Superconducting Magnetic Energy Storage Research Articles

Enhancing Ethiopian power distribution with novel hybrid renewable energy systems for sustainable reliability and cost efficiency

Economic development relies on access to electrical energy, which is crucial for society’s growth. However, power shortages are challenging due to non-renewable energy depletion, unregulated use, and a lack of new energy sources. Ethiopia’s Debre Markos distribution network experiences over 800 h of power outages annually, causing financial losses and resource waste on diesel generators (DGs) for backup use. To tackle these concerns, the present study suggests a hybrid power generation system, which combines solar and biogas resources, and integrates Superconducting Magnetic Energy Storage (SMES) and Pumped Hydro Energy Storage (PHES) technologies into the system. The study also thoroughly analyzes the current and anticipated demand connected to the distribution network using a backward/forward sweep load flow analysis method. The results indicate that the total power loss has reached its absolute maximum, and the voltage profiles of the networks have dropped below the minimal numerical values recommended by the Institute of Electrical and Electronics Engineers (IEEE) standards (i.e., 0.95–1.025 p.u.). After reviewing the current distribution network’s operation, additional steps were taken to improve its effectiveness, using metaheuristic optimization techniques to account for various objective functions and constraints. In the results section, it is demonstrated that the whale optimization algorithm (WOA) outperforms other metaheuristic optimization techniques across three important objective functions: financial, reliability, and greenhouse gas (GHG) emissions. This comparison is based on the capability of the natural selection whale optimization algorithm (NSWOA) to achieve the best possible values for four significant metrics: Cost of Energy (COE), Net Present Cost (NPC), Loss of Power Supply Probability (LPSP), and GHG Emissions. The NSWOA achieved optimal values for these metrics, namely 0.0812 €/kWh, 3.0017 × 106 €, 0.00875, and 7.3679 × 106 kg reduced, respectively. This is attributable to their thorough economic, reliability, and environmental evaluation. Finally, the forward/backward sweep load flow analysis employed during the proposed system’s integration significantly reduced the impact of new energy resources on the distribution network. This was evident in the reduction of total power losses from 470.78 to 18.54 kW and voltage deviation from 6.95 to 0.35 p.u., as well as the voltage profile of the distribution system being swung between 1 and 1.0234 p.u., which now comply with the standards set by the IEEE. Besides, a comparison of the cost and GHG emission efficiency of the proposed hybrid system with existing (grid + DGs) and alternative (only DGs) scenarios was done. The findings showed that, among the scenarios examined, the proposed system is the most economical and produces the least amount of GHG emissions.

Neural network predictive control for fault detection and identification in DFIG with SMES for low voltage ride-through requirements

The increasing reliance on renewable energy sources brings to light the operational challenges of doubly fed induction generators (DFIGs), particularly under grid disturbances. This study introduces an innovative approach employing Neural Network Predictive Control (NNPC) for fault detection and identification (FDI) in DFIG systems, integrated with Superconducting Magnetic Energy Storage (SMES) to meet Low Voltage Ride-Through (LVRT) requirements. Our method uniquely combines NNPC for dynamic wind speed prediction and precise control of rotor-side and grid-side converters with the stability enhancement offered by SMES. Simulation results demonstrate a notable improvement in DFIG performance under variable wind conditions and grid failures. The system-maintained voltage stability at the Point of Common Coupling (PCC) with less than 5% deviation during transients and ensured consistent power output, marking a significant advancement in LVRT compliance. However, the model assumes steady-state grid conditions and does not account for extreme weather scenarios, indicating areas for future research. This study's findings contribute valuable insights into the robust operation of DFIGs within modern renewable energy grids.

Optimal Placement of Superconducting Magnetic Energy Storages in a Distribution Network with Embedded Wind Power Generation

The prevalence of distributed generation in most power grids can negatively affect their performance in terms of power loss, voltage deviation, and voltage stability. Superconducting Magnetic Energy Storages (SMESs) can help in addressing this problem as long as they are optimally placed in the distribution network. This paper presents a hybrid Grasshopper Optimization Algorithm and a Simulated Annealing (GOA-SA) method to determine the optimal placement of SMESs in a distribution network with an embedded wind power generation system. The optimization was formulated as a multi-objective problem to minimize active power losses, reactive power losses, and voltage deviation and maximize the voltage stability index. An IEEE 57-node distribution network was employed and simulations were performed using MATLAB R2020b. Based on simulations using 200 kW SMESs in discharge mode, the active power loss decreased by 82.57%, the reactive power loss decreased by 80.71%, the average voltage deviation index decreased by 66.91%, and the voltage stability index improved by 34.97%. In the charging operation mode, the active power loss increased by 24.86%, the reactive power loss increased by 8.21%, the average voltage deviation increased by 12.86%, and the voltage stability index increased by 12.79%. These results show that SMESs can improve the technical performance of a distribution network.

