Unit Power Research Articles

Research on Frequency Regulation with Dynamic Trajectory Planning of Participation Factors

The energy transformation has led to a high proportion of new energy entering the grid. New energy has high randomness, which challenges the frequency stability of the power system. A new approach to improve frequency based on dynamic trajectory planning of participation factors is proposed in this work. In the frequency regulation interval, the trajectory and termination time of participation factors are regarded as the variables to be optimized. Then, taking the frequency regulation performance and economy as the goals, a multi-objective optimization problem is constructed. The participation factors are used to dispatch the output power of different units, which breaks the constraint that the output characteristics of different units are consistent in the original regulation process. Therefore, the generator units with different regulation characteristics in the system achieve complementary coordination on the second time scale. In simulation cases, frequency oscillation is reduced, while the overall economy of the system is improved. The numerical evaluation results show that the frequency performance is improved by 2.7% at most and 2.9% of the economy is improved at most simultaneously. The above results demonstrate the effectiveness of the proposed approach.

Experimental study on the vacuum dehumidification performance of PVA/CaCl2 selective permeation membrane under vortex conditions

Vacuum membrane dehumidification is a promising power-saving isothermal dehumidification technology, and the development of low-cost and efficient selective permeation membranes is beneficial to its application. In this study, the dehumidification performance and mechanism of the PVA/CaCl2 water vapor selective permeation membrane are investigated experimentally. The effects of the CaCl2 concentration in the casting membrane solution, the permeation side vacuum level, and the inlet air flow rate and relative humidity on the dehumidification performance are discussed. In addition, the effect of the deflector fins on the dehumidification performance is analyzed. The results show that the vortex coupled dissolution-diffusion theory can explain the experimental results. In addition, from the point of view of dehumidification capacity per unit power consumption, the best concentration of CaCl2 in casting membrane solution is 2.08 %, and the worst permeation side vacuum level is 60 kPa. The higher the inlet air flow rate and relative humidity under the deflector fins, the better the dehumidification performance. The dehumidification performance can be significantly improved by the deflector fins, which increase the COP by 38.31 %∼146 % and the selectivity by 35.85 %∼147 %.

The human lower leg muscle pump functions as a flow diverter pump, maintaining low ambulatory venous pressures during locomotion

ObjectiveAmbulatory venous pressure (AVP) is the drop of pressure observed in the superficial veins of the lower leg during movement. This phenomenon has been linked to the function of the calf muscle pump (CMP) and the competence of venous valves. Nevertheless, the concept of the CMP function remains controversial. This study aimed to elucidate the association between lower leg muscles activity, changes in pressure in distinct venous segments, and lower extremity arterial blood supply in healthy subjects during various types and intensities of exercise. MethodsTwelve legs of nine healthy volunteers were enrolled in the study. Continuous pressure (intramuscular vein [IV] and three great saphenous vein [GSV] points) and surface electromyography data (gastrocnemius and anterior tibial [ATM] muscles) were recorded during treadmill walking, running, and plantar flexion exercises. The pressure gradient (ΔP, mmHg) between adjacent points of measurement was calculated. Minute unit power of muscle pump ejection and suction (NE, and NS, MPa/min) were calculated and compared with the arterial blood supply of the lower extremity (LBF, L/min). ResultsΔP demonstrated a consistent pattern of changes during walking and running. In GSV, the ΔP was observed to be directed from the thigh to the mid-calf (retrogradely) and from the ankle to the mid-calf (anterogradely) throughout the entire stride cycle. However, its value decreased with increasing stride cycle frequency. The dynamics of ΔP between the IV and GSV were as follows: It was directed from the IV to GSV during gastrocnemius contraction and was reversed during anterior tibial muscle contraction and gastrocnemius relaxation (swing phase). LBF, NE, and NS demonstrated similar exponential growth with increasing stride frequency during walking and running. ConclusionsDuring natural locomotion, the muscle pump acts as a flow diverter pump, redirecting the flow of blood from the superficial veins to the intramuscular veins via the perforating veins. During ambulation, the pressure in the superficial venous network depends upon the capacity of the muscle pump to provide output that matches the changes in arterial blood flow.

