High-speed Flywheel Energy Storage System Research Articles

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.

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.

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.

Research on Low Switching Loss Control Strategy of High-Speed FESS Based on NPC Three-Level Converter

The high-speed flywheel energy storage system (FESS) has been used in urban rail transit system to provide network stability and regenerative braking energy recovery due to its merits of high-power density, almost infinite charging–discharging cycles, nonexistent capacity deterioration, and environmental friendliness. The electrical fundamental frequency of the FESS motor/generator will be significantly increased when the rotor is mainly composed of carbon fiber composites to achieve higher speed. In addition, in view of the 1500-VDC power supply of the urban rail transit system, the switching loss of the power switching devices will be significantly increased or the system failure may be occurred when the high switching-to-fundamental frequency ratio (SFFR) control strategy is applied. Therefore, a low SFFR <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$=$ </tex-math></inline-formula> 1 control strategy of the I-type neutral point clamped (NPC) three-level converter for the high-speed FESS with brushless direct current (BLDC) motor in two-phase conduction mode is designed, and the matching midpoint voltage balance strategy is proposed. The effectiveness of the proposed control strategy is verified by simulation and experiments. The stable and low switching loss operation of the high-speed FESS rated at 1500 VDC, 330 kW, and 36 000 r/min is realized, and the midpoint voltage balance is strongly controlled.

Linear Robust Discharge Control for Flywheel Energy Storage System With RLC Filter

High speed becomes an important development direction of flywheel energy storage system (FESS) for higher energy storage density. However, the high speed leads to a wide-range and rapid speed variation (tens of thousands of revolutions in seconds) and a limited frequency modulation index, both of which aggravate the current harmonics and deteriorate the robustness of the discharge control, and even lead to instability. To address this issue, this article proposes a robust and practical discharge control strategy for high-speed FESS with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RLC</i> filter, which realizes speed adaptation and harmonic suppression. In this scheme, the linear extended state observer and two-degree-of-freedom internal model control (TDOF-IMC) are applied to FESS in the framework of linear active disturbance rejection control (LADRC). Besides, considering that high-speed FESS usually require sensorless control due to magnetic bearings, a reduced-order Luenberger observer for the investigated FESS is proposed. The salient feature of this strategy is to introduce the TDOF-IMC containing FESS dynamic information into LADRC, so that the discharge control is both practical and robust. Experiments and simulations verify the effectiveness of the control strategy.

Adaptive droop control strategy for Flywheel Energy Storage Systems: A Power Hardware-in-the-Loop validation

Low-inertia power systems can suffer from high rates of change of frequency during imbalances between the generation and the demand. Fast-reacting storage systems such as a Flywheel Energy Storage System (FESS) can help maintain the frequency by quickly reacting to frequency disturbances, with no concern over its lifetime. While a modern high-speed FESS has a significantly higher energy density than the conventional low-speed ones, the capacity of this storage technology is still limited. Therefore, this paper proposes a new adaptive droop controller for a FESS, considering the practical advantages and also limitations of this storage technology. The proposed controller increases the contribution of the FESS for frequency support during the first instances of a disturbance, while it reduces its output when the frequency is recovering. To verify the advantages of the proposed control strategy, the controller is implemented on a real 60 kW high-speed FESS using the concept of rapid control prototyping. Next, the performance of the FESS with the new controller is tested using Power Hardware-in-the-Loop simulations in a low-voltage microgrid. The PHIL simulation results show that the proposed adaptive controller improves the performance of the FESS in terms of limiting the frequency deviations, while preserving more energy in the FESS.

Design and Evaluation of High-Speed FESS Converter for 1500 VDC Urban Rail Transit System

