Characteristics Of Power System Research Articles

A review of research considering polymorphic load response characteristics in power system

As more and more loads start to join the electricity market and the role of loads in power system balancing and regulation becomes more and more important, the study of the response characteristics of polymorphic loads becomes more and more important. This paper firstly reviews the aggregation methods for loads, introduces its parameter aggregation model using temperature-controlled loads as an example, and introduces the use of machine learning methods to first cluster and then aggregate. It then reviews methods for the study of load response characteristics, with an increasing number of neural networks and hybrid neural networks being introduced into the field. Finally, a review of load uncertainty is presented, introducing sources of load uncertainty and methods for coping with load uncertainty.

Generation expansion planning for Guizhou province based on the complementary characteristics of wind and solar

With the growth of wind power and solar power, power source clean transformation has become a feasible way for achieving the carbon peak target. As a hydropower resource-abundant province, Guizhou has already built Wujiang river cascade hydropower plants. This paper introduces the basic information of the Guizhou provincial power system and geometrical renewable resource distribution characteristics, especially the power source structure. Then, the wind and solar power complementary characteristics are analyzed by different copula conjunction functions. Then, the power structure transformation and generation expansion plan are provided with both carbon peak restriction and curtailment restrictions. At last, the future Guizhou provincial power system in 2029 operation simulation cases are provided, which can reduce the thermal power generation ratio to 42% and increase wind and solar power generation ratio to 8.5% and 13% approximately. The conclusion indicates that coal-fired power plant flexible reform and larger capacity energy storage installation effectively solve the larger power fluctuation and peak regulation demand with more renewable energy integration target.

Hybrid Modeling and Simulation for Shipboard Power System Considering High-Power Pulse Loads Integration

The complex dynamic characteristics of a shipboard power system (SPS) are not only related to its continuous dynamics but also influenced by discrete control behavior. Especially, during combat mission execution of high-power pulse loads (HPPLs), their operation plan as a sequence of discrete control events will cause successive abrupt changes in the continuous dynamics of SPS due to the sudden and intermittent nature of the external attacks, which requires overall comprehension of the hybrid dynamics evolution process driven by discrete events. In this paper, considering the zonal distribution structure of SPS and the influences of extreme events on the discrete dynamics of each zone, the extended hybrid models for each zone, including normal operation configuration and fault configuration, are obtained based on the hybrid automata theory. Then, the global hybrid model of SPS is developed. The mapping relationship of discrete state transition to the continuously controlled system is analyzed to reconstruct the set of differential equations model of the continuous system for the purpose of simulation. Two case studies are carried out to perform the simulation under the proposed hybrid model. It is demonstrated that this proposed method can reveal the operating characteristics of the hybrid dynamic evolution process driven by discrete events, both in normal operation and pulse loads operation. Although the precise measure of discrete states of SPS can be challenging to obtain, especially during the confrontation phase, the proposed method still provides valuable insights on evaluating the sophisticated dynamics of an SPS.

Virtual Shaft Control of DFIG-Based Wind Turbines for Power Oscillation Suppression

The flexible shaft coupled to the synchronous generator (SG) is critical for the doubly-fed induction generators (DFIG) based wind turbines to improve the ability to suppress system power oscillations. The rigid shaft coupling relationship between the DFIG and SG is analyzed first under the current virtual synchronous generator (VSG) control. To give the power system a vibrational degree of freedom, a novel virtual shaft is added to the VSG emulated by the DFIG-based wind turbine. The power system's two-degree-of-freedom (TDOF) coupled motion model with VSG is then established. The virtual shaft coupling adapted to a DFIG is designed using anti-resonance theory, and the amplitude-frequency characteristic of the TDOF power system is analyzed. With the additional stiffness of the virtual shaft, the power support functions of the VSG, including inertia and damping, are integrated by optimizing the oscillation amplitude at two fixed points in the frequency domain. Finally, on a controller hardware-in-the-loop platform, a typical power system with a high penetration of wind power generation is simulated. The test results demonstrate that by employing virtual shaft coupling, it is possible to suppress system frequency variation and rotor angle oscillation during transient events, significantly improving the reliability of the power support provided by wind turbines.

Attack estimation–based resilient control for cyber-physical power systems

This article is concerned with the resilient control problem for cyber-physical power systems. The main difference from the existing works lies in that the proposed resilient control scheme focuses on robust control in consideration of the attack reconstruction. First, power systems under false data injection attacks are modeled as cyber-physical power systems through the characteristics of power systems and attacks. Second, we design a robust adaptive attack estimation observer with a prescribed [Formula: see text] performance index to reconstruct the attack signals. Sufficient conditions for the design of the observer are formulated into matrix inequalities by choosing an appropriate adaptive law for online learning. Third, on the basis of attack estimation, a resilient control strategy by dynamic output feedback is proposed, which avoids the difficulty in designing state feedback resilient control based on the observer. Meanwhile, the attack estimation observer and output feedback resilient control are designed separately, and their performance is considered respectively, which simplifies the design process. Finally, a power system with three generators and six buses is used as an example to verify the feasibility of attack estimation and resilient control scheme.