Sustainable Operation Strategy for Wet Flue Gas Desulfurization at a Coal-Fired Power Plant via an Improved Many-Objective Optimization

Coal-fired power plants account for a large share of the power generation market in China. The mainstream method of desulfurization employed in the coal-fired power generation sector now is wet flue gas desulfurization. This process is known to have a high cost and be energy-/materially intensive. Due to the complicated desulfurization mechanism, it is challenging to improve the overall sustainability profile involving energy-, cost-, and resource-relevant objectives via traditional mechanistic models. As such, the present study formulated a data-driven many-objective model for the sustainability of the desulfurization process. We preprocessed the actual operation data collected from the desulfurization tower in a domestic ultra-supercritical coal-fired power plant with a 600 MW unit. The extreme random forest algorithm was adopted to approximate the objective functions as prediction models for four objectives, namely, desulfurization efficiency, unit power consumption, limestone supply, and unit operation cost. Three metrics were utilized to evaluate the performance of prediction. Then, we incorporated differential evolution and non-dominated sorting genetic algorithm-III to optimize the multiple parameters and obtain the Pareto front. The results indicated that the correlation coefficient (R2) values of the prediction models were greater than 0.97. Compared with the original operation condition, the operation under optimized parameters could improve the desulfurization efficiency by 0.25% on average and reduce energy, cost, and slurry consumption significantly. This study would help develop operation strategies to improve the sustainability of coal-fired power plants.

Energy consumption analysis and operating characteristics research on small time scale of variable refrigerant flow air conditioning systems in public buildings

In order to analyze the energy consumption and operation characteristics of the variable refrigerant flow (VRF) air-conditioning system on small time scale and put forward effective energy-saving suggestions, the VRF system operation experiments are carried out under different indoor set temperatures, different indoor unit opening quantities and different indoor set air velocities. This experiment studies the main influencing factors of energy consumption and operation of the VRF system, such as indoor temperature difference, indoor air velocity, outdoor environment temperature and so on. The results show that the rated power of indoor unit is linearly related to the energy consumption of the VRF system. The total active power changes greatly when the VRF starts and stops, and the outdoor ambient temperature changes. The indoor set air velocities have a great influence on the energy consumption and operation of the VRF system. The performance parameters increase first and then decrease with the increase of compressor frequency and load rate. When the load rate is 40 %∼60 %, the performance parameters can reach 3.2 ∼ 4.2.

Techno-Economic evaluation and multi-objective optimization of a filter equipped solar chimney system

Urban air pollution has recently become a pressing challenge, and innovative solutions are needed to reduce it. The current study proposes and investigates the performance of integrating a solar chimney system with an air filtration unit to mitigate urban air pollution and generate electricity simultaneously. A comprehensive computational fluid dynamics model coupled with optimization techniques is proposed to analyze and optimize the design parameters from system performance and cost perspectives. A multi-objective optimization is performed to determine the optimal placements of the air filter and geometric parameters of the hybrid solar chimney to maximize power output and filtration efficiency while minimizing the capital cost. Results indicated that placing the filter in the middle of the chimney resulted in optimal configuration with a power output of 18.83 kW, and filter efficiency of 53.73 % at a cost of $ 4.83 million, whereas placing the filter close to the inlet of the collector achieved the highest output power of 100.4 kW, a filter efficiency of 89.67 % at a capital cost of $ 7.35 million. It is concluded that placing the filter on the collector side is more beneficial in terms of performance and cost per unit of power produced.

Coordinated Control of Transient Voltage Support in Doubly Fed Induction Generators

The large-scale integration of wind power significantly alters the voltage dynamic characteristics of power systems. Wind turbines have a weak ability to withstand grid disturbances and have difficulty in providing effective reactive power support during transient periods. The sensitivity of wind turbines to the grid voltage significantly increases the probability of large-scale, cascading off-grid events. This paper proposes a coordinated control strategy to enhance the transient reactive power support capability of doubly fed wind farms. The additional stator current demagnetization control reduces the risk of a crowbar protection action after a fault and ensures that the unit power is controllable. Based on the voltage–reactive power coupling relationship, each unit can produce reactive power according to the voltage–reactive power sensitivity matrix during the transient period. After the reactive power output of the unit reaches the limit, transient active and reactive combined control is further adopted to reduce the active power output of the unit to a certain extent and improve the reactive power support capability. Finally, two cases are built in the PSCAD to verify the effectiveness of the proposed control strategy. The results show that the proposed control strategy can enable the wind farm to output more reactive power to the grid during the transient period, effectively supporting the system voltage during the transient process and avoiding further deterioration of the fault.

