Emergency Power Supply Research Articles

High-Efficiency Microwave Wireless Power Transmission via Reflective Phase Gradient Metasurfaces and Surface Wave Aggregation.

Microwave Wireless Power Transfer (MWPT) technology is crucial for emergency power supply during natural disasters and powering off-grid equipment. Traditional antenna arrays, however, suffer from low energy capture efficiency, difficult impedance matching, complex synthetic networks, and intricate manufacturing processes. This paper introduces a microwave energy receiver design utilizing Reflective Phase Gradient Metasurfaces (R-PGMs) and surface wave energy convergence technology. The design leverages the effective plane wave-to-surface wave conversion capability of R-PGMs to transform incident microwave energy into a surface wave mode, which is then efficiently harvested using a circular energy convergence array before being output to a coupling port. By optimizing R-PGM parameters, an ideal 60° phase gradient distribution is achieved, facilitating the focus of surface wave energy via dispersion characteristics. These components are integrated into a hybrid antenna array, complemented by a matched energy output port structure. Numerical simulations show that this array can efficiently convert microwave energy from plane waves to surface waves, achieving a conversion efficiency of 85.32% and a collection efficiency of 68.26%. Experimental results corroborate these findings, with peak energy collection efficiency reaching 64.68% at 5.8 GHz and an RF-DC conversion efficiency of 42%, confirming the design's efficacy. Compared to conventional methods, this design simplifies the system by avoiding complex combining networks and significantly enhances the efficiency of microwave MWPT.

Multi-Scale Risk-Informed Comprehensive Assessment Methodology for Lithium-Ion Battery Energy Storage System

Lithium-ion batteries (LIB) are prone to thermal runaway, which can potentially result in serious incidents. These challenges are more prominent in large-scale lithium-ion battery energy storage system (Li-BESS) infrastructures. The conventional risk assessment method has a limited perspective, resulting in inadequately comprehensive evaluation outcomes, which impedes the provision of dependable technical support for the scientific appraisal of intricate large-scale Li-BESS systems. This study presents a novel Li-BESS-oriented multi-scale risk-informed comprehensive assessment framework, realizing the seamless transmission of assessment information across various scales. The findings from a previous smaller-scale analysis serve as inputs for a larger scale. The evaluation process of this method is more scientifically rigorous and yields more comprehensive results compared to assessment technologies just relying on a single perspective. By utilizing the proposed comprehensive assessment methodology, this study utilized the emergency power supply of nuclear power plants (NPPs) as an application scenario, demonstrating the complete implementation process of the framework and conducting a comprehensive assessment of Li-BESS feasibility as an emergency power source for NPPs. Our findings propose a novel paradigm for the comprehensive assessment of Li-BESS, which is expected to serve as a scientific foundation for decision-making and technical guidance in practical applications.

Research on mobile energy storage scheduling strategy for emergency power supply protection of post-disaster isolated loads

Aiming at the problem of insufficient power supply capacity of isolated loads in oceanic islands, a concept based on mobile energy storage and power conservation is proposed in this paper. Firstly, the energy flow and traffic flow characteristics of mobile energy storage are quantitatively analyzed, and an accurate mathematical model is established. Furthermore, the time-space distribution characteristics of load are carefully considered, and the Voronoi diagram and Tyson polygon method are introduced to determine cell differentiation. On this basis, combined with the power demand of load nodes and the energy storage characteristics of mobile energy storage vehicles, the evaluation indicators of cell energy and relative surplus energy of cells are designed, and the agent-cellular automata algorithm is used to schedule the mobile energy storage. The simulation results show that the power supply mode based on mobile energy storage can effectively improve the reliability of isolated loads. This paper provides a new perspective for solving the reliable power supply problem of isolated loads.

