Hasil untuk "Production of electric energy or power. Powerplants. Central stations"

V. Коvalov

Abstract. The mechanical power of traction electric motors of mainline electric locomotives with a supply voltage of 25 kV is determined by the efficiency when powered from a multi-arm single-phase semi-controlled thyristor rectifier, the arms of which are connected to separate sections of a traction single-phase transformer. Purpose: to obtain an analytical expression for calculating the coefficient of reduction of mechanical power of traction electric motors under the condition of maintaining the nominal thermal regime of the motors. The task is to determine the quantitative influence of armature current harmonics on the mechanical power of traction motors. Methodology. The determination methodology is based on the law of conservation of energy, the method of harmonic analysis of the pulsating current of the armature winding, methods from the theory of electric machines and the method of computer modeling to obtain experimental dependences of the pulsation coefficient of the armature current on the control angle of thyristors, the inductance of the armature circuit and the load current. Results and their scientific novelty. A computer model of a thyristor electric drive has been developed, on the basis of which experimental graphical dependences of the armature current ripple coefficient on the thyristor control angle, armature circuit inductance and load current have been obtained. For the first time, an analytical expression for the coefficient of reduction of the mechanical power of a DC traction motor when powered by single-phase semi-controlled thyristor rectifiers has been obtained, taking into account the current ripple coefficient, based on the calculation of relative electrical losses from the harmonic components of the current, which are equal to the square of the current ripple coefficient. An analytical expression for calculating the armature current ripple coefficient, taking into account the thyristor control angle, armature winding inductance and load current, has been further developed. Practical significance. The analytical expression for determining the coefficient of reduction of the mechanical power of a DC motor when powered by a single-phase half-controlled thyristor rectifier allows: 1) to calculate the load capacity of the traction motor by mechanical power on the shaft, taking into account the permissible heating by the effective value of the current with harmonic components; 2) to calculate the inductance of the smoothing reactor to increase the mechanical power of the motor by reducing the current ripple coefficient.

Xin Zou, Zhiping Hu

Zhibin Li, Xiaoyan Diao, Qianwen Xiang et al.

As an emerging physical energy storage technology, the magnetic suspension flywheel battery boasts prominent advantages such as high working efficiency, long service life, and short charging time. However, improving the energy conversion efficiency of magnetic suspension flywheel battery systems and reducing their overall energy loss have long been critical bottleneck technologies that urgently need to be addressed for practical applications. To promote China’s green and low-carbon energy transition and accelerate the achievement of the “double carbon” goals, this paper summarizes two core components of flywheel battery systems—magnetic bearings and flywheel motors—along with two key technologies: topological structure and control strategy, based on numerous cutting-edge studies. Subsequently, focusing on further reducing the energy consumption of flywheel energy storage systems, technical prospects are extended from aspects including system material selection and intelligent integrated control, aiming to provide research directions for the low-energy-consumption operation of flywheel battery systems.

Riccardo Ramaschi, Mario Paolone, Sonia Leva

Large-scale Electric Vehicle (EV) Charging Station (CS) may be too large to be dispatched in real-time via a centralized approach. While a decentralized approach may be a viable solution, the lack of incentives could impair the alignment of EVs' individual objectives with the controller's optimum. In this work, we integrate a decentralized algorithm into a hierarchical three-layer Energy Management System (EMS), where it operates as the real-time control layer and incorporates an incentive design mechanism. A centralized approach is proposed for the dispatch plan definition and for the intra-day refinement, while a decentralized game-theoretic approach is proposed for the real time control. We employ a Stackelberg Game-based Alternating Direction Method of Multipliers (SG-ADMM) to simultaneously design an incentive mechanism while managing the EV control in a distributed manner, while framing the leadership-followership relation between the EVCS and the EVs as a non-cooperative game where the leader has commitment power. Part I of this two-part paper deals with the SG-ADMM approach description, literature review and integration in the abovementioned hierarchical EMS, focusing on the modifications needed for the proposed application.

B Hariprasad Associate Professor, G Sreenivasan, P Bharath Kumar et al.

Shahriar Rahman Fahim, Rachad Atat, Cihat Kececi et al.