Triboelectric-electromagnetic hybrid wind energy harvesting and multifunctional sensing device for self-powered smart agricultural monitoring

The power supply for numerous small electronic sensors, which are extensively used in agricultural settings, is a critical challenge for advancing the Agricultural Internet of Things (IoT) and fostering the development of smart agriculture in the upcoming era of intelligent technology. Hereby, a triboelectric-electromagnetic hybrid wind energy harvesting and sensing device (TEH-WSD) based on triboelectric-electromagnetic hybrid generator (TEHG) and multi-channel triboelectric nanogenerator (MC-TENG) for wind direction and speed sensing is proposed. Among them, the TEHG is used to collect wind energy. The instantaneous peak power of TENG units and EMG unit in TEHG can reach 5.95 mW and 5.65 mW respectively. In addition, the modified TEHG can measure the wind speed within the range of 3–5 m/s, and the output signal of MC-TEHG can be used to measure the wind direction based on the corresponding circuit and designed program continuously. Overall, TEH-WSD is capable of detection for the wind direction, wind speed, temperature and humidity information in the environment and this work provides a solution for wind energy collection and self-powered environmental monitoring in agricultural environment.

Global dynamic features and information of adjacent hidden layer enhancement based on autoencoder for industrial process soft sensor application

AbstractThere is a lack of consideration of temporal and spatial correlation in the process variables and adjacent hidden layers correlation in the soft sensor model of stacked autoencoders. To address the issue, a novel global dynamic adjacent layer information enhancement auto encoder (GD‐ALIEAE) method is proposed to improve the poor prediction performance. The gated recurrent unit (GRU) and uniform manifold approximation and projection (UMAP) are applied to the GD‐ALIEAE model for obtaining global dynamic features of the temporal and spatial information of process variables by parallel computation. An adjacent layer information correlation algorithm is proposed to avoid the loss of hidden layers information during the stacking process. The algorithm enhances the features of the low layer through nonlinear mapping, combining the low layer and its adjacent layer as input. The input then is fed to the multi‐head attention mechanism to obtain features that contain adjacent layer correlation. Finally, a prediction model is established through a fully connected layer. Through simulation experiments on two industrial cases of sulphur recovery unit and thermal power plant, and compared with models of stacked autoencoder (SAE), stacked isomorphic autoencoder (SIAE), and target‐related stacked autoencoder (TSAE), the effectiveness of the proposed method was verified.

Solutions for the Implementation of Algorithms for Closed-Loop Control of the Frequency and Power of Large Power Plant Units Comprising Once-Through Boilers

Solutions for the Implementation of Algorithms for Closed-Loop Control of the Frequency and Power of Large Power Plant Units Comprising Once-Through Boilers

A Multi-Functional Reactive Power Compensation Device with the Capability of Grounding Fault Regulation and Its Parameter Design Method

Aiming at the problems of low equipment utilization and the high-capacity requirements of existing arc-suppression devices, a multi-functional reactive power compensation device with the capability of grounding fault regulation (MF-RPCD) is proposed. Firstly, the topology and operation mechanism of MF-RPCD are introduced in this paper. MF-RPCD works in a reactive power compensation mode when a power grid is under normal operation to ensure the unit power factor operation of the power-grid side. When a single line-to-ground fault occurs in the power grid, MF-RPCD works in a fault-regulation mode to effectively suppress the ground-fault current. Secondly, the parameters of the active and passive parts of MF-RPCD are optimally designed to ensure the stable operation of MF-RPCD. Finally, the correctness, feasibility and effectiveness of the proposed topology and functions are verified using simulations and experiments.

Comprehensive linear and nonlinear heart rate variability normative data in children.

The autonomic nervous system (ANS) is critical in regulating involuntary bodily functions, including heart rate. Heart rate variability (HRV) reflects the complex interplay between the ANS and humoral factors, making it a valuable noninvasive tool for assessing autonomic function. While HRV has been extensively studied in adults, normative data for HRV in children, primarily based on long-term rhythm recordings, are limited. This study aimed to establish comprehensive normative data for HRV in children. In this retrospective study, we examined 24-h Holter monitors of children aged 1day to 18years, divided into six age groups, at Nemours Children's Health in Orlando, Florida, spanning the years 2013-2023. HRV analysis encompassed time-domain, frequency-domain, and nonlinear indices. Holter data for a total of 247 patients in six age groups were included. An age-related uptrend was observed in all time- and frequency-domain variables except the normalized unit of low-frequency power. Entropy analysis revealed contradictory results among different entropy techniques. Sample and approximate entropy analyses were consistent and showed less complexity and more predictability of HRV with decreasing heart rate, while Shannon entropy analysis showed the opposite. Fractal detrended fluctuation analysis exhibited significant decreases across the age groups, suggestive of diminishing self-similarity of HRV patterns. Control of heart rate and HRV is a highly complex process and requires further study for a better understanding. It seems that no single parameter can fully elucidate the entire process. A combination of time-domain, frequency-domain, and nonlinear indices may be necessary to explain HRV behavior in the growing body.