The Effect of the Interfacial Resistance of the Superconducting-stabilizer Film on the Typical Sector Diffusion Pace for 2G HTS Tapes

High temperature superconducting (HTS) tapes of the second generation have been widely used as energy storage materials, such as in superconducting magnetic energy storage (SMES) devices. In order to enhance the current-carrying characteristics, these systems are typically run close to the critical currents of the coated conductors; as a result, hot spots may develop, which could cause the superconductor to become quenched. In order to prevent the start of hot spots and to reduce the amount of faulting, efforts have been made to raise the normal zone propagation velocity (NZPV) in this manuscript. The interfacial resistance between the superconductor and stabilizer layer, which can act as a current flow diverter during fault circumstances, has been shown to be the key to producing massive NZPV. The tape's architecture has been slightly modified by the addition of a high resistive layer between the superconducting and stabiliser layers, where various interfacial resistances have been utilised to forecast the temperature distribution between 10 cm lengths of HTS tape. A 2D numerical model was created using COMSOL to assess the NZPV and temperature distribution of the 2G superconducting tape. It has been concluded that larger NZPVs can be achieved by using substantial interfacial resistances to prevent superconducting tape quenching.

Multifunctional Superconducting Magnetic Energy Compensation for the Traction Power System of High-Speed Maglevs

With the global trend of carbon reduction, high-speed maglevs are going to use a large percentage of the electricity generated from renewable energy. However, the fluctuating characteristics of renewable energy can cause voltage disturbance in the traction power system, but high-speed maglevs have high requirements for power quality. This paper presents a novel scheme of a high-speed maglev power system using superconducting magnetic energy storage (SMES) and distributed renewable energy. It aims to solve the voltage sag caused by renewable energy and achieve smooth power interaction between the traction power system and maglevs. The working principle of the SMES power compensation system for topology and the control strategy were analyzed. A maglev train traction power supply model was established, and the results show that SMES effectively alleviated voltage sag, responded rapidly to the power demand during maglev acceleration and braking, and maintained voltage stability. In our case study of a 10 MW high-speed maglev traction power system, the SMES system could output/absorb power to compensate for sudden changes within 10 ms, stabilizing the DC bus voltage with fluctuations of less than 0.8%. Overall, the novel SMES power compensation system is expected to become a promising solution for high-speed maglevs to overcome the power quality issues from renewable energy.

Modeling of flexible AC transmission system devices and fuzzy controller for automatic generation control of electric vehicle-injected power system

The automatic generation control (AGC) is a paradigm topic of interest that is continuously evolving for adequate power generation control in the power system. In this proposed study, a fuzzy adapted PID (FPID) controller is assigned for the AGC of the hybrid power system in various electrical risks and hazards. The hybrid power system includes traditional thermal and hydroelectric facilities along with gas and nuclear power plants. Two FACTS components, the superconducting magnetic energy storage (SMES) and the interline power flow controller (IPFC), have been included in to the system to improve stability of the system. The proposed FPID controller is developed to its full potential using the newly developed teaching learning-based optimization (TLBO) method. The TLBO technique's capability has been compared against a few common evolutionary strategies in order to demonstrate its superiority. It also shows how FPID controllers outperform traditional PID controllers. Investigations are also done on how IPFC and SMES might improve system stability performance. Owing to the outcome study, it is revealed that suggested TLBO-FPID, IPFC and SMES are most effective tool to advance the AGC mechanism. It is revealed from the outcomes that anticipated FPID controller reduces the settling time of area1 frequency (ΔF1) by 135.72 %, 428.58 % and 471.42 % over TLBO;PID, DE;PID and PSO;PI respectively. Finally, the proposed mechanisms are discussed with employing in electric vehicle integrated three-area distributed energy source-based power network to justify the efficacy of the proposed approaches.