The urban rail transit system has the characteristics of wide voltage fluctuation, intermittent and strong impact load, limited heat dissipation capacity. The high-speed flywheel energy storage system (FESS) is used to provide network voltage stability and regenerative braking energy recovery due to its high power density, unlimited number of charge-discharge cycles, fast response and environmental friendliness. When considering the design of high-speed FESS converter with 3.6 kHz fundamental frequency and 330 kW rated power used in 1500 VDC urban rail transit system, the two-stage topological converter reduces the efficiency and increase the cost and size, meanwhile, the series-connected converters and the multilevel converter increase the difficulties of control and insulation, so the two-level and I-type three-level converters of high-speed FESS are designed and evaluated. Several comparisons are made by detailed experimental data from the perspective of the traction load characteristics of the 1500 VDC urban rail transit system and the technical and economical requirements of the high-speed FESS. It is found that the three-level converter has significant advantages in matching the traction load characteristics for its higher duty cycle capability, as well as improving the technical and economical performances such as efficiency, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">du/dt</i> value, THD, voltage stability, and reducing the cost by 40% when compared to the two-level converter. While in the future MW class high-speed FESS development, the maximum output power capacity of the three-level FESS is relatively lower than that of the two-level FESS. The theoretical analyses were verified by experiments.

Model validation of a high-speed flywheel energy storage system using power hardware-in-the-loop testing

Low-inertia power systems with a high share of renewables can suffer from fast frequency deviations during disturbances. Fast-reacting energy storage systems such as a Flywheel Energy Storage System (FESS) can help limit the frequency deviations by injecting or absorbing high amounts of active power, with almost no degradation concerns. But for an accurate evaluation of the benefits of using a FESS in power systems, an accurate and validated model is necessary, which not only reflects its advantages, but also shows the practical limitations of this technology, such as its losses, its auxiliary power requirements, and its limitations during the whole operational range. In this paper, an accurate model for a high-speed FESS is presented, and then experimentally validated by means of Power Hardware-in-the-Loop (PHIL) testing of a full-scale commercial high-speed FESS in several frequency deviation scenarios. The PHIL testing setup allows testing the FESS during extreme and realistic frequency deviation, including the major frequency disturbance of August 9, 2019, in the power system of the UK. In each scenario, the same inputs that are sent to the real FESS are also given to the FESS model, running in real time, for model validation, and an excellent match between the results of the real FESS and its model is observed. Moreover, the PHIL testing results demonstrate the quick response of the FESS, following a frequency deviation, and its compliance with the latest grid code requirements in Germany for frequency support.

Prototype production and comparative analysis of high-speed flywheel energy storage systems during regenerative braking in hybrid and electric vehicles

In conventional EVs and HEVs, only a small part of the vehicle's kinetic energy can be usefully stored during deceleration. Generally, this storage process can be done by providing energy flow to the main battery of the vehicle. Since batteries work with a chemical reaction, they are not suitable for fast charging and discharging required for regenerative braking. In this case, a fast storage system is needed to store the regenerative braking energy in a short time. As a solution, the flywheel energy storage system (FESS) can be offered.In the literature, power transmission of vehicles with integrated FESS is provided by mechanical systems (CVT FESS). These systems are heavy, high cost, large volume, and occupy the rear axle of the vehicle.In the proposed system, a purely electrical power transmission is proposed to store the kinetic energy of the vehicle in FESS. In developed topology, the traction machine of the vehicle is also used as a generator, and the recuperation energy is stored in the electrically driven (M/G) FESS.As a result of the experimental studies, a minimum of 56% energy recovery efficiency was obtained. In addition, it has been shown that the developed system is 30% lighter, occupies 60% less space in volume, is at least 50% more cost-effective, maintenance-free, and has fewer moving parts compared to the CVT FESS.As a result, the addition of a fast-response secondary energy storage system to the electric vehicle battery contributes to the increase in efficiency.

Adaptive inertia emulation control for high‐speed flywheel energy storage systems

Low-inertia power systems suffer from a high rate of change of frequency (ROCOF) during a sudden imbalance in supply and demand. Inertia emulation techniques using storage systems, such as flywheel energy storage systems (FESSs), can help to reduce the ROCOF by rapidly providing the needed power to balance the grid. In this work, a new adaptive controller for inertia emulation using high-speed FESS is proposed. The controller inertia and damping coefficients vary using a combination of bang–bang control approaches and self-adaptive ones, to simultaneously improve both the ROCOF and the frequency nadir. The performance of the proposed adaptive controller has been initially validated and compared with several existing adaptive controllers by means of offline simulations, and then validated with experimental results. The proposed controller has been implemented on a real 60 kW high-speed FESS, and its performance has been evaluated by means of power hardware-in-the-loop (PHIL) testing of the FESS in realistic grid conditions. Both simulations and PHIL testing results confirm that the proposed inertia emulation control for the FESS outperforms several previously reported controllers, in terms of reducing the maximum ROCOF and improving the frequency nadir during large disturbances.