Fiber laser-based two-wavelength sensors for detecting temperature and strain on concrete structures

In this article, we discuss the scientific research we conducted to ensure information security on concrete structures using the fiber Bragg grating method. As a result, guided by the experiences of other researchers and their results in our studies, the main hazards were identified, and the influence of temperature and deformation sensors in concrete was studied. The work determines the dependence of temperature on the optical cable and its effect on concrete deformation. It also studies the change in the internal structure of the optical fiber when exposed to concrete, and in comparison, with non-concrete optical fiber. In the experimental chapter, conducted on laboratory bench, we consider and study the signal transmission structure of an optical sensor that experiences deformation upon impact with concrete and such fibers. Graphic data was obtained using the OptiSystem program. During the process of determining the optical power of the sensors, we discovered that the higher the vibration during signal transmission, the higher the power of the optical data acquisition system unit. The results presented in this paper show the promise of fiber optics in other environments, as well as new discoveries in the construction industry and the successful use of electrical laser sensors to maintain temperature and stress in a variety of concrete structures, including cooling towers in nuclear and thermal power plants.

Unit-Power Half-Normal Distribution Including Quantile Regression with Applications to Medical Data

In this paper, we present the unit-power half-normal distribution, derived from the power half-normal distribution, for data analysis in the open unit interval. The statistical properties of the unit-power half-normal model are described in detail. Simulation studies are carried out to evaluate the performance of the parameter estimators. Additionally, we implement the quantile regression for this model, which is applied to two real healthcare data sets. Our findings suggest that the unit power half-normal distribution provides a robust and flexible alternative for existing models for proportion data.

Participation of wind-storage combined system in the secondary frequency regulation control strategy of power grid

Abstract The secondary frequency modulation of the unit, that is, the automatic generation control (AGC), is the process of increasing or decreasing the power of the power generation unit by the power plant unit according to the dispatching command issued by the power grid dispatching center, and then using the frequency modulator to restore the frequency. Based on the principle of AGC, this paper establishes a frequency dynamic response model of the secondary frequency modulation of the traditional unit and the wind storage participation system including load frequency control (LFC) and traditional proportional-integral-derivative (PID) controllers, determines the frequency modulation control strategy of wind storage, and uses the distribution mode based on Area Control Error (ACE) signal to assist in the secondary frequency modulation. In order to solve the parameter optimization problem of the classical PID controller when the wind-storage combined system participates in the secondary frequency modulation under the large load disturbance, a parameter optimization model of the controller with PID was established, and the ITAE evaluation index was finally selected as the fitness function by comparing different fitness evaluation indexes. To overcome the problem that the conventional Particle Swarm Optimization (PSO) is prone to local extremum, the inertia weights and learning factors are adjusted nonlinearly to balance and optimize the global and local optimization capabilities and improve the search efficiency, and the parameters of the PID controller are optimized by the improved PSO algorithm. The simulation results show that the proposed algorithm improves the secondary frequency modulation effect under the background of a high proportion of renewable energy connected to the power grid.

Fuzzy logic-based coordinated operation strategy for an off-grid photovoltaic hydrogen production system with battery/supercapacitor hybrid energy storage

The coupling of photovoltaic power generation with water electrolyzer is advantageous for enhancing solar energy utilization and generating green hydrogen. In this work, an off-grid photovoltaic-based hydrogen production system consisting of photovoltaic, electrolyzer, battery energy storage system and supercapacitor was developed. A coordinated operation strategy is designed to manage the power of each unit in the system to avoid significant fluctuations in working power and frequent start-stop operations of the electrolyzer unit. Firstly, the coordinated operation strategy sets five operation modes for the photovoltaic-based hydrogen production system, and the fuzzy logic control algorithm is used to choose the operation mode to determine the reference power of each unit. On this basis, the state of charge feedback-based first-order low-pass filter algorithm is used to achieve the power allocation to mitigate deep charging and discharging of the supercapacitor. The proposed solution is extensively assessed through comparative simulation experiments based on three typical test days. The numerical results confirm its effectiveness and demonstrate the potential for achieving high system efficiency.