Longitudinal Insulation Design of Hybrid Toroidal Magnet for 10 MJ High-Temperature Superconducting Magnetic Energy Storage

Longitudinal Insulation Design of Hybrid Toroidal Magnet for 10 MJ High-Temperature Superconducting Magnetic Energy Storage

Type‐2 fuzzy‐based adaptively predictive controlled variable frequency transformer coordinated to SMES for improved load frequency control

AbstractTraditionally, phase shifters powered by power electronics are used in conjunction with energy storage devices to improve the load frequency control. Conventional phase shifters provide minimal inertia and offer a significant threat to power quality due to harmonics. This study suggests the type‐2 fuzzy based adaptively predictive controlled variable frequency transformer (F2‐APC‐VFT) as a phase shifter to work in coordination with superconducting magnetic energy storage (SMES) for improved load frequency control. To assess the effectiveness of coordinated control, a two‐area, four‐machine linked power system with F2‐APC‐VFT installed in succession with the connecting line near to area one and SMES in the other area is employed. A type‐2 fuzzy controller is used to tune the cost function weights of the adaptive predictive controller (APC). A simulation study is conducted in MATLAB to show the effectiveness of the suggested strategy. Tuning the cost function weights with a type‐2 fuzzy controller considerably impacts in minimising the frequency and tie‐power deviations. The effectiveness of the F2‐APC is verified by comparing its performance with that of an adaptive neuro fuzzy inference system (ANFIS) controller and constant weight‐based adaptive predictive controller (C‐APC).

Adaptive Model Predictive Control Scheme for Application of SMES for Load Frequency Control

The use of superconducting magnetic energy storage (SMES) has been widely reported in the literature to mitigate various load frequency control (LFC) issues in a multi-area power system. Most of these are thyristor based SMES, employing proportional type controllers. In this paper, a supervisory adaptive model predictive control scheme (AMPC) is proposed for a voltage source converter based relatively small rating SMES for LFC application. The reference power command for the SMES is derived from the AMPC in such a manner that it effectively handles the operational constraints of the SMES system. A representative first-order system emulating the inner loop dynamics of the SMES chopper system, is tuned offline via genetic algorithm (GA) and is used to derive dynamic constraints for the cost function in AMPC. The effectiveness of the scheme is demonstrated through simulations.

Superconducting Magnetic Energy Storage (SMES) for Urban Railway Transportation

Superconducting Magnetic Energy Storage (SMES) for Urban Railway Transportation

Overall design of a 5 MW/10 MJ hybrid high-temperature superconducting energy storage magnets cooled by liquid hydrogen

The integration of superconducting magnetic energy storage (SMES) into the power grid can achieve the goal of storing energy, improving energy quality, improving energy utilization, and enhancing system stability. The early SMES used low-temperature superconducting magnets cooled by liquid helium immersion, and the complex low-temperature cooling system greatly limited the promotion and application of such devices. SMES based on high temperature superconductivity (HTS) materials can operate in the temperature range of 15–30 K, which simplifies the cooling system and reduces the cooling loss, and greatly improves the operating efficiency and stability of the cooling system. In this paper, the overall design of a 5 MW/10 MJ SMES based on state of the art HTS materials is achieved. The structural parameters of YBCO and MgB2 cables are introduced and the structural parameters of energy storage magnet are analyzed. And the cooling scheme for SMES is provided.

Stabilization of isolated hybrid microgrids with electric vehicle-based energy storage systems using a fractional order proportional-integral-derivative control

ABSTRACT Electric vehicles (EVs) are considered to be the most promising technology upgrades in the coming years to reduce the carbon emission, since the EVs could replace the conventional combustion vehicles as well as mitigate power fluctuations in power grids. This paper focuses on addressing the frequency stability issues in isolated hybrid grids (IHGs) by introducing a fractional order proportional-integral-derivative (FOPID) control for grid-connected power converters. A particle swarm optimization (PSO) technique is adopted to optimize the parameters of the controllers. The advantages of the proposed control method over the conventional proportional-integral-derivative (PID) control, proportional-integral with proportional-derivative (PI-PD) control, and proportional-integral-derivative with filter (PIDF) control schemes are verified by simulation case studies. Besides, a modified virtual rotor concept (MVRC) is proposed in this paper to enhance the inertia of the system. Furthermore, the performance of using EVs to regulate the frequency of IHGs is compared to the superconducting magnetic energy storage (SMES) units, capacitive energy storage (CES) units, and redox flow batteries (RFB) under fixed and variable load conditions.