The integration of information and communication technologies into modern power systems has contributed to enhanced efficiency, controllability, and voltage regulation. Concurrently, these technologies expose power systems to cyberattacks, which could lead to voltage instability and significant damage. Traditional false data injection attacks (FDIAs) detectors are inadequate in addressing cyberattacks on voltage regulation since a) they overlook such attacks within power grids and b) primarily rely on static thresholds and simple anomaly detection techniques, which cannot capture the complex interplay between voltage stability, cyberattacks, and defensive actions. To address the aforementioned challenges, this paper develops an FDIA detection approach that considers data falsification attacks on voltage regulation and enhances the voltage stability index. A graph autoencoder-based detector that is able to identify cyberattacks targeting voltage regulation is proposed. A bi-level optimization approach is put forward to concurrently optimize the objectives of both attackers and defenders in the context of voltage regulation. The proposed detector underwent rigorous training and testing across different kinds of attacks, demonstrating enhanced generalization performance in all situations. Simulations were performed on the Iberian power system topology, featuring 486 buses. The proposed model achieves 98.11% average detection rate, which represents a significant enhancement of 10-25% compared to the cutting-edge detectors. This provides strong evidence for the effectiveness of proposed strategy in tackling cyberattacks on voltage regulation.

Wei Jiang, Xiaohua Li, Na Zhang et al.

With the integration of large-scale renewable energy sources into modern power systems, coal-fired power plants are frequently forced into deep peak-shaving operations to manage fluctuating power outputs. Under these operational conditions, coal consumption exhibits significant non-stationary characteristics, posing considerable challenges to intelligent dispatch optimization and coordinated pollutant control systems. Effective forecasting of coal consumption is thus critical. While conventional long short-term memory (LSTM) and Transformer models are capable of capturing both short-term and long-term temporal dependencies, their performance deteriorates significantly when handling highly volatile coal consumption data due to the absence of uncertainty modeling mechanisms.To address these challenges, this paper proposes a novel coal consumption forecasting method, termed DDPM-Informer, that integrates an Informer architecture with a Denoising Diffusion Probabilistic Model (DDPM). First, the Informer network effectively captures long-term dependencies using a sparse attention mechanism, enhancing computational efficiency and preliminary forecasting accuracy. Second, we innovatively introduce a DDPM-based diffusion mechanism into the latent layers of the Informer model to implicitly capture and model uncertainties embedded in the data. Unlike traditional explicit uncertainty modeling methods, the proposed DDPM mechanism requires no manual specification of modeling functions or parameters, as it implicitly models uncertainties through a latent diffusion-denoising process.Experimental validation using real operational data from a 2 × 1000 MW coal-fired power plant in Wuhan, China, demonstrates the superior accuracy of the proposed DDPM-Informer method compared with existing state-of-the-art models. The proposed method provides a new technical pathway for intelligent dispatch, combustion efficiency optimization, and emission control in coal-fired power plants under deep peak-shaving scenarios.

Yanqing Huang, Meizhou Deng, Nan Duan et al.

The recent discovery of natural gas within the fifth member of the Xujiahe Formation (T3x5) in the Dongfeng area within the Sichuan Basin highlights the significant exploration potential of this member. However, the unconvincing previous understanding of the sedimentary microfacies, combined with a total lack of studies on the sand body architecture and reservoir distribution, hampers the further exploration of this member. Using core data, log curves, and seismic data, along with sedimentary microfacies analysis, this study investigated the interfaces between the sand bodies of various scales in the Dongfeng area. Furthermore, this study explored the morphological characteristics, types, and stacking patterns of these sand bodies and determined the distributions of sand bodies and reservoirs in the area. The results indicate that the first sand group of the T3x5 member (T3x51) exhibits delta-front deposits, including subaqueous distributary channels, sheet sands, and interdistributary bays. Seven levels of sand body interfaces are identified in the T3x51 sand group. Among them, the interfaces of the first and second levels were identified only in cores, those of the third and fourth levels were recognizable from cores combined with log curves, while those of the fifth, sixth, and seventh levels were distinguishable using seismic data. Three superimposed subaqueous distributary channel complexes are found in the Dongfeng area. Among them, complex 1 in the northwest exhibits the strongest water body energy, while complex 2 in the south displays the weakest. Complex 2 was formed earlier than complexes 1 and 3. Also, complex 1 is further subdivided into three vertically stacked subaqueous distributary channels. The subdivision of sedimentary microfacies in the T3x5 member reveals nine lithofacies types. Among them, stacked pancake-shaped, carbonaceous debris-bearing, massive, and cross-bedded medium-grained sandstones are considered favorable lithofacies. These four lithofacies types exhibit high porosity, as well as low natural gamma-ray (GR) values, low-to-medium deep investigate double lateral resistivity (RD), and high interval transit time (AC) on the log curves. Additionally, the reservoir distribution in the Dongfeng area was delineated based on the characterization of the favorable lithofacies. This study serves as a guide for future exploration and evaluation of the T3x5 member in the Dongfeng area while also augmenting the methodologies for describing tight sandstone reservoirs.