Multi-objective economic operation of smart distribution network with renewable-flexible virtual power plants considering voltage security index

This paper discusses the simultaneous management of active and reactive power of a flexible renewable energy-based virtual power plant placed in a smart distribution system, based on the economic, operational, and voltage security objectives of the distribution system operator. The formulated problem aims to specify the minimum weighted sum of energy cost, energy loss, and voltage security index, considering the optimal power flow model, voltage security formulation, and the operating model of the virtual power plant. The virtual unit includes renewable sources, like wind systems, photovoltaic, and bio-waste units. Flexibility resources include electric vehicle parking lot and price-based demand response. In the mentioned scheme, parameters of load, renewable sources, electric vehicles, and energy prices are uncertain. This paper utilizes the Unscented Transformation method for modeling uncertainties. Fuzzy decision-making is utilized to extract a compromised solution. The suggested approach innovatively considers the simultaneous management of active and reactive power of a virtual unit with electric vehicles and price-based demand response. This is performed to promote economic, operational, and network security objectives. According to numerical results, the approach with optimal power management of renewable virtual units is capable of boosting the economic, operation, and voltage security status of the network by approximately 43%, 47–62%, and 26.9%, respectively, to power flow studies. Only price-based demand response can improve the voltage security, operation, and economic states of the network by about 19.5%, 35–47%, and 44%, respectively, compared to the power flow model.

Electric vehicle supply equipment monitoring and early fault detection through autoencoders

This paper presents a novel approach to detecting anomalies in Electric Vehicle charging unit power profiles using a combination of Autoencoders with LSTM techniques. This study presents a robust methodology, combining the two Machine Learning techniques, for early fault estimation in a real-world case study. The proposed methodology offers significant advantages over existing methods by providing a more comprehensive analysis of anomalous trends. To validate the effectiveness of the proposed methodology, the authors tested it on real Electric Vehicles charging power curves provided by an Italian Distribution System Operator recorded on a historical database and compared the performances with the ones of a traditional anomaly detection technique. The results of the study, tested on Electric Vehicles Supply Equipment or charging stations, demonstrate that the proposed approach is highly effective in detecting anomalous trends in Electric Vehicles charging profiles.

Advanced nonlinear control of WEC system in AC microgrid connected to the main grid with electric vehicle integration

This research investigates an AC microgrid interconnected with the utility grid, comprising a 5.2 kW wind power system using a Permanent Magnet Synchronous Generator (PMSG), a 6.1 kW photovoltaic system (PVS), and integrated electric vehicles (EVs) with 600 V, 10Ah batteries operating in V2G and G2V modes. Bidirectional back-to-back converters, controlled via a voltage-oriented control (VOC) strategy, facilitate the interconnections. The PMSG system is controlled using vector control methodology, while the PVS employs a double-stage configuration with a perturb and observe algorithm for maximum power point tracking (MPPT). Advanced controllers based on Active Disturbance Rejection Control (ADRC) regulate generator speed and the DC link voltage of the grid-connected converters. The backstepping technique is utilized for internal loop control of PMSG currents and coupling filter currents for the grid-connected converters. A comparative study between the ADRC-Backstepping controller and the PI controller was conducted, demonstrating the superior efficacy of the ADRC-Backstepping approach. Simulation results show accurate regulation of DC link voltage at reference levels, operation with unit power factor, with a current THD below 4 %, demonstrating the effectiveness and robustness of the proposed control strategies under varying conditions.

IoT Integrated Electric Car Energy Monitoring System: Case Study of IMEI TEAM UMSIDA

The increasingly rapid development of technology accompanied by the ever-increasing consumption of fossil fuels has a negative impact on environmental sustainability and provides challenges related to innovation regarding these problems. Electric fuel vehicles are one of the relevant innovations to reduce air pollution and minimize exhaust emissions from fossil fuel vehicles on global warming. IMEI TEAM UMSIDA continues to contribute to the development of vehicles powered by electric energy by participating in energy-saving vehicle competitions such as KMHE and Shell Eco Marathon. In developing electric cars, the IMEI TEAM UMSIDA experienced problems related to obtaining information on the car's energy consumption in real time or when the car was on the track. This problem prompted researchers to create a tool that is capable of monitoring car energy consumption in real time and can be accessed remotely. The experimental method is the right method for this research, because with this method the researcher carries out many experiments to ensure that the tool system works well. The parameters produced in this research are voltage, current, power and energy values in units of time. This tool is equipped with an IoT-based communication system with an internet network as a link between the user, hardware system and software system which functions to carry out remote monitoring in real time. The test results show that this tool functions well and is able to carry out voltage measurements with an error percentage of less than 0.1% and current measurements with an error percentage of less than 0.2%.