Flywheel Energy Storage System Research Articles

Feasibility Assessment of a Small-Scale Agrivoltaics-Based Desalination Plant with Flywheel Energy Storage—Case Study: Namibia

As climate change and population growth threaten rural communities, especially in regions like Sub-Saharan Africa, rural electrification becomes crucial to addressing water and food security within the energy-water-food nexus. This study explores social innovation in microgrid projects, focusing on integrating micro-agrovoltaics (APV) with flywheel energy storage systems (FSSs) and small-scale water desalination and purification plants. Employing a mixed-methods approach to assess the economic viability of FSS and APV-powered desalination, we believe that social innovation could serve as a significant tool for rural development, requiring collaboration between governments, the private sector, and nonprofit organizations. While FSS technology for microgrids has not been entirely developed, it holds promise as an alternative energy storage solution. Our capital budgeting analysis, presented within the context of social innovation, reveals positive Net Present Values (NPV) and a short payback period over the project’s 20-year lifespan.

Minimum loss optimization of flywheel energy storage systems via distributed adaptive dynamic programming

AbstractIn this article, a distributed controller based on adaptive dynamic programming is proposed to solve the minimum loss problem of flywheel energy storage systems (FESS). We first formulate a performance function aiming to reduce total losses of FESS in power distribution applications. Then we use the Hamilton–Jacobi–Bellman (HJB) equation to solve this optimal control problem. The solution of the HJB equation is approximated by neural networks. To achieve distributed control, we estimate the global variables in the HJB equation by using the dynamic average consensus algorithm. A barrier Lyapunov function and a saturation function are introduced to handle the issue of state and input constraints, respectively. Then the stability of the system is proved through the Lyapunov stability analysis. Finally the effectiveness of the proposed strategy is verified by simulations. Simulation results show that FESS can track the power command while minimizing total power losses by interacting with neighbors. The proposed algorithm leads to a loss reduction of compared to the equal power distribution strategy.

Strategy of Flywheel–Battery Hybrid Energy Storage Based on Optimized Variational Mode Decomposition for Wind Power Suppression

The fluctuation and intermittency of wind power generation seriously affect the stability and security of power grids. Aiming at smoothing wind power fluctuations, this paper proposes a flywheel–battery hybrid energy storage system (HESS) based on optimal variational mode decomposition (VMD). Firstly, the grid-connected power and charging–discharging power of the HESS are determined based on the sliding average algorithm. Secondly, the VMD algorithm, optimized using long short-term memory (LSTM), is used to decompose the hybrid energy storage power (HESP) into a series of sub-modes with frequencies from low to high. Then, the state of charge of the battery energy storage system and the speed of the flywheel energy storage system are monitored in real time, and the primary power of the HESS is modified according to the rules formulated by fuzzy control. Finally, through a simulation example, it is concluded that the method meets the requirements of smoothing wind power fluctuations and gives full play to the characteristics of energy storage battery and flywheel energy storage to ensure the stable operation of the energy storage system. The method presented in this paper can provide a reference for HESP configuration and control operation strategy formulation.

Research on Energy Storage Flywheel Motor Drive Control Technology

Currently there is a way to use for energy storage: batteries for chemical energy storage, super for electric field energy storage, and flywheel batteries for mechanical energy storage. Flywheel energy storage has the advantages of high energy storage density, high efficiency, short charging time, no pollution, wide applicability, no noise, long service life, easy maintenance and continuous operation. Recently the most promising and competitive new energy storage technology - flywheel energy storage technology, relative to other forms of energy storage, by domestic and foreign experts unanimously optimistic. This paper will focus on the composition and operation principle of flywheel energy storage system, the classification of drive control strategy, charging control strategy, discharge control strategy and other aspects.