Application of EV aggregators and SMES for frequency deviation control using fractional fuzzy controller

<span lang="EN-US">Secondary controllers are implemented in the alternator control loop to take care of the swinging of frequency initiated due to inequality of load and demand. A fractional fuzzy-PID controller (FFPID) is projected in this work for frequency deviation control in unified system including EV aggregators and superconducting magnetic energy storage (SMES). EVs and SMES are given primacy because of their ecofriendly nature. Proper adjustment of gains of FFPID is also required to extract the best performance of the secondary controllers. Here a recent tuning process named as artificial rabbits optimization (ARO) is applied for proper tuning of projected controller. The implemented dual area power system includes time varying delay-based EV aggregators, SMES, and thermal generating units. The ARO technique is applied in the model to tune the controller constraints with abrupt increment of demand in one of the control areas. A time-based function is treated as fitness function to evaluate the system performance. The dominance property of the projected FFPID controller over conventional PID and FPID controller in terms of different response specifications like maximum positive deviation (overshoot), settling time and minimum negative deviation (undershoot). The robust nature of the projected controller is also confirmed by multiple analysis like random load deviations and system constraint alteration.</span>

Improved Load Frequency Control in Power Systems Hosting Wind Turbines by an Augmented Fractional Order PID Controller Optimized by the Powerful Owl Search Algorithm

The penetration of intermittent wind turbines in power systems imposes challenges to frequency stability. In this light, a new control method is presented in this paper by proposing a modified fractional order proportional integral derivative (FOPID) controller. This method focuses on the coordinated control of the load-frequency control (LFC) and superconducting magnetic energy storage (SMES) using a cascaded FOPD–FOPID controller. To improve the performance of the FOPD–FOPID controller, the developed owl search algorithm (DOSA) is used to optimize its parameters. The proposed control method is compared with several other methods, including LFC and SMES based on the robust controller, LFC and SMES based on the Moth swarm algorithm (MSA)–PID controller, LFC based on the MSA–PID controller with SMES, and LFC based on the MSA–PID controller without SMES in four scenarios. The results demonstrate the superior performance of the proposed method compared to the other mentioned methods. The proposed method is robust against load disturbances, disturbances caused by wind turbines, and system parameter uncertainties. The method suggested is characterized by its resilience in addressing the challenges posed by load disturbances, disruptions arising from wind turbines, and uncertainties surrounding system parameters.

Application of optimal control for wind integrated power system

<div align="center"><span>This paper presents the modeling and application of an optimal controller for frequency and tie-line power stability for a two-area interconnected hydro-thermal power plant having tandem compound non-reheat turbines integrated with wind power generation having doubly fed induction generator (DFIG) wind turbines in each area. The power system is interconnected using AC tie-lines. The designed optimal controller was implemented and the system dynamic responses for three power system model states were obtained considering a 1% load fluctuation in one of the areas. The optimal control strategy presented in this paper depends on formulating an error value and finding the feedback gains corresponding to each state of the system, which are easily attainable as outputs. The analysis was undertaken and verified by calculating the performance index value, the closed ring real and imaginary values, finding the feedback gains, and through graphical simulations of the three system models under investigation. The output of the optimal controller was enhanced when the DFIG-based wind turbines were installed in each area combined with a superconducting magnetic energy storage (SMES) unit and a thyristor control phase shifter (TCPS).</span></div>

A model predictive control strategy for enhancing fault ride through in PMSG wind turbines using SMES and improved GSC control

Wind energy has emerged as a prominent player in the realm of renewable energy sources, both in terms of capacity and technological adaptability. Among the various renewable energy technologies, wind turbine generators stand out as the most widely employed. Recently, gearless permanent magnet synchronous generators have gained traction in the wind energy sector due to their appealing features, such as reduced maintenance costs and the elimination of gearboxes. Nevertheless, challenges remain, particularly concerning the grid-friendly integration of wind turbines, specifically with regard to high voltage ride-through (HVRT) and low voltage ride-through (LVRT) improvements. These challenges pose a threat to grid stability, impede Wind Turbine Generator performance, and may lead to significant damage to wind turbines. To address these concerns, this research proposes an integrated strategy that combines a model predictive control (MPC) superconducting magnetic energy storage (SMES) device with a modified WTG grid-side converter control. By coupling SMES devices to the dc-link of Permanent Magnet Synchronous Generator WTGs, the proposed approach aims to achieve an overvoltage suppression effect during grid disturbances and provide support for grid reactive power. Through various test scenarios, the feasibility and practicality of this suggested technique are demonstrated.