Opinions on the multi-grade pricing strategy for emergency power supply of mobile energy storage systems

Opinions on the multi-grade pricing strategy for emergency power supply of mobile energy storage systems

Modeling and SOC estimation of on-board energy storage device for trains under emergency traction

The sudden interruption of train power supply in an extreme environment will seriously threaten the safety of passengers and affect the operational efficiency of the railway system. In this case, the focus of attention becomes a method of running the train to the nearest rescue point based on the limited capacity of the on-board emergency energy storage device. Therefore, this paper reports research on the state of charge (SOC) estimation of train energy storage equipment to optimize the emergency traction strategy and energy utilization rate of trains to the maximum extent. First, with the emergency power supply of on-board lithium titanate batteries, the energy flow model of train emergency power supply is constructed for the first time. Second, based on the second-order equivalent circuit model and considering the utilization of regenerative braking energy, the relationship between battery capacity and open circuit voltage (OCV), temperature, current and SOC are constructed through experimental data, which significantly improves the accuracy and robustness of SOC estimation in complex and variable environments. Then, to effectively eliminate the impact of environmental on the estimation especially in the case of extremely low temperature (−20 °C), online model parameter discrimination and SOC estimation of lithium batteries are realized by combining recursive least squares with an optimal forgetting factor (FRLS) algorithm and a new temperature forgetting factor based adaptive extended Kalman filter (TFFAEKF) algorithm. The experimental results show that the proposed method achieves accurate SOC estimation, and the maximum error is less than 1% at different temperatures.

Investigation on the hydrogen absorption and dissociation properties of ball milling CeMg12/Ni/NbF5 type alloy for emergency power supply of fuel cell for meteorological radar station

In this article, in order to investigate the mechanism of action of catalysis on the hydrogenation and dehydrogenation properties of CeMg12-type alloy, the catalysis Ni and NbF5 was been added to prepare the CeMg12/Ni/NbF5 composite materials during ball milling treatment. The results in term of microstructure indicate that part of NbF5 is transformed into low valence NbF4 and helpful for forming MgF2 phase after ball milling treatment, which is advantageous for ameliorating the hydriding and dehydriding performances of experimental alloy. The results of the study from the perspective of hydrogen absorption and desorption performance test show that the increasing NbF5 decreases the enthalpy-value for hydrogen release and the platform pressure for the process of hydrogen releasing of ball-milled alloy, which is good for improving the hydrogen release performance of the alloy. The addition of a certain amount of NbF5 can effectively upgrade the kinetics of hydrogen dissociation of CeMg12-type alloy treated through mechanical ball milling. The alloy with 6 wt.% NbF5 has the best kinetic performance of hydrogen release, corresponding to activation energy can be reduced from 90.86 kJ/mol (0 wt.% NbF5) to 86.41 kJ/mol(6 wt.% NbF5).

Predictive Models for Aggregate Available Capacity Prediction in Vehicle-to-Grid Applications

The integration of vehicle-to-grid (V2G) technology into smart energy management systems represents a significant advancement in the field of energy suppliers for Industry 4.0. V2G systems enable a bidirectional flow of energy between electric vehicles and the power grid and can provide ancillary services to the grid, such as peak shaving, load balancing, and emergency power supply during power outages, grid faults, or periods of high demand. In this context, reliable prediction of the availability of V2G as an energy source in the grid is fundamental in order to optimize both grid stability and economic returns. This requires both an accurate modeling framework that includes the integration and pre-processing of readily accessible data and a prediction phase over different time horizons for the provision of different time-scale ancillary services. In this research, we propose and compare two data-driven predictive modeling approaches to demonstrate their suitability for dealing with quasi-periodic time series, including those dealing with mobility data, meteorological and calendrical information, and renewable energy generation. These approaches utilize publicly available vehicle tracking data within the floating car data paradigm, information about meteorological conditions, and fuzzy weekend and holiday information to predict the available aggregate capacity with high precision over different time horizons. Two data-driven predictive modeling approaches are then applied to the selected data, and the performance is compared. The first approach is Hankel dynamic mode decomposition with control (HDMDc), a linear state-space representation technique, and the second is long short-term memory (LSTM), a deep learning method based on recurrent nonlinear neural networks. In particular, HDMDc performs well on predictions up to a time horizon of 4 h, demonstrating its effectiveness in capturing global dynamics over an entire year of data, including weekends, holidays, and different meteorological conditions. This capability, along with its state-space representation, enables the extraction of relationships among exogenous inputs and target variables. Consequently, HDMDc is applicable to V2G integration in complex environments such as smart grids, which include various energy suppliers, renewable energy sources, buildings, and mobility data.