Review of Mechanical, Electrochemical, Electrical, and Hybrid Energy Storage Systems Used for Electric Vehicles

The population rate in the world is increasing rapidly. Depending on the population, the need for transportation increases at the same rate. Traditional vehicles, which provide great convenience in transportation, bring with them some disadvantages. For example, the fossil fuel used in conventional vehicles creates greenhouse gases such as CO2 and N2O. This has a negative impact on global warming. To eliminate these negativities, interest in electric vehicle (EV) and hybrid electric vehicles (HEV) technology studies has increased recently. Some problems have arisen with these technological studies. The range problem in vehicles is the biggest of these problems. Therefore, various solutions are sought for energy storage problems in vehicles. In this article, studies on HEV and energy storage in EVs are examined. According to the data obtained because of this examination, the performance analysis of the Energy Storage Systems (ESS) was made. The performances of the electrochemical batteries used in HEVs and EVs were compared. In addition to these, flywheel energy storage system was also investigated in HEVs and EVs to recover the energy lost because of braking.

Research on intelligent control system of permanent magnet motor for high-speed flywheel energy storage system based on deep learning

With the continuous development of society, more and more people pay attention to energy issues, and the realization of energy storage has become a hot research direction today. Despite advancements, the control system of the high-speed flywheel energy storage system’s permanent magnet motor still encounters issues in effectively regulating the magnetic suspension bearing and motor speed. In addressing this issue, a technical solution involves the implementation of an intelligent control system for the high-speed flywheel energy storage system’s permanent magnet motor, utilizing deep learning principles. This innovative approach employs deep neural networks to model, optimize, and regulate the flywheel energy storage system. The essence of flywheel energy storage lies in the conversion of electrical energy into mechanical energy, followed by its reconversion into electrical energy during output. It has the advantages of high energy density, high power density, long cycle life, fast charging and discharging, maintenance-free and environmental protection. A permanent magnet motor is a motor that uses permanent magnets to generate a magnetic field. It has the characteristics of high efficiency, high power density, and low rotor loss. It remains the most widely utilized motor in flywheel energy storage systems. An intelligent control system is characterized by its use of artificial intelligence technology to adapt, self-learn, and self-organize complex systems. This system is distinguished by its robust nonlinear processing capabilities and resilience to faults. The high-speed flywheel energy storage system permanent magnet motor intelligent control system based on deep learning can improve the performance, efficiency and reliability of the flywheel energy storage system, reduce costs and risks, and is suitable for electric vehicles, rail transit, power grid frequency regulation and other fields. In this paper, the convolutional neural network and PSO algorithm are used to obtain the PSNN neural network structure to predict the speed of the motor, so as to achieve its control. And the reliability of the structure is verified by experiments.

AI-Based Control of Storage Capacity in High-Power-Density Energy Storage Systems, Used in Electric Vehicles

Exempting batteries from supplying power transients in Electric Vehicles (EVs) is beneficial to extend their useful lifespan. The adaptive capacity of High Power-density Energy Storage Systems (HPESSs) like ultracapacitors or high-speed Flywheel Energy Storage Systems (FESSs) could fulfill the targets in this context. This paper proposes a sizing/control methodology and real-time AI-based control of the storage capacity for the adaptive capacity HPESSs, used in EVs. The sizing approach consists of an optimal energy management strategy and a sizing algorithm applied to a Variable-Step HPESS (VS-HPESS). This methodology derives the battery/VS-HPESS power-split and sizes of the storage capacities. In addition, a Nonlinear Autoregressive Neural Network with eXogenous inputs (NARX-NN) is trained offline to switch the desirable capacity of the VS-HPESS in real-time operation. Finally, an experiment is designed to evaluate the proposed real-time control scheme, in which the EV power transients are emulated and applied to a dual-capacitance ultracapacitor as the VS-HPESS. The results confirm the capability of the proposed approach to meet the considered targets.

