Anomaly-Resistant Decentralized State Estimation Under Minimum Error Entropy With Fiducial Points for Wide-Area Power Systems

This paper investigates the anomaly-resistant decentralized state estimation(SE) problem for a class of wide-area power systems which are divided into several non-overlapping areas connected through transmission lines. Two classes of measurements(i.e., local measurements and edge measurements) are obtained, respectively, from the individual area and the transmission lines. A decentralized state estimator, whose performance is resistant against measurement with anomalies, is designed based on the minimum error entropy with fiducial points(MEEF) criterion. Specifically, 1) An augmented model, which incorporates the local prediction and local measurement, is developed by resorting to the unscented transformation approach and the statistical linearization approach;2) Using the augmented model, an MEEF-based cost function is designed that reflects the local prediction errors of the state and the measurement;and 3) The local estimate is first obtained by minimizing the MEEF-based cost function through a fixed-point iteration and then updated by using the edge measuring information. Finally, simulation experiments with three scenarios are carried out on the IEEE 14-bus system to illustrate the validity of the proposed anomaly-resistant decentralized SE scheme.

Abnormal State Detection in Lithium-ion Battery Using Dynamic Frequency Memory and Correlation Attention LSTM Autoencoder

This paper addresses the challenge of identifying abnormal states in Lithium-ion Battery(LiB)time series data.As the energy sector increasingly focuses on integrating distributed energy resources,Virtual Power Plants(VPP)have become a vital new framework for energy management.LiBs are key in this context,owing to their high-efficiency energy storage capabilities essential for VPP operations.However,LiBs are prone to various abnormal states like overcharging,over-discharging,and internal short circuits,which impede power transmission efficiency.Traditional methods for detecting such abnormalities in LiB are too broad and lack precision for the dynamic and irregular nature of LiB data.In response,we introduce an innovative method:a Long Short-Term Memory(LSTM)autoencoder based on Dynamic Frequency Memory and Correlation Attention(DFMCA-LSTM-AE).This unsupervised,end-to-end approach is specifically designed for dynamically monitoring abnormal states in LiB data.The method starts with a Dynamic Frequency Fourier Transform module,which dynamically captures the frequency characteristics of time series data across three scales,incorporating a memory mechanism to reduce overgeneralization of abnormal frequencies.This is followed by integrating LSTM into both the encoder and decoder,enabling the model to effectively encode and decode the temporal relationships in the time series.Empirical tests on a real-world LiB dataset demonstrate that DFMCA-LSTM-AE outperforms existing models,achieving an average Area Under the Curve(AUC)of 90.73%and an F1 score of 83.83%.These results mark significant improvements over existing models,ranging from 2.4%–45.3%for AUC and 1.6%–28.9%for F1 score,showcasing the model’s enhanced accuracy and reliability in detecting abnormal states in LiB data.

Predicting of Power Quality Steady State Index Based on Chaotic Theory Using Least Squares Support Vector Machine

An effective power quality prediction for regional power grid can provide valuable references and contribute to the discovering and solving of power quality problems. So a predicting model for power quality steady state index based on chaotic theory and least squares support vector machine (LSSVM) is proposed in this paper. At first, the phase space reconstruction of original power quality data is performed to form a new data space containing the attractor. The new data space is used as training samples for the LSSVM. Then in order to predict power quality steady state index accurately, the particle swarm algorithm is adopted to optimize parameters of the LSSVM model. According to the simulation results based on power quality data measured in a certain distribution network, the model applies to several indexes with higher forecasting accuracy and strong practicability.

Dynamic State Forecasting in Electric Power Networks

The real time monitoring and control have become very important in electric power system in order to achieve a high reliability in the system. So, improvement in Energy Management System (EMS) leads to improvement in the monitoring and control functions in the control center. In this paper, DSE is proposed based on Weighted Least Squares (WLS) estimator and Holt’s exponential smoothing to state predicting and Extended Kalman Filter to state filtering. The results viewing the dynamic state the estimator performance under normal and abnormal operating conditions.

POWER OPTIMIZATION OF FINITE STATE MACHINE BASED ON GENETIC ALGORITHM

Using state assignment to minimize power dissipation and area for finite state ma-chines is computationally hard. Most of published results show that the reduction of switchingactivity often trades with area penalty. In this paper, a new approach is proposed. Experimentalresults show a significant reduction of switching activity without area penalty compared withprevious publications.