Shuaibin Shi, Yongli Liu, Qing Wang et al.

Abstract The access of electric vehicle charging stations (EVCS) brings challenges to the stable operation of the distribution network.At present, there is a lack of indicator to quantify the economic losses caused by the decrease in power quality of the distribution network due to the access of EVCSs.In the paper, the travel trajectories of electric vehicle users are constructed through trip chain and state transition matrices,thereby obtaining the spatiotemporal distribution of charging loads.In addition, the voltage deviation and line loss caused by charging loads are unified into economic indicator to quantify.The simulations are conducted in a road network coupled to the IEEE 33-node distribution network.The result shows that the charging load of electric vehicle charging stations have a significant impact on the power quality of the distribution network.At the same time, optimizing the location of charging stations and guiding electric vehicle users’ charging behaviorcan effectively improve the power quality and economic efficiency of distribution networks.

Biling Wang, Gaojian Fan, Xinming Zhang et al.

The pure pursuit (PP) method has been widely employed in automated guided vehicles (AGVs) to address path tracking challenges. However, the traditional pure pursuit method exhibits certain limitations in tracking performance. For instance, selecting a look-ahead point that is too close can lead to oscillations during tracking, while selecting one that is too far away can result in slow tracking and corner-cutting issues. To address these challenges, this paper proposes a multistep prediction pure pursuit method. First, the look-ahead distance calculation equation is adjusted by incorporating path curvature, allowing it to adaptively adjust according to road conditions. Next, to avoid oscillations caused by constant changes in the look-ahead distance, this paper adopts the prediction concept of model predictive control (MPC) to make multistep predictions for the pure pursuit method. The final input is derived from a linear weighted combination of the multistep prediction results. Simulation analyses and experiments demonstrate that the multistep predictive pure pursuit method significantly enhances the tracking performance of the traditional pure pursuit method.

Feng Ren, Xin Wen, Hui Tang

Flow past one or multiple bluff bodies is almost ubiquitous in nature and industrial applications, and its rich underlying physics has made it one of the most typical problems in fluid mechanics and related disciplines. The search for ways to control such problems has attracted extensive attention from both the scientific and engineering fields, as this could potentially bring about benefits such as reduced drag, mitigated noise, suppressed vibration, and enhanced heat transfer. Flow control can be generally categorized into passive and active approaches, depending on whether there is an external energy input to the flow system. Active control is further divided into open-loop approaches and closed-loop approaches, depending on whether the controller depends on feedback signals extracted from the flow system. Unlike in many other applications of passive flow control and open-loop active flow control, theoretically advantageous closed-loop controls are quite rare in this area, due to the complicated features of flow systems. In this article, we review the recent progress in and future perspectives of flow past a single or multiple bluff bodies using model-free closed-loop control so as to outline the state-of-the-art research, determine the physical rationale, and point to some future research directions in this field.

DONG Jianning, AN Jizhen, CHEN Heng et al.