Research Review of Flywheel Energy Storage Technology

to study the flywheel energy storage technology, a great number of papers about the researches on and development of high-speed flywheel energy storage system in China and overseas were reviewed and summarized. The technology started early in foreign countries. It developed rapidly and has formed a certain series of products today, while in China, the research on this technology is quite laggard and still in the experimenting stage. Now there is no flywheel energy storage product which can be applied in practice in quantity. Therefore, the research on a new type of efficient and low power consumption energy storage flywheel is of great value and significance today.

A Novel Optimal Power Control for a City Transit Hybrid Bus Equipped with a Partitioned Hydrogen Fuel Cell Stack

The development of more sustainable and zero-emissions collective transport solutions could play a very important measure in the near future within smart city policies. This paper tries to give a contribution to this aim, proposing a novel approach to fuel cell vehicle design and operation. Traditional difficulties experienced in fuel cell transient operation are, in fact, normally solved in conventional vehicle prototypes, through the hybridization of the propulsion system and with the complete fulfillment of transients in road energy demand through a high-capacity onboard energy storage device. This makes it normally necessary to use Li-ion battery solutions, accepting their restrictions in terms of weight, costs, energy losses, limited lifetime, and environmental constraints. The proposed solution, instead, introduces a partitioning of the hydrogen fuel cell (FC) and novel optimal power control strategy, with the aim of limiting the capacity of the energy storage, still avoiding FC transient operation. The limited capacity of the resulting energy storage systems which, instead, has to answer higher power requests, makes it possible to consider the utilization of a high-speed flywheel energy storage system (FESS) in place of high energy density Li-ion batteries. The proposed control strategy was validated by vehicle simulations based on a modular and parametric model; input data were acquired experimentally on an operating electric bus in real traffic conditions over an urban bus line. Simulation results highlight that the proposed control strategy makes it possible to obtain an overall power output for the FC stacks which better follows road power demands, and a relevant downsizing of the FESS device.

Active Magnetic Bearing Design and Backstepping-Adaptive Control for High-Speed Rotors

Friction and vibrations hindering high-speed are the most pertinent problems facing the rotating machines. Thus, friction and vibration attenuation are essential in improving the overall performance of turbomachines. Conventionally, high-speed flywheel energy storage systems use Active Magnetic Bearings (AMB) to nullify friction losses and to deal with unbalances but, in the present era with increasing demand for high-speed machinery, the applications of AMBs are proliferating. They are not like the traditional bearings; they generate forces through magnetic fields with no contact between bearing and rotor thus decreasing the friction and providing the ability to counteract imbalances actively. This paper investigates an optimized design methodology along with backstepping adaptive control design of an 8-pole radial AMB used for flywheel energy storage systems. Design optimization using GA, along with analytical design constraints are presented. The design details along with finite element simulations are given to verify the optimization results and system requirements. Bearing parameters then obtained are used to develop a linearized mathematical model of the system, an adaptive back-stepping controller is designed for it to regulate the deviation of the rotating shaft from its equilibrium position.

A DC-Link Voltage Fast Control Strategy for High-Speed PMSM/G in Flywheel Energy Storage System

This paper presents a dc-link voltage fast control strategy for high-speed permanent magnet synchronous motor/generator of flywheel energy storage system (FESS) to ensure fast dynamic performance within its wide operation range. Instead of the conventional strategy with cascaded outer dc-link voltage loop and inner current loop, the proposed strategy is a direct voltage control strategy without an intermediate current loop. The nonlinear dc-link voltage loop model is globally linearized by treating the square of dc-link voltage as the state variable, and lumping the nonlinear and uncertain terms in the power balance equation as the total disturbance. An extended state observer (ESO) is designed to observe the total disturbance, and a control law that compensates the speed variation and the total disturbance is proposed. The inner dynamic of the proposed ESO is analyzed, and the tracking performance and antidisturbance capability of the proposed strategy is hereby derived. Finally, the proposed strategy is validated on a high-speed FESS test bench.