Hydrogen leakage risk analysis of hydrogen emergency power supply vehicles using the AET-RM method

In recent years, research and application of hydrogen fuel emergency power supply vehicle technologies have been steadily advancing. However, due to the highly flammable and explosive nature of hydrogen gas, the safety risk of hydrogen leakage has been taken seriously. Addressing the current inadequacies in the understanding of hydrogen leakage risks, unclear sources of risk, incomplete coverage of risk scenarios, and insufficiencies in risk assessment methods associated with hydrogen fuel emergency power supply vehicles, this study firstly establishes a multi-scenario and multi-factor coupled hydrogen leakage risk event database and an accident risk system. This effort focuses on the diversity of application scenarios, types of hydrogen leakage hazards and complexity of interfering factors. Subsequently, by refining existing risk assessment methods, a more balanced subjective-objective evaluation and more granular risk ratings approach, termed AET-RM, is proposed, which ensures finer risk grading. Finally, through this method, the types of hydrogen leakage hazards and their harm boundaries are clarified, achieving a systematic and precise graded quantitative assessment of risk sources, probabilities, and consequences. The study results indicate that the established event database contains no risk events rated as I (acceptable) or V (unacceptable). There are 37 events classified as low risk (rating II), accounting for 17.54% of the total. Medium-risk events (rating III) comprise 142 incidents, making up 67.30%, while high-risk events (rating IV) include 32 cases, representing 15.17%. The highest risk score, determined by the AET-RM method, pertains to a risk event in the power generation scenario, Contingencies: metal corrosion within the battery.

An allocative method of stationary and vehicle‐mounted mobile energy storage for emergency power supply in urban areas

AbstractExtreme climate events are on the rise, posing significant challenges to power systems, leading to blackouts and infrastructure damage. Energy storage plays a crucial role in enhancing grid resilience by providing stability, backup power, load shifting capabilities, and voltage regulation. While stationary energy storage has been widely adopted, there is growing interest in vehicle‐mounted mobile energy storage due to its mobility and flexibility. This article proposes an integrated approach that combines stationary and vehicle‐mounted mobile energy storage to optimize power system safety and stability under the conditions of limiting the total investment in both types of energy storages. The principal aim is to minimize the weighted energy not served index in the presence of fault conditions. By strategically allocating energy storage resources and dynamically dispatching stored energy, operators can ensure rapid response and effective power restoration, improving overall reliability in the face of extreme weather events.

Fabrication of ZnO-carbon dots composite via microcrystalline cellulose for enhanced photocatalytic hydrogen production under simulated sunlight irradiation

The composite ZnO@CDs was prepared via the hydrothermal method. Microcrystalline cellulose (MCC) was used as the source of carbon dots (CDs). X-ray diffraction, Fourier transform infrared spectrometry, scanning electron microscopy, and transmission electron microscopy analyses were used to characterize the structure and morphology of ZnO@CDs. The prepared ZnO showed a flake morphology with the exposed plane of (001). The X-ray photoelectron spectroscopy and photoluminescence spectroscopy (PL) characterization showed that CDs can be produced by decomposition of MCC and then attached on the surface of ZnO. The photocatalytic properties of ZnO@CDs were investigated under simulated sunlight irradiation. The hydrogen production reached 1240 µmol·g-1 in 30 min, which was much higher than the bare ZnO. The mechanism for the enhanced catalytic property of ZnO@CDs was studied. A high hydrogen production rate (2480 µmol·g-1·h-1) in the short term would enable ZnO@CDs to work as an emergency power supply by hydrogen production and use for restoring electricity and wireless communication in complicated situations.