ObjectivesDirect air-cooled unit is a common equipment of thermal power generation in some water-deficient areas. The operation is subject to many restrictions because it uses air as its cooling medium. Heat transfer performance of air-cooled island was studied to solve these problems that direct air-cooled units are greatly affected by the environment and have high coal consumption.MethodsBased on history-data of a supercritical 2×600 MW unit in Hebei Province, the performance of its air-cooled island was calculated with MATLAB software, this study considered the acquired data as the training set and the test set,which were used to predict future performance in virtue of long short-term memory (LSTM) neural network machine learning algorithm. Under the condition that the model parameters were not changed, the feature importance ranking was determined by removing all features, based on which the best feature selection strategy was determined to further optimize the model. Considering the great impact from the weather, a prediction procedure, taking into account weather factors, was written to improve the accuracy of predicting air-cooled island performance, by combining the original data set with historical weather data. Accordingly prediction results were subjected to visualization and analyzation.ResultsThe prediction accuracy of the adopted prediction model is significantly higher than that of the traditional autoregressive integrated moving average model (ARIMA), and the goodness of fit of the direct air-cooled unit heat transfer performance prediction within the next hour is above 0.90.ConclusionsThe data characteristics and algorithms used in the model can provide data support for the stable operation of the direct air-cooled unit and provide a technical basis for the construction of intelligent power plants.

Dominik Scholtes, Ralf-Kilian Zäh, Benedikt Faupel et al.

Shape memory alloys (SMAs) are becoming a more important factor in actuation technology. Due to their unique features, they have the potential to save weight and installation space as well as reduce energy consumption. The system integration of the generally small-diameter NiTi wires is an important cornerstone for the emerging technology. Crimping, a common method for the mechanical and electrical connection of SMA wires, has several drawbacks when it comes to miniaturization and high-force outputs. For high-force applications, for example, multiple SMA wires in parallel are needed to keep actuation frequencies high while scaling up the actuation force. To meet these challenges, the proposed study deals with the development of a resistance-welding process for manufacturing NiTi wire bundles. The wires are welded to a sheet metal substrate, resulting in promising functional properties and high joint strengths. The welding process benefits from low costs, easy-to-control parameters and good automation potential. A method for evaluating the resistance-welding process parameters is presented. With these parameters in place, a manufacturing process for bundled wire actuators is discussed and implemented. The welded joints are examined by peel tests, microscopy and fatigue experiments. The performance of the manufactured bundle actuators is demonstrated by comparison to a single wire with the same accumulated cross-sectional area.

DONG Jun, TANG Jianfang, ZANG Chuncheng et al.

The ball joint is a key component of a parabolic trough solar collector. To address the problems of operation sticking and heat conduction oil leakage in ball joints, a performance test system was developed. The system can perform accelerated life tests of ball joints in rotational, angular, or rotational-angular motion, and at temperature up to 393 ℃ and pressure up to 4.1 MPa. Using thermal conductivity oil as heat transfer fluid, performance tests of the ball joints were conducted under working conditions of 393 ℃ and 2.3 MPa, as well as under varying temperature and pressure conditions. The torque characteristics and sealing performance of the ball joint over a simulated 12-year lifespan were analyzed. Furthermore, the stability and reliability of the test system were verified through the test process, and the control and measurement accuracy of key technical parameters met the operational requirements. This test system provides technical support for the performance assessment of ball joints.

Alban Puech, Tristan Rigaut, William Templier et al.

This paper introduces an Electric Vehicle Charging Station (EVCS) model that incorporates real-world constraints, such as slot power limitations, contract threshold overruns penalties, or early disconnections of electric vehicles (EVs). We propose a formulation of the problem of EVCS control under uncertainty, and implement two Multi-Stage Stochastic Programming approaches that leverage user-provided information, namely, Model Predictive Control and Two-Stage Stochastic Programming. The model addresses uncertainties in charging session start and end times, as well as in energy demand. A user's behavior model based on a sojourn-time-dependent stochastic process enhances cost reduction while maintaining customer satisfaction. The benefits of the two proposed methods are showcased against two baselines over a 22-day simulation using a real-world dataset. The two-stage approach demonstrates robustness against early disconnections by considering a wider range of uncertainty scenarios for optimization. The algorithm prioritizing user satisfaction over electricity cost achieves a 20% and 36% improvement in two user satisfaction metrics compared to an industry-standard baseline. Additionally, the algorithm striking the best balance between cost and user satisfaction exhibits a mere 3% relative cost increase compared to the theoretically optimal baseline - for which the nonanticipativity constraint is relaxed - while attaining 94% and 84% of the user satisfaction performance in the two used satisfaction metrics.