A Robust Flywheel Energy Storage System Discharge Strategy for Wide Speed Range Operation

Wide speed range operation in discharge mode is essential for ensuring discharge depth and energy storage capacity of a flywheel energy storage system (FESS). However, for a permanent magnet synchronous motor/generator-based FESS, the wide-range speed variation in a short discharge period causes consecutive decreases in ac voltage frequency and amplitude. As a result, operation point shift leads to performance deterioration of the conventional local linearization based dc-link voltage control strategies. This study aims to realize a consistent robust discharge performance within the entire available operation range for FESS. We propose a robust discharge strategy that incorporates the speed variation to the dc-link voltage controller. A speed-dependent extended state observer is designed to realize global linearization and enhance the robustness. A speed adaptive feedback control law is designed to ensure consistent dynamic performance within the entire available operation range. Finally, the discharge strategy is validated at different speeds on a high-speed FESS test bench.

Modeling and Stability Analysis of Hybrid PV/Diesel/ESS in Ship Power System

Due the concern about serious environmental pollution and fossil energy consumption, introducing solar generation into ship power systems has drawn greater attention. However, the penetration of solar energy will result in ship power system instability caused by the uncertainties of the solar irradiation. Unlike on land, the power generated by photovoltaic (PV) modules on the shipboard changes as the ship rolls. In this paper, a high-speed flywheel energy storage system (FESS) is modeled to smooth the PV power fluctuations and improve the power quality on a large oil tanker which contains a PV generation system, a diesel generator, a FESS, and various types of ship loads. Furthermore, constant torque angle control method combined with sinusoidal pulse width modulation (SPWM) approach is proposed to control the FESS charging and discharging. Different ship operating situations and the impact of the ship rolling is taken into consideration. The simulation results demonstrate the high efficiency and fast response of the flywheel energy storage system to enhance the stability of the proposed hybrid ship power system.

The Dynamic Analysis of an Energy Storage Flywheel System With Hybrid Bearing Support

Active magnetic bearings and superconducting magnetic bearings were used on a high-speed flywheel energy storage system; however, their wide industrial acceptance is still a challenging task because of the complexity in designing the elaborate active control system and the difficulty in satisfying the cryogenic condition. A hybrid bearing consisting of a permanent magnetic bearing and a pivot jewel bearing is used as the support for the rotor of the energy storage flywheel system. It is simple and has a long working life without requiring maintenance or an active control system. The two squeeze film dampers are employed in the flywheel system to suppress the lateral vibration, to enhance the rotor leaning stability, and to reduce the transmitted forces. The dynamic equation of the flywheel with four degrees of complex freedom is built by means of the Lagrange equation. In order to improve accuracy, the finite element method is utilized to solve the Reynolds equation for the dynamic characteristics of the squeeze film damper. When the calculated unbalance responses are compared with the test responses, they indicate that the dynamics model is correct. Finally, the effect of the squeeze film gap on the transmitted force is analyzed, and the appropriate gap should be selected to cut the energy loss and to control vibration of the flywheel system.

Transient stability control of multimachine power systems using flywheel energy injection

Owing to advances in many technologies, the high-speed flywheel energy storage system (FESS), flywheel battery, has become a viable alternative to electrochemical batteries and attracted much research attention in recent years. A self-organising fuzzy neural network controller is presented for FESS to improve transient stability and increase transfer capability of power systems. The main difference from a traditional control approach lies in the model-free description of the control system and parallel computing capability. Simulation results from the Taiwan power system (Taipower) show that FESS with the proposed controller has produced significant improvement in power system performance.

A superconducting high-speed flywheel energy storage system

High-speed flywheel systems have been studied as compensators of voltage sags and momentary interruptions of energy. Besides the complexity of these systems, the main concerns are bearing losses. This work is part of the development of a superconducting high-speed flywheel energy storage prototype. In order to minimize the bearing losses, this system uses a superconducting axial thrust magnetic bearing in a vacuum chamber, which guarantees low friction losses, and a switched reluctance motor-generator to drive the flywheel system. Dynamic simulations made for this prototype, connected to the electric power network, show the viability of use it as a compensator.