Improving the quality of performing in-service inspections using manipulators

Many in-service inspections, mainly carried out by the ultrasonic method, were until recently carried out manually or semi-automated with the use of encoders. These types of inspections usually lack data recording and are dependent on the experience of the operator performing these inspections. For these reasons, in recent years one of the important activities carried out within the Research Centre Rez has been the development and production of manipulators for non-destructive testing. This article will describe in more detail the manipulators used for ultrasonic testing of the reactor head nozzles, nozzles of the emergency power supply system of steam generators treated with weld overlay, inspection of low-pressure blade dovetails and others. The developed manipulators will make it possible to refine and improve the repeatability of inspections that were previously carried out manually (more precise guidance of probes, etc.) or were not carried out at all due to inaccessibility for operators. Among other examples of the use of manipulators is in conditions where manual testing is not possible. One of the applications can be measurement using the phased array technique on pipelines during service, when the temperature on the surface of the pipeline can be up to 320°C (the maximum temperature of the primary pipeline of a nuclear power plant).

Multi-objective optimization for low hydrogen consumption and long useful life in fuel cell emergency power supply systems

The power system using hydrogen fuel cells (FCs) as the primary energy source holds significant potential for applications in emergency fields such as post-disaster relief and outdoor power supply. The operational environment of the FC emergency power supply system (FCEPSS) is challenging, with long continuous operation time, difficulties in hydrogen supply, high maintenance costs, and, accordingly, requirements for hydrogen consumption and useful life of FCs are heightened. Hence, this paper proposes a multi-objective energy management strategy (EMS) for FCEPSS. First, the structure of FCEPSS is designed based on the demand analysis in emergency scenarios. Then, the hydrogen consumption and life degradation models of FCEPSS are established. Aiming at the multi-objective optimization problem of minimizing hydrogen consumption and life degradation value in the FCEPSS, an improved multi-objective optimization algorithm is proposed. This paper converts complex constraints into the penalty term and incorporates it as one of the objectives, constructing a three-objective optimization model. To enhance the solution of multi-objective optimization problems, an improved strategy based on relaxation-tightening and three-objective sorting is proposed. Combining the fast non-dominated sorting genetic algorithm-II and the above improved strategy, an improved multi-objective optimization algorithm (IMOOA) is constructed. In the simulation, the advantages of the proposed IMOOA algorithm are verified. In the experimental part, compared with the logical threshold strategy, the proposed strategy saves 0.60% of hydrogen consumption and reduces 5.65% of life degradation within 24 h, respectively. Finally, the superiority of the multi-objective EMS utilizing the IMOOA is demonstrated.

Analysis of A Bidirectional Resonant Converter Applied in High/Low Voltage Conversion

In order to ensure the safe and reliable operation of the ship, the emergency power supply of the ship can provide short-term power supply when the main power supply of the ship fails. This paper proposes a two-way LLC resonant converter to be used in marine emergency power supplies. While ensuring the high efficiency and soft switching performance of the converter, it realizes high and low voltage conversion and bidirectional energy flow. By analyzing the topology, working principle and gain under variable frequency control of the two-way LLC resonant converter, and constructing the principle prototype and verifying its performance, the experiment shows that the application of the two-way LLC resonant converter in the emergency power supply can achieve high and low voltage The conversion and has good soft switching characteristics.

Effects of floating charge ageing on electrochemical impedance spectroscopy of lead-acid batteries

The lead-acid battery as a direct current emergency power supply to the substation is subjected to long-term floating charge ageing, which is a special working condition. However, there is limited research on estimating the battery life for floating charge ageing. Compared to other parameters, Electrochemical Impedance Spectroscopy (EIS) is closely related to changes in the battery. This paper investigates a simple and effective method based on EIS to estimate the state of health (SOH) of lead-acid batteries used in substation backup power supply. In this paper, a high-temperature floating charge ageing experiment was carried out to simulate the ageing process of backup power supply in a substation and shorten the experimental time. The Pearson correlation coefficient of impedance from 0.01 Hz to 1000 Hz was calculated with the battery's SOH, and the impedances at three frequencies (19.860 Hz, 9.931 Hz, and 3.946 Hz) with high correlation coefficients were selected as indicators of battery SOH. The proposed health indicators and method were validated by batteries retired from the substations, and the results showed that the impedances selected could be used as indicators of lead-acid batteries, with an average estimation error of 2.723 %.