High temperature superconducting CORC cable with variable winding angles for low AC loss and high current carrying SMES system

Owing to the rising demand for enhanced high-current capacity within superconducting magnetic energy storage (SMES) system used in power grids, there is a growing focus on enhancing the current-carrying capability of SMES setups wound with conductor on round core (CORC) cables. However, it is crucial to note that the dissipation of AC losses in CORC cables during rapid charge and discharge cycles can substantially impact the safe operation of SMES. The CORC cable is crafted by spirally winding numerous ReBCO tapes around copper tubes. Even slight alterations in the winding angles of these tapes can result in shifts at current distribution across the ReBCO tapes, thus leading to differences in AC losses. Hence, the primary objective of this paper is to study the effect of varying winding angles of each ReBCO layer on AC loss. The adoption of variable angles results in the reduction of current flowing through the outermost tapes. And the AC losses in the outermost tapes happen to account for the majority of the total AC losses. Through simulations and experiments, it was observed that the AC loss in the CORC cable with variable angles (4 × 12, 25°–40°) was 25% lower than that in the case of fixed angles (3 × 11, 45°). These findings demonstrate a noteworthy downward trajectory in AC losses when variable angles are applied to the CORC cable. These insights hold significant value for the practical application of CORC cables within SMES systems.

Review of ancillary services and optimal sizing of an energy storage system in a microgrid

The rapid growth of distributed energy generation has brought new challenges for the management and operation of power systems. Voltage fluctuation is one of the primary factors preventing further photovoltaic (PV) penetration in low-voltage networks. The proper sizing and location of any storage system are essential for reducing costs and eliminating losses, which is another element. This review presents an in-depth overview of the different ancillary services that storage systems may offer and a proper sizing of energy storage systems (ESS). Different kinds of ESSs store energy in different ways. Some of these have reached their full potential, while others are still being worked on. Specific storage solutions may be picked depending on how well the application needs to run. Pumped-hydro and thermal energy storage systems are best for large-scale energy storage, while battery energy storage systems are highly suggested for high power and energy needs. Most of the time, supercapacitors, superconducting magnetic energy storage (SMES), and flywheel energy storage (FES) are used for short-term and fast-response uses. Hydrogen and methane are not often used to store energy because they could be more efficient. A few case studies are also given.

Design and Numerical Study of Magnetic Energy Storage in Toroidal Superconducting Magnets Made of YBCO and BSCCO

The superconducting magnet energy storage (SMES) has become an increasingly popular device with the development of renewable energy sources. The power fluctuations they produce in energy systems must be compensated with the help of storage devices. A toroidal SMES magnet with large capacity is a tendency for storage energy because it has great energy density and low stray field. A key component in the creation of these superconducting magnets is the material from which they are made. The present work describes a comparative numerical analysis with finite element method, of energy storage in a toroidal modular superconducting coil using two types of superconducting material with different properties bismuth strontium calcium copper oxide (BSCCO) and yttrium barium copper oxide (YBCO). Regarding the design of the modular torus, it was obtained that for a 1.25 times increase of the critical current for the BSCCO superconducting material compared with YBCO, the dimensions of the BSCCO torus were reduced by 7% considering the same stored energy. Also, following a numerical parametric analysis, it resulted that, in order to maximize the amount of energy stored, the thickness of the torus modules must be as small as possible, without exceeding the critical current. Another numerical analysis showed that the energy stored is maximum when the major radius of the torus is minimum, i.e., for a torus as compact as possible.

Modeling and exergy analysis of an integrated cryogenic refrigeration system and superconducting magnetic energy storage

Superconducting magnetic energy storage (SMES) systems widely used in various fields of power grids over the last two decades. In this study, a thyristor-based power conditioning system (PCS) that utilizes a six-pulse converter is modeled for an SMES system. The main subject of this research is the generation of required helium for an SMES because for the coil to be at superconducting temperature, it needs to always be immersed in liquid helium. In the conducted simulation, the helium production system provided, in which primarily the gaseous helium temperature was reduced by heat transfer in LNG heat exchangers, and then after the sudden pressure drop, it turned into a liquid. The effect of the various firing angles is investigated, and it is found that at angles lower than 90°, at a specific angle, the output current enhances with time. In the 90°, this current remains constant, and at degrees greater than 90°, the output current reduces with time. The percentage of input flows to the expanders is investigated to find the rate of the maximum liquid helium production amount to the inlet gaseous helium. The diverted ratio of mass flow via expander 1 and expander 2 was 0.46 and 0.35, respectively. The system's work utilization of network, and liquid helium production is 67.18 MW and 12.7 kg/h. Also, the exergy analysis is done and the results show 35.7 % exergy efficiency. The efficiency of helium production has a direct relation to liquid nitrogen mass flow. However, due to the required high power for producing liquid nitrogen, with mass flow rate increment, the total system's efficiency is reduced. The results are evaluated with Aspen HYSYS, Aspen Energy Analyzer, and MATLAB. Specific work obtained from the analysis is 290,097 kW.s/kg which indicates that uses lower power in comparison with the other helium production methods which saves power and electrical costs.