is enriched by introducing corrections for rarefied gasses, using kinetic gas theory formulation. Therefore, it is possible the reduce the windage overestimation occurring with Navier–Stokes equation solutions for laminar flow. The model is compared to case studies from the literature featuring different boundary and operating conditions, to check consistency of all the harmonised models. A dedicated experimental test-rig is developed to validate the corrections to the model for rarefied gas at different vacuum levels. Then, a non-invasive characterisation approach for FESS windage losses in self-discharge phase is proposed and validated on the test-rig.

Review of Hybrid Energy Storage Systems for Hybrid Electric Vehicles

Energy storage systems play a crucial role in the overall performance of hybrid electric vehicles. Therefore, the state of the art in energy storage systems for hybrid electric vehicles is discussed in this paper along with appropriate background information for facilitating future research in this domain. Specifically, we compare key parameters such as cost, power density, energy density, cycle life, and response time for various energy storage systems. For energy storage systems employing ultra capacitors, we present characteristics such as cell voltage, cycle life, power density, and energy density. Furthermore, we discuss and evaluate the interconnection topologies for existing energy storage systems. We also discuss the hybrid battery–flywheel energy storage system as well as the mathematical modeling of the battery–ultracapacitor energy storage system. Toward the end, we discuss energy efficient powertrain for hybrid electric vehicles.

Design of an adaptive frequency control for flywheel energy storage system based on model predictive control to suppress frequency fluctuations in microgrids

Frequency fluctuations are brought on by power imbalances between sources and loads in microgrid systems. The flywheel energy storage system (FESS) can mitigate the power imbalance and suppress frequency fluctuations. In this paper, an adaptive frequency control scheme for FESS based on model predictive control (MPC) is proposed to suppress the frequency fluctuation in microgrids. Firstly, a linear-fuzzy control is proposed and employed in a frequency regulation controller (FRC) to carry out adaptive frequency control according to the frequency fluctuation and the energy of the FESS, which improves the utilization rate of the FESS, and at the same time avoid the power oscillation caused by overcharging and over-discharging situations. Secondly, a voltage regulation controller (VRC) for dynamic power balance is designed to improve the speed of FESS power balance and suppress the large fluctuation of DC bus voltage. In addition, a MPC based on quadratic programming method is proposed to make the actual current quickly follow the reference current, speed up the power response, and respond to system changes in time through real-time feedback state variables to improve system stability. Finally, the stability of the proposed control system is verified by simulation and experiment.

Control Strategy of Flywheel Energy Storage System for Improved Model Reference Adaptive System Based on Tent-Sparrow Search Algorithm

This study addresses speed sensor aging and electrical parameter variations caused by prolonged operation and environmental factors in flywheel energy storage systems (FESSs). A model reference adaptive system (MRAS) flywheel speed observer with parameter identification capabilities is proposed to replace traditional speed sensors. The proposed method uses reference and adjustable models to identify the stator resistance and permanent magnet flux (PM Flux) to mitigate the adverse effects of electrical parameter changes on control performance. The Tent chaotic mapping-improved Sparrow Search Algorithm (SSA) optimizes the Proportional-Integral (PI) controller parameters for the dual closed-loop and MRAS speed adaptation laws of the flywheel motor. Moreover, a self-switching parameter identification (SSPI) scheme, which constructs a cost function based on the current, parameter identification, and speed errors, is proposed to prevent inaccuracies in parameter identification. The MRAS observer selects the appropriate PI adaptive mechanism based on the error values, thereby enhancing identification accuracy. Simulink simulations show significant improvements in the rapidity and accuracy of the Tent-SSA optimized MRAS flywheel speed observer, enhancing the stability and robustness of the flywheel rotor. Experimental validation on a constructed FESS platform confirms the feasibility of this method.

Distributed coordinated speed control of flywheel energy storage matrix systems with model uncertainties and disturbances

SummaryThis paper studies a coordinated rotor speed control of flywheel energy storage matrix systems (FESMS) in the presence of model uncertainties and unknown disturbances. We consider the scenarios that the torque variation during the operation of flywheel energy storage system (FESS) cannot be accurately measured and the coordinated operation of FESMS is realized without the measurements of accurate rotor speeds. We design a distributed extended state observer (ESO) only using local rotor position measurements to estimate the rotor speeds and unknown disturbances. Based on the estimated states, a coordinated control strategy with the compensation of model uncertainties and unknown disturbances is proposed. The proposed control strategy has the advantage of speed‐free feature and active disturbance rejection. By using Lyapunov stability theory, sufficient conditions are given to ensure that the FESMS can achieve the reference tracking. The performance of the control strategy is verified by simulations.

Standalone and Hybridised Flywheels for Frequency Response Services: A Techno-Economic Feasibility Study

Frequency response services are one of the key components used by major electrical networks worldwide, acting to help control the frequency within set boundaries. Battery Energy Storage Systems (BESSs) are commonly deployed for this purpose; however, their potential is limited by susceptibility to cycle-based degradation and widely reported safety incidents. Flywheel Energy Storage Systems (FESSs) do not share these weaknesses and hence could be a potential candidate for longer-term participation in frequency response markets. This study presents the most in-depth and wide-ranging techno-economic analysis of the feasibility of FESSs for frequency response to date. Standalone FESSs are shown to be economically viable across a range of different specifications, achieving a positive Net Present Value (NPV) under varying economic conditions. At a capital cost of 500 GBP/kW with a discount rate of 4%, a 5C FESS can achieve an NPV of GBP 38,586 as a standalone unit. The complex trade-offs when considering hybridising FESSs and BESSs for this application are also investigated in-depth for the first time, again showing positive changes to NPV under various scenarios. Conversely, under some conditions, hybridisation can have a significant negative impact, showcasing the optimisation needed when considering hybrid systems. The impact of introducing a hybrid BESS varies from a low of decreasing the NPV of the system by GBP 97,955 to a high of increasing the NPV by GBP 119,621 depending on the configuration chosen. This comprehensive work provides the foundations for future research into FESS deployment for frequency response services and shows for the first time the circumstances under which deployment for this application would be both technically and economically viable.

Enhancing grid stability through predictive control and fuzzy neural networks in flywheel energy storage systems integration

Renewable energy systems, exemplified by solar and wind power, are increasingly integrated into modern power grids to mitigate environmental impact and reduce reliance on fossil fuels. However, the inherent intermittency and unpredictability of renewable energy sources pose challenges to grid stability and reliability. Energy Storage Systems (ESS) offer a promising solution to address these challenges by smoothing out power fluctuations and ensuring a consistent power supply. Among various ESS technologies, Flywheel Energy Storage Systems (FESS) have emerged as a noteworthy contender due to their rapid response times, low operating costs, and extended lifespan. This paper focuses on investigating the operation of a novel unit comprising a solar power system integrated with a Flywheel Energy Storage System (PV-FESS). The aim is to develop an effective control algorithm utilizing adaptive fuzzy neural networks and model predictive control (ANFIS-MPC) to manage power fluctuations stemming from renewable energy sources within the grid. The proposed control strategy aims to optimize the operation of the PV-FESS system by dynamically adjusting the energy absorption or release of the flywheel to maintain grid stability. Simulation studies conducted using Matlab-Simulink/Simcape software validate the efficacy of the ANFIS-MPC algorithm in mitigating abnormal fluctuations from renewable energy sources. The results demonstrate that the PV-FESS system effectively balances power fluctuations, ensuring a stable and reliable power output to the grid.