Justification of measures aimed at ensuring the required fire resistance of structures enclosing NPP premises using CFD fire modeling

Introduction. The article presents a methodological approach to justifying measures designed to ensure the required fire resistance of structures enclosing NPP premises with the use of CFD (computational fluid dynamics) fire modeling. Approaches to justifying fire safety are considered using the fuel storage facility of an NPP standby diesel power plant as an example.Aim. To develop and analyze the methodological approach to justifying measures designed to ensure the required fire resistance of structures enclosing NPP premises with the use of CFD fire modeling.Materials and methods. The purpose and application scope of various methods for modeling fire dynamics was analyzed. Fire modeling used to justify measures for ensuring the required fire resistance of enclosing structures was considered using the fuel storage facility of an NPP standby diesel power plant as an example.Results. The performed analysis of different methods for modeling fire dynamics shows the possibility of using different fire simulation methods in the analysis of the fire hazard of buildings and facilities. The most dangerous fire development scenarios were modeled and the obtained results were analyzed on the example of a specific typical NPP facility in the NPP emergency power supply system. The redundancy requirements for these systems were taken into account to ensure tolerance to system failures in case of process failures and external effects on these systems.Conclusion. Since the CFD method is the most universal of the existing deterministic methods, it can be widely used to determine/revise the requirements for fire resistance of load-bearing and enclosing structures at NPP premises. It is possible to apply CFD-based fire modeling for the fire hazard of various buildings and facilities. This model is particularly effective in justifying the sufficiency of fire resistance requirements established for structures to prevent the spread of fire beyond the fire zone within the estimated burnout time of the entire fire load The obtained regularities can be used in the development/revision of regulatory documents on fire safety at operating NPPs and NPPs under construction.

Emergency power supply enabling solar PV integration with battery storage and wireless interface

ABSTRACT This paper presents a detailed investigation of an emergency power supply that enables solar photovoltaic (PV) power integration with a battery energy storage system (BESS) and a wireless interface. Through the utilisation of solar PV-based generation and BESS with wireless/contactless power transmission, the proposed method offers an easy-to-setup and flexible alternative solution for the emergency power supply (EPS) for household appliances and wireless electric vehicle (EV) charging for all weather conditions. During bad weather conditions, the battery acts as the main power supply and can be charged from the solar PV panel and during rainy days, it can be charged from the grid by the proposed wireless interface for emergency use. The proposed system is analysed by mathematical modelling, focusing on the interface of the solar PV, BESS, and load, with inductive power transfer (IPT) as a wireless power transfer (WPT) method. The simulation and a scaled-down experimental prototype are built to demonstrate that the proposed system enables wireless power transfer with PV and BESS, and easy installation can be achieved by just placing the primary charging coil of the proposed power supply close to the wireless charging pad that is available in the existing system for e.g. EV charging. The results show that the load voltage is kept constant at 48 V against the varying input characteristic of the solar panel which is the solar irradiance ranging from 20% to 100% and output characteristics of the load of the proposed integrated system with variation of 20–50%, respectively. Moreover, the wireless power transfer efficiency across the inductive coils is maintained at about 97% under these variations.

Development of Pumping-type for Turgo Impulse Micro Hydroelectric System in Emergency Power Supply

Development of Pumping-type for Turgo Impulse Micro Hydroelectric System in Emergency Power Supply

Arrangement for reliable power supply to emergency commercial customers with techno-economic performance improvement of PV enhanced distribution systems

Accelerating engagement of distributed energy resources unleashed the dependency on traditional electric power generation. To reduce the craving for traditional power dependency and unplanned outages the power distribution sectors are gradually adopting cleaner and reliable electrification. However, the unscheduled and unorganized engagement of stochastic generation from renewable energy sources (RES) makes the distribution system operation more vulnerable. For reliable and continuous power supply with RES, scheduled operation of BSSs and power capacitor (CAP) units can be integrated to provide emergency power supply support to consumers. In this paper, the supply of continuous and reliable power to commercial and emergency customers has been investigated subject to complete reliability (CR). The benefit-to-cost ratio (BCR) has been maximized to give reliable power to consumers by the minimum investment cost by utility, which can benefit both electric customers and power distribution operators in a single platform. The maximization of BCR has been evaluated by optimal S-CDS of the BSSs and S-S of CAP units’ operation through the PSO technique in the considered 28-bus active distribution network in different seasons. The techno-economic benefit of integrating only BSSs and BSSs with CAP units in the prospective locations has been analyzed. The improvement in battery life and decrease in SAENS, SADPL, and SADD have been obtained, which shows the efficacy of the proposed work.