Effects of reservoir fluids on sand packs consolidated by furan and epoxy resins:Static and dynamic states

One of the most effective methods for sand control is the chemical consolidation of sandstone structures.In this paper,the impacts of crude oil and brine in the static state and the impact of the flow rates of the fluids in the dynamic state have been assessed at the reservoir conditions.The analyses in this research were Young’s modulus,compressive strength,porosity,and permeability which were done on core samples after and before fluid contact.Samples made with two different resins showed good resistance to crude oil in both states.No considerable change was seen in the analyses even at high crude oil injection rates in the dynamic state.Conversely,brine caused a noticeable change in the analyses in both states.In the presence of brine at the static state,Young’s modulus and compressive strength respectively decreased by 37.5%and 34.5%for epoxy cores,whereas these parameters respectively reduced by 30%and 41%for furan cores.In brine presence at the dynamic state,compressive strength reduction was 10.28 MPa for furan and 6.28 MPa for epoxy samples and their compressive strength reached 16.75 MPa and 26.54 MPa respectively which are higher than the critical point to be known as weak sandstone core.Moreover,Young’s modulus decrease values for furan and epoxy samples were respectively 0.37 GPa and 0.44 GPa.Therefore,brine had a more destructive effect on the mechanical characteristics of samples in the static state than the dynamic one for two resins.In addition,brine injection increased permeability by about 13.6%for furan and 34.8%for epoxy.Also,porosity raised by about 21.8%for furan,and 19%for epoxy by brine injection.The results showed that the chemical sand consolidation weakens in the face of brine production along with crude oil which can lead to increasing cost of oil production and treating wellbore again.

Short-term prediction of photovoltaic power generation based on LMD-EE-ESN with error correction

Considering the instability of the output power of photovoltaic(PV)generation system,to improve the power regulation ability of PV power during grid-connected operation,based on the quantitative analysis of meteorological conditions,a short-term prediction method of PV power based on LMD-EE-ESN with iterative error correction was proposed.Firstly,through the fuzzy clustering processing of meteorological conditions,taking the power curves of PV power generation in sunny,rainy or snowy,cloudy,and changeable weather as the reference,the local mean decomposition(LMD)was carried out respectively,and their energy entropy(EE)was taken as the meteorological characteristics.Then,the historical generation power series was decomposed by LMD algorithm,and the hierarchical prediction of the power curve was realized by echo state network(ESN)prediction algorithm combined with meteorological characteristics.Finally,the iterative error theory was applied to the correction of power prediction results.The analysis of the historical data in the PV power generation system shows that this method avoids the influence of meteorological conditions in the short-term prediction of PV output power,and improves the accuracy of power prediction on the condition of hierarchical prediction and iterative error correction.

A hybrid method integrating Green's function Monte Carlo and projected entangled pair states

This paper introduces a hybrid approach combining Green’s function Monte Carlo(GFMC)method with projected entangled pair state(PEPS)ansatz.This hybrid method regards PEPS as a trial state and a guiding wave function in GFMC.By leveraging PEPS’s proficiency in capturing quantum state entanglement and GFMC’s efficient parallel architecture,the hybrid method is well-suited for the accurate and efficient treatment of frustrated quantum spin systems.As a benchmark,we applied this approach to study the frustrated J_(1)–J_(2) Heisenberg model on a square lattice with periodic boundary conditions(PBCs).Compared with other numerical methods,our approach integrating PEPS and GFMC shows competitive accuracy in the performance of ground-state energy.This paper provides systematic and comprehensive discussion of the approach of our previous work[Phys.Rev.B 109235133(2024)].

Development of a Medium Voltage, High Power, High Frequency Four-Port Solid State Transformer

The power and voltage levels of renewable energy resources is growing with the evolution of the power electronics and switching module technologies.For that,the need for the development of a compact and highly efficient solid-state transformer is becoming a critical task in-order to integrate the current AC grid with the new renewable energy systems.The objective of this paper is to present the design,implementation,and testing of a compact multi-port solid-state transformer for microgrid integration applications.The proposed system has a four-port transformer and four converters connected to the ports.The transformer has four windings integrated on a single common core.Thus,it can integrate different renewable energy resources and energy storage systems.Each port has a rated power of 25 kW,and the switching frequency is pushed to 50 k Hz.The ports are chosen to represent a realistic industrial microgrid model consisting of grid,energy storage system,photovoltaic system,and load.The grid port is designed to operate at 4.16 k VAC corresponding to 7.2 kV DC bus voltage,while the other three ports operate at 500 VDC.Moreover,the grid,energy storage and photovoltaic ports are active ports with dual active bridge topologies,while the load port is a passive port with full bridge rectifier one.The proposed design is first validated with simulation results,and then the proposed transformer is implemented and tested.Experimental results show that the designed system is suitable for 4.16 k VAC medium voltage grid integration.