Research on Control Strategy of High-Speed Grid-Connected FESS (Flywheel Energy Storage System) Based on Dual-PWM Converter

Research on Control Strategy of High-Speed Grid-Connected FESS (Flywheel Energy Storage System) Based on Dual-PWM Converter

Distributed fixed-time cooperative control for flywheel energy storage systems with state-of-energy constraints

This paper studies the cooperative control problem of flywheel energy storage matrix systems (FESMS). The aim of the cooperative control is to achieve two objectives: the output power of the flywheel energy storage systems (FESSs) should meet the reference power requirement, and the state of FESSs must meet the relative state-of-energy (SOE) variation rate constraints. When the above objectives are reached, the FESSs are able to track reference power command while ensuring that all flywheels are fully charged or discharged at the same time. To achieve these two objectives, a distributed power allocation strategy is proposed. A distributed estimator is designed to estimate the global state information required for each FESS in the allocation strategy. In addition, a fixed-time estimator based on a dynamic average consensus algorithm is designed, which is capable of quickly estimating the global average information. The convergence of the fixed-time estimator under the boundedness assumption of the time derivative of input signal is analyzed by the Lyapunov stability theory. The simulation results show that the FESSs interact with neighbors through local information such that the evolution of the SOE among the FESSs satisfies the constraints and the total power tracks the total reference power. Furthermore, compared with the existing methods, the proposed dynamic average consensus estimators achieve an accurate tracking of the global state information in a fixed time, regardless of the initial conditions.

Low‐voltage ride‐through control strategy for flywheel energy storage system

AbstractDue to its high energy storage density, high instantaneous power, quick charging and discharging speeds, and high energy conversion efficiency, flywheel energy storage technology has emerged as a new player in the field of novel energy storage. With the wide application of flywheel energy storage system (FESS) in power systems, especially under changing grid conditions, the low‐voltage ride‐through (LVRT) problem has become an important challenge limiting their performance. In this paper, we propose a machine‐grid side coordinated control strategy based on model predictive current control (MPCC) for the insufficient LVRT capability of traditional FESS during grid faults. Excellent dynamic properties are demonstrated by the technique, which allows the grid‐side converter output current to swiftly follow the reference current instruction. The FESS's LVRT capability is increased when the grid‐side converter uses the MPCC current inner loop rather than the proportional–integral current inner loop during grid voltage dips. This greatly increases the reactive power response speed and efficiently supports the quick recovery of grid voltage. According to simulation verification carried out by Matlab/Simulink, the suggested control approach can assure the long‐term dependable operation of the FESS during voltage dips. This study can also be used as a reference for improving the FESS's LVRT capabilities in the future.

Applications of Tungsten Pseudo-Alloys in the Energy Sector

New energy generation methods are currently being discussed with a view towards the transition from traditional primary sources to more environmentally friendly options, particularly renewables. Energy storage is also closely related to this transition. Battery storage currently dominates this area. However, flywheel energy storage system technology offers an alternative that transforms stored kinetic energy into mechanical and electrical energy using a motor generator. The flywheel energy storage system technology is thus flexible and can be applied in different industrial applications. The management of the technology of recycling tungsten multi-metallic composites (W-MMC) waste material from other products and the subsequent trial production of high-strength W-MMC material with a density of more than 17,500 kg/m3 from recycled powders allowed us to test the limits of the so-called “heavy” flywheels used in rotor production. The results achieved lead to the conclusion that the developed recycled materials of the W-MMC type with a density ≥17,500 kg/m3, with a yield strength of 1200–1700 MPa depending on the production method, can be used as a substitute for the structural steels used today without an enforced reduction in the maximum allowed rotor speed due to exceeding the maximum allowed stress.

Accounting for the Temperature Dependence of Hardness in Numerical Simulation of Wear in Pivot-Jewel Bearings

Pivot-jewel bearings are important components in rotor systems and flywheel energy storage systems; the relative rotation speed can reach about 10³ rps under nominal operating conditions, while the lifespan can amount to years. Wear calculations of the contact surfaces are necessary in such scenarios to assess the life cycle of friction joints. Accounting for the variation in the surface hardness due to friction heating can considerably affect the amount of wear in the contact surface.