Matthew Deakin, Xu Deng

A low-cost reconfiguration stage connected at the output of balanced three-phase, multi-terminal ac/dc/ac converters can increase the feasible set of power injections substantially, increasing converter utilization and therefore achieving a lower system cost. However, the approach has yet to be explored for phase unbalance mitigation in power distribution networks, an important application for future energy systems. This study addresses this by considering power converter reconfiguration's potential for increasing the feasible set of power transfers of four-wire power converters. Reconfigurable topologies are compared against both conventional four-wire designs and an idealised, fully reconfigurable converter. Results show that conventional converters need up to 75.3% greater capacity to yield a capability chart of equivalent size to an idealised reconfigurable converter. The number and capacity of legs impact the capability chart's size, as do constraints on dc-side power injections. The proposed approach shows significant promise for maximizing the utilization of power electronics used to mitigate impacts of phase unbalance.

Dekang Zhao, Zhenghao Li, Guorui Feng et al.

The accurate calculation of the height of fractured water-conducting zone (FWCZ) is of great significance for mine optimization design, water disaster prevention, and safety production of the coal mines. In this article, a height-prediction model of FWCZ based on extreme learning machine (ELM) is proposed. To address the issues of low prediction accuracy and challenging parameter optimization, we optimized the ELM model using the gray-wolf optimization algorithm (GOA), whale optimization algorithm (WOA), and salp optimization algorithm (SOA). These optimization algorithms mitigate the issues of slow convergence, poor stability, and local optimality associated with traditional neural networks. The mining depth, mining height, overburden strata structure, working face length, and coal seam dip angle are selected as the main controlling factors for the height of FWCZ. A total of 42 fields-measured samples are collected and divided into 2 subsets for training and validating with a ratio of 36/6. The prediction capability of GOA-ELM, WOA-ELM, and SOA-ELM models are evaluated and compared, and the results show that the calculation results of the three models are optimized compared with the ELM model. The prediction capability of GOA and WOA are similar, while the prediction results of SOA-ELM are better than the other two models, and the relative errors of the test sets are all less than 10%. Therefore, the SOA-ELM model is finally applied to predict the height of FWCZ formed after the mining of No.15 coal seam in Xinjian Coal Mine. Finally, we verified the prediction results using measured data from the borehole television detection instrument, which showed good consistency. This provides further evidence of the effectiveness of the swarm intelligence optimization algorithm in predicting the height of FWCZ.

Dajun Du, Minggao Zhu, Xue Li et al.

Potential malicious cyber-attacks to power systems which are connected to a wide range of stakeholders from the top to tail will impose significant societal risks and challenges. The timely detection and defense are of crucial importance for safe and reliable operation of cyber-physical power systems (CPPSs). This paper presents a comprehensive review of some of the latest attack detection and defense strategies. Firstly, the vulnerabilities brought by some new information and communication technologies (ICTs) are analyzed, and their impacts on the security of CPPSs are discussed. Various malicious cyber-attacks on cyber and physical layers are then analyzed within CPPSs framework, and their features and negative impacts are discussed. Secondly, two current mainstream attack detection methods including state estimation based and machine learning based methods are analyzed, and their benefits and drawbacks are discussed. Moreover, two current mainstream attack defense methods including active defense and passive defense methods are comprehensively discussed. Finally, the trends and challenges in attack detection and defense strategies in CPPSs are provided.

Guangtang Pan, Qingxuan Jia, Gang Chen et al.

This paper presents a novel approach for analyzing and optimizing motion coupling in the coordinated operation tasks of flexible space multi-arm robots (FMSRs). The method integrates motion coupling between multiple arms and system stiffness to improve the motion and force accuracy of FMSRs by optimizing the configuration. First, a comprehensive model of an FMSR is established using the hypothetical modal method. Then, the motion coupling relationship among multiple arms is analyzed, and a motion coupling degree evaluation index is developed. Furthermore, the constraint relationship of coordinated operation is analyzed, and an equivalent stiffness model for the coordinated operation of the FMSR is formulated along with a stiffness evaluation index. Based on these analyses, the motion trajectory of the FMSR is optimized by comprehensively considering both the motion coupling degree and the equivalent stiffness factors. Finally, numerical simulation experiments are conducted to validate the proposed method, and the results show that the accuracy of the FMSR can be improved by 40% using this approach.