Study on the Horizontal Movement State of Suction Anchor Piles for Offshore Wind Power during Horizontal Pulling

The subsea anchor piles of offshore wind power floating platform structures are mainly subjected to uplift and horizontal loads, and this paper focuses on the case of horizontal loads. A three-dimensional numerical simulation study of the horizontal pullout characteristics of wind power suction anchor piles in clay layers was carried out to reveal the horizontal movement state of the anchor piles during horizontal pile pullout, the range of pile depth at the pullout point where the horizontal movement is achieved (referred to as the horizontal movement range), the relationship between the pullout load and the ultimate load during the horizontal movement, and the optimal location of the pullout point for the horizontal movement. The results show that at certain pull-out points, the anchor pile produces an overall horizontal movement state under suitable horizontal pull-out loads. The depth of the pile pull-out point for horizontal movement is in the middle and lower part of the pile, i.e. 14.2 m to 14.5 m. The horizontal pull-out load of 24,000 kN at a depth of 14.5 m within the pile horizontal movement range of 14.2m to 14.5 m is the maximum ultimate horizontal pull-out load;the optimum pull-out point depth is 14.5 m at 0.275 L (L is the pile length). For each pull-out point of the anchor pile in horizontal movement, the horizontal pull-out load in horizontal movement and the horizontal ultimate pull-out load existed and it was found that the two values were not exactly the same, the values were compared and it was found that at the optimum pull-out point the value of the ultimate horizontal pull-out load/horizontal pull-out load in horizontal movement tended to 1.

Evaluation of Generalized Error Function via Fast-Converging Power Series

A generalized form of the error function, Gp(x)=pΓ(1/p)∫0xe−tpdt, which is directly associated with the gamma function, is evaluated for arbitrary real values of p>1and 0x≤+∞by employing a fast-converging power series expansion developed in resolving the so-called Grandi’s paradox. Comparisons with accurate tabulated values for well-known cases such as the error function are presented using the expansions truncated at various orders.

Robust Nonlinear Current Sensorless Control of the Boost Converter with Constant Power Load

The boost converter feeding a constant power load (CPL) is a non-minimum phase system that is prone to the destabilizing effects of the negative incremental resistance of the CPL and presents a major challenge in the design of stabilizing controllers. A PWM-based current-sensorless robust sliding mode controller is developed that requires only the measurement of the output voltage. An extended state observer is developed to estimate a lumped uncertainty signal that comprises the uncertain load power and the input voltage, the converter parasitics, the component uncertainties and the estimation of the derivative of the output voltage needed in the implementation of the controller. A linear sliding surface is used to derive the controller, which is simple in its design and yet exhibits excellent features in terms of robustness to external disturbances, parameter uncertainties, and parasitics despite the absence of the inductor’s current feedback. The robustness of the controller is validated by computer simulations.

New thermal optimization scheme of power module in solid-state amplifier

The new 1 kW power module for ADS project needs the optimization of cooling design including water flow and tunnel layout, and the water flow of three tons per hour was chosen to be a goal for a 20 kW power source.According to analysis from the insertion and integrated loss, about 24 modules were integrated into the rated power. Thus, every module has a cooling flow of 2.1 L/min for RF heat load and power supply loss, which is very hard to achieve if no special consideration and techniques. A new thermal simulation method was introduced for thermal analysis of cooling plate through CST multi-physics suite,especially for temperature of power LDMOS transistor.Some specific measures carried out for the higher heat transfer were also presented in this paper.

Tri-state Modulation Power Driving of Electro-hydraulic Proportional Amplifier

Switch electro-hydraulic proportional amplifier（PA） widely employs single switch modulation power driving（SSMPD） or reverse discharging power driving（RDPD） at present. SSMPD has slow dynamic response, and can＇t adjust independently the dither signal＇s amplitude and frequency; RDPD accelerates the current decay; consequently, it increases current ripple and power loss. For the purpose of solving the above mentioned problem, the tri-state modulation power driving（TSMPD） scheme was proposed for improving the performance of power driving. Detailedly, the hardware circuit for the tri-state modulation power driving is designed; the tri-state modulation algorithm is realized by digital signal processor（DSP）. The tri-state modulation power driving is investigated by experiments, comparetive experiments among the single switch modulation power driving（SSMPD）, reverse discharging power driving（RDPD）, and the TSMPD are implemented, and the experimental results demonstrate that the linearity error of TSMDP meets the requirement of PA; the current response of TSMSP is the best; the amplitude of ripple current of the TSMPD can be reduced without increasing frequency of PWM, in addition, dither signal amplitude and frequency can be adjusted independently for each other. It is very meaningful to guide the development of high performance proportional amplifier for high frequency response proportional solenoid.

A Steady State Voltage Stability Analysis of Wind Power Centralized System

It is significant to research the voltage stability of the wind power centralized system (WPCS) for the effective development of the large scale clustering wind energy resources. A steady state voltage stability analysis of the WPCS by employing the PV curve and model analysis is proposed to reveal the voltage stability influence from different aspects. The PV curve is utilized to trace and indicate the voltage collapse point of the WPCS when the small disturbance of wind power is increased gradually. Then the steady state voltage instability modes of the WPCS are analyzed by calculating the bus participation factors of the minimum eigenvalue model at the collapse point. The simulation results of an actual WPCS in North China show that the static state voltage instability mode of the WPCS is closely related to the operating features and control strategies of different reactive power sources. In addition, the implementation of the doubly-fed induction generator wind turbine generator voltage control is beneficial to improve the WPCS voltage stability.