Screen printing approach for high throughput and flexible adhesive deposition in graphite bipolar plate production

The struggle against climate change necessitates innovative technologies for storing and utilizing renewable energy. Hydrogen is considered a promising solution for harnessing renewable energy in a wide range of applications. In addition to its application as a raw material in the steel and the chemical industry, hydrogen can also be utilized as an energy carrier in conjunction with fuel cells (e.g. with Polymer Electrolyte Membrane Fuel Cells PEMFC) for heavy-duty vehicles, emergency power supplies or the maritime sector. To achieve the required electrical voltages for these applications, several hundred cells are assembled to a stack. A crucial component of an individual cell alongside the Membrane Electrode Assembly (MEA) is the Bipolar Plate (BPP), consisting of two bonded Bipolar Half Plates (BPHP). The BPP enables an inflow of reactive media, the cooling of the cell and is also required for the electrical contacting of the stacked cells as well as the overall mechanical stability. According to previous studies, fully bonded BPPs, especially in the flow field, significantly improve both mechanical and electrical properties of the entire stack. The here presented innovative approach for adhesive deposition aims at bonding graphitic BPHPs to BPPs with a high throughput capability while maintaining high flexibility and process stability. The process is based on the conventional screen printing technique, which in this case is performed without a stencil, allowing for a high flexibility regarding the cell geometry. Furthermore, the range of usable adhesives can be expanded with minor adjustments, allowing for not only paste adhesives but also thermally activated powders. With the presented approach, the adhesive volume can be controlled precisely and applied uniformly by selecting a suitable screen. The feasibility of the approach was tested and initial parameter estimations for potential industrial implementation were determined.

SIMULATION MODELING OF MULTI-PORT DC-DC CONVERTER IN MPPT SOLAR BATTERY CONTROLLERS UNDER NEURAL NETWORK CONTROL

Photovoltaic generation system - energy system, designed to convert useful solar energy through photovoltaic systems. It can consist of several components, including a solar array, DC/DC and DC/AC semiconductor converter, battery, filter or transformer, control system (CS). Depending on the application, photovoltaic systems can be operated as part of a self-contained power plant or operate on a network. Thus, it is possible to distinguish several basic configurations of photovoltaic generation systems. The standalone generation system is the most common configuration of photovoltaic generation systems, which contains rechargeable batteries (AB). This system is completely independent of the centralized power supply networks and is suitable for comfortable energy supply to consumers. The use of AB makes it possible to increase the reliability of the photovoltaic system and to extend the possibilities of using e.g. battery power is used during insufficient light or when the load exceeds the generation of solar cells. The scope of such configurations are lighting systems of residential and non-residential objects, power supply of houses and buildings, security systems and emergency power supply, power supply of remote residential and non-residential objects, Power supply to spacecraft, etc. Autonomous generation systems typically contain two transducers. The DC/DC converter acts as a battery charge controller. The control system for such a transducer may include the function of tracking the maximum power point for the maximum use of solar energy. The excess energy will be stored in AB. The DC/AC converter converts the DC current energy into the AC energy of the required frequency and voltage. The advantage of such a system is the possibility of using solar energy, both during the day and at night, due to the power of AB and the possibility of using the system at remote sites where there is no grid power supply. The disadvantage of such a system is the loss of double conversion of solar energy and the high cost of batteries. Artificial Neural Network (ANN) provides an alternative way to solve complex problems. A neural network, with the right structure, can compute the values of any continuous function with some predetermined accuracy. The neural network requires no knowledge of the internal parameters of the solar module, learns quickly, has the ability to optimize and approximate. Therefore, the use of INS to track the maximum power point is relevant and of practical and scientific importance. Keywords: multi-port DC converter, artificial neural network (ANN), rechargeable batteries (AB), pulse width modulation (PWM), solar panels (SP), MOSFET power keys