Multiphysics Analysis of Flywheel Energy Storage System Based on Cup Winding Permanent Magnet Synchronous Machine

Multiphysics Analysis of Flywheel Energy Storage System Based on Cup Winding Permanent Magnet Synchronous Machine

Improved Gorilla Troops Optimizer-Based Fuzzy PD-(1+PI) Controller for Frequency Regulation of Smart Grid under Symmetry and Cyber Attacks

In a smart grid (SG) system with load uncertainties and the integration of variable solar and wind energies, an effective frequency control strategy is necessary for generation and load balancing. Cyberattacks are emerging threats, and SG systems are typical cyber-attack targets. This work suggests an improved gorilla troops optimizer (iGTO)-based fuzzy PD-(1+PI) (FPD-(1+PI)) structure for the frequency control of an SG system. The SG contains a diesel engine generator (DEG), renewable sources like wind turbine generators(WTGs), solar photovoltaic (PV), and storage elements such as flywheel energy storage systems (FESSs) and battery energy storage systems (BESSs) in conjunction with electric vehicles (EVs). Initially, the dominance of the projected iGTO over the gorilla troops optimizer (GTO) and some recently suggested optimization algorithms are demonstrated by considering benchmark test functions. In the next step, a traditional PID controller is used, and the efficacy of the GTO method is compared with that of the GTO, particle swarm optimization (PSO), and genetic algorithm (GA) methods. In the next stage, the superiority of the proposed FPD-(1+PI) structure over fuzzy PID (FPID) and PID structures is demonstrated under various symmetry operating conditions as well as under different cyberattacks, leading to a denial of service (DoS) and delay in signal transmission.

Integrated Optimal Energy Management and Sizing of Hybrid Battery/Flywheel Energy Storage for Electric Vehicles

This paper presents an integrated optimal Energy Management Strategy (EMS) and sizing of a high-speed Flywheel Energy Storage System (FESS) in a battery electric vehicle (EV). The methodology aims at extending the battery cycle life and drive range by relegating fast dynamics of the power demand to the FESS. For the EMS, the battery power and FESS energy are considered as weighted objectives of an optimization problem that are established using Pontryagin's Minimum Principle (PMP). In order to derive the optimal FESS size, the sizing algorithm is targeted to minimize the battery degradation level and increase the FESS energy interaction with the system. The performance of the proposed methodology is assessed using some driving cycles including ECE-15, UDDC, HWFET, and US06. Comparing the proposed battery/FESS to the battery-only topology, the battery SoH and life cycle are improved considerably for different driving cycles.

Vibration Characteristics and Vibration Mitigation Analysis of End Cap PM Excitation Homopolar Inductor Machine

Vibration analysis and vibration mitigation are very important to ensure the safe and stable operation of electrical machines applied in flywheel energy storage systems (FESS). In traditional integer slot synchronous machines, it is generally believed that there is only the zeroth-mode vibration caused by odd tooth harmonics. However, the homopolar inductor machine (HIM) adopts the end cap excitation structure, which makes its air-gap magnetic field contain the DC component, odd tooth harmonics and even tooth harmonics. The force density distribution on the slotted stator is analyzed by the magnetomotive force-multiplying permeance method. The results show that there are both zeroth- and pth(pole pairs)-mode vibrations caused by tooth harmonics and DC component of the air-gap flux density. Furthermore, to reduce vibration and resonance, and to improve the electromagnetic performance of HIM, it is best to use the stator skew slot, the magnetic slot wedge (MSW) and the sinusoidal rotor slot at the same time. Finally, a 54-slot/6-pole EPE-HIM is tested to validate the analytical and the finite-element method (FEM) results, and the variation trend of the experimental results and FEM results is the same.