All-solid-state flexible asymmetric supercapacitors with high energy and power densities based on NiCo_2S_4@MnS and active carbon

Electrode material based on a novel core–shell structure consisting of NiCoS（NCS） solid fiber core and Mn S（MS） sheet shell（NCS@MS） in situ grown on carbon cloth（CC） has been successfully prepared by a simple sulfurization-assisted hydrothermal method for high performance supercapacitor. The synthesized NiCoS@Mn S/CC electrode shows high capacitance of 1908.3 F gat a current density of 0.5 A gwhich is higher than those of NiCoSand Mn S at the same current density. A flexible all-solid-state asymmetric supercapacitor（ASC） is constructed by using NiCoS@Mn S/CC as positive electrode, active carbon/CC as negative electrode and KOH/poly（vinyl alcohol）(PVA) as electrolyte. The optimized ASC shows a maximum energy density of 23.3 Wh kgat 1 A g, a maximum power density of about7.5 kw kgat 10 A gand remarkable cycling stability. After 9000 cycles, the ASC still exhibited67.8% retention rate and largely unchanged charge/discharge curves. The excellent electrochemical properties are resulted from the novel core–shell structure of the NiCoS@Mn S/CC electrode, which possesses both high surface area for Faraday redox reaction and superior kinetics of charge transport. The NiCoS@Mn S/CC electrode shows a promising potential for energy storage applications in the future.

State Estimation of Regional Power Systems with Source-Load Two-Terminal Uncertainties

The development and utilization of large-scale distributed power generation and the increase of impact loads represented by electric locomotives and new energy electric vehicles have brought great challenges to the stable operation of the regional power grid.To improve the prediction accuracy of power systems with source-load twoterminal uncertainties,an adaptive cubature Kalman filter algorithm based on improved initial noise covariance matrix Q0 is proposed in this paper.In the algorithm,the Q0 is used to offset the modeling error,and solves the problem of large voltage amplitude and phase fluctuation of the source-load two-terminal uncertain systems.Verification of the proposed method is implemented on the IEEE 30 node system through simulation.The results show that,compared with the traditional methods,the improved adaptive cubature Kalman filter has higher prediction accuracy,which verifies the effectiveness and accuracy of the proposed method in state estimation of the new energy power system with source-load two-terminal uncertainties.

Assessing Strategy of Power Transformers Insulation State Based on Part-division and Entropy Method

Failure mechanisms of power transformers are complex and uncertain; it is difficult to determine index weights of insulation state. Therefore, it is a challenge to acquire an accurate assessment of insulation state of power transformers. In this paper, an assessing strategy for transformer insulation is proposed base on part-division of transformer and a comprehensive weight determination method. An index system of transformer is established on the basis of part-division of transformer. Each index’s weight is consisted of two parts, the constant weight and the variable weight, which are determined by improved analytic hierarchy process (AHP) and entropy method respectively. Af- ter categorizing insulation state into four levels and standardizing assessing indexes, a Cauchy membership function is forged, and a fuzzy algorithm is employed to simulate the uncertainty of the insulation state. Finally, a confidence criterion is employed to perform part-division based condition assessment of transformer. Case studies reveal that the proposed assessing strategy method is effective, convenient, and practical; with the new strategy, potential failures of transformers can be forecasted and insulation state of transformer parts can also be as- sessed. Furthermore, the assessing results can be used to guide condition-based maintenance.

Comparison of Earnings Power between State Commercial Banks and Stock Banks

As earnings power is one of the primary capacities for commercial banks, by analyzing several indexes on banks' operation performance, this article compared the earnings power between the state banks and the stock banks in China. Through the analysis, some problems of domestic banks may be found and pointed out that the commercial bank should stress on the target of profit maximum to avoid the financial risks. With enough earnings power, the domestic banks can take the challenge with those foreign banks entering domestic money market.

An S-band solid-state radio frequency power amplifier used at Shanghai soft X-ray FEL facility

In this paper,we present the general design methods and parameter measurements of a 1-k W solidstate radio frequency(RF) power amplifier at 2856 MHz,for the soft X-ray free electron laser facility.Three-stage amplification with a 4-way combination is used.An RF switch module is integrated with the solid-state RF power amplifier to convert the continuous wave(CW) signal into pulse signal,with adjustable pulse width.The power gain is measured at 57.7 d B at 60 d Bm output.The RF phase noise,which is measured by the low-level RF system,is\0.015 degree(RMS),while the pulse frontier jitter is\5 ns.