Research on control strategy of flywheel energy storage system based on active disturbance rejection control

The flywheel energy storage system (FESS) has been attracting the attention of national and international academicians gradually with its benefits such as high energy power density, high conversion productivity, and inexpensive pollution. For the mutual limitation problem of reaction speed and overshoot of the conventional PI controller, it is hard to satisfy the demand of high efficiency control. In this study, the Active Disturbance Rejection Controller (ADRC) is adopted to substitute the classical PI controller in the flywheel energy storage control system. The control system of an external loop of speed and an internal loop of current is adopted at the motor side. The standard ADRC is adopted by increasing the new nonlinear control function. The control system adopted the control strategy of the DC bus voltage external loop and the current internal loop on the grid side, as well as the second-order Linear Active Disturbance Rejection Controller (LADRC), to enhance the control ability of the DC bus voltage. In the charge/discharge control of the FESS, both the velocity external loop and current internal loop control strategies are utilized to simplify the system structure. The performance shows that the improved control system could effectively enhance the charging and discharging speed of the FESS and effectively suppress the DC bus voltage rise caused by flywheel state switching so that the system has better robustness.

Analysis of the Amount of Flux Variation on the HTS Surface by the Oscillation of HTS Magnetic Bearing Rotor

Magnetic bearing is used in flywheel energy storage system and can address energy loss at contact points in rotating because a rotor can be supported without contact points. However, in order to keep a rotor levitating, a control system is required. The HTS magnetic bearing levitates the rotor by pinning force without a control system and of a rotor including permanent magnets and a HTS. The vertical oscillation of the rotor is suppressed because the flux is interlinked to the outside of the HTS. Therefore, the rotor oscillates in the horizontal direction in rotating. This oscillation generates the flux variation on the HTS surface and it decreases the number of revolutions. This paper proposes an analysis of flux variation on the HTS surface by the oscillation of HTS magnetic bearing rotor. The effect of the oscillation of the rotor on the number of revolutions is shown by the analysis of the flux variation of the HTS. In the analysis results, the amount of flux variation increased rapidly because the rotor increases the oscillation. The flux variation causes a decrease the in number of revolutions and the small oscillations cause flux variation on the HTS surface. However, the decrease in the number of revolutions is small because the amount of the flux variation is small.

Hybrid cyber-attack compensation of sustainable microgrid using active disturbance rejection control strategy

A modified active disturbance rejection control (ADRC) strategy for the frequency regulation of sustainable microgrid against hybrid cyber-attacks is proposed in this paper. The proposed technique mitigates the effect of attacks which in turn regulates the frequency of microgrid. The sustainable microgrid consists of solar and wind as renewable energy sources, energy storage systems (ESSs) like battery ESS and flywheel ESS, and controllable sources of energy like fuel cell and diesel generator. The cyber-attacks such as false data injection, denial-of-service and time delay attack are considered for designing the proposed ADRC technique. The robustness of the microgrid system with the proposed controller is investigated by varying generation and load, stochastic nature of attacks, parametric uncertainties and generation rate constraint and governor dead band nonlinearities. Further, the stability analysis of the microgrid with proposed ADRC is investigated under the aforementioned cyber-attacks using the small gain theorem.

Permanent Magnet Motors in Energy Storage Flywheels

Flywheel energy storage system stores energy in the form of mechanical energy and can convert mechanical energy into electrical energy. Flywheel energy storage is a mechanical energy storage system. Due to its high energy storage density, high power, high efficiency, long life, no pollution and other characteristics, it has a broad application prospect in the field of aerospace, power peaking, UPS, electric vehicles, high-power electromagnetic guns and so on. With the continuous development of magnetic levitation, composite materials, vacuum and other technologies, the current flywheel energy storage technology is mainly through the increase in the speed of the flywheel rotor to achieve energy storage, the continuous development of various technologies, so that the research of flywheel energy storage technology has stepped into the "high-speed" development period, and has been widely used in many fields. Application, and gradually become the focus of research in various countries.