Fast screening method for important transmission lines in electrical power system

Abstract In the electrical power system, a few transmission lines play a crucial role in cascading failures propagation. Once it participates in the cascading failures propagation process, catastrophic power blackouts will inevitably occur. In this paper, the Electrical Transmission Line-Stochastic Approach for Link Structure Analysis method (ETL-SALSA method) is proposed, which combines the Internet thinking with the physical characteristics of power system. At the same time, important transmission lines are screened to prevent cascading failures of the power system. Additionally, considering the influence of hidden failures, the expanded adjacent matrix concept is proposed. Based on the expanded adjacent matrix, fault propagation relationship and topology structure are also taken into account in the ETL-SALSA method. In the calculation process of ETL-SALSA method, Markov probability transfer matrix of the Stochastic Approach for Link Structure Analysis algorithm (SALSA algorithm) of random method is adopted, so as to achieve higher computational efficiency. Simulations carried out on the IEEE 39-bus electrical power system and the IEEE 118-bus electrical power system show that the ETL-SALSA method can achieve high-accuracy to screen important transmission lines compared with graph theory method and cascading failure simulation method. Moreover, the screening speed of the ETL-SALSA method can be enhanced for several orders of magnitude compared with cascading failure simulation method.

Calculation and analysis of plasma impedance during closing process of laser‐triggered vacuum switch

The plasma characteristics of laser‐triggered vacuum switch (LTVS) have significant effects on the output characteristics of a pulsed power system during closing process. The plasma impedance can link the microscopic properties of plasma and the macroscopic electrical parameters effectively. In this paper, the mathematic representations of plasma impedance are calculated theoretically with the equivalent circuit. External circuit inductance and resistance are calculated by means of ANSYS software and discharge time constant, respectively. Furthermore, the current and voltage experimental waveforms during closing process are analyzed by fitting piecewise linear functions in MATLAB. The plasma impedance can be calculated based on the above conditions. The calculation results show that the plasma resistance reduces with time exponentially, which is caused by an exponential increase in electron density during closing process. In addition, the plasma inductance shows an overall trend of decreasing over time, but there are fluctuations.

Impacts of integration of very large‐scale photovoltaic power plants on rotor angle and frequency stability of power system

The increase in penetration of large-scale renewable generation significantly affects power system characteristics. Thus, it is necessary to assess the steady state and dynamic performance of a power system for different installing scenarios of renewable power plants such as photovoltaic (PV) ones. The paper specifically investigates the impacts of very large-scale photovoltaic (VLS-PV) generation on the power system dynamic performance including rotor-angle and frequency stabilities. For this purpose, a detailed equivalent dynamic model for a multi-unit VLS-PV system and corresponding controllers are developed. The paper also proposes a comprehensive set of replacement scenarios comprising different PV penetration, location, and voltage control strategies as well as simulating various large disturbances. To investigate the impacts of VLS-PV generation on dynamic system performance, a study framework for frequency and rotor-angle stability involving the modal and transient analysis is presented as well. By using the VLS-PV detailed model along with other dynamic components of a power system such as synchronous generators, automatic voltage regulators (AVRs), and governors, the stabilities studying instructions are employed for the IEEE 39-bus and 118-bus test systems.

An Adaptive Voltage Control Using Local Voltage Profile Mode and Similarity Ranking

Emergency voltage control provides a real-time online response to maintain the long-term voltage stability of a power system. Searching for an optimal emergency control solution is a hard combinatorial optimization problem because of the highly dynamic and nonlinear characteristics of power systems with discrete control variables. Additionally, real-time response is required. A new mode-matching–based adaptive voltage control is proposed in this article to achieve a fast response by exploring local voltage profile modes and the technique of similarity ranking. First, some typical emergencies are studied in advance, and their control knowledge is collected for preparation. The set of local voltage profile modes and their corresponding optimal control solutions are stored as knowledge for each emergency. Second, fast online control is realized and the control solution is configured according to a similarity ranking among local voltage profile modes. Furthermore, a learning process is applied to accumulate knowledge in case of unprepared situations. Thus, improved control performances in the future are ensured. This article depends on a new concept of local voltage profile mode with which knowledge preparation, emergency identification, configuration of control, and knowledge accumulation work together to perform an effective response. Simulations of the IEEE 39-bus system verify the outcomes of this voltage control scheme.

Two-level model predictive control energy management strategy for hybrid power ships with hybrid energy storage system

Compared with the load power characteristics of ground power systems, the intermittent and random fluctuation of ship load power demand brings challenges to the energy management system of ship power systems. To achieve fuel economy and solve the problem of power fluctuation, the hybrid energy storage system (HESS) composed of the battery pack and ultra-capacitor is applied to the diesel-electric hybrid ship. A two-level model predictive control (MPC) strategy consisting of two optimization stages is proposed. The first stage aims to determine the power distribution solution of the diesel generator and battery at a large time-scale. In the second stage, the operation strategy of the ultracapacitor is determined at a small time-scale based on the power distribution solution of the first stage. The conventional MPC-based strategy and global optimization strategy based on dynamic programming (DP) are compared with the proposed strategy. The simulation results show that the proposed strategy has better fuel saving ability, and realizes the clear power frequency division between the supercapacitor and battery. In addition, the proposed strategy can also approach the performance of global optimization.

Wide-area damping power system control based on robust self-triggered model predictive control

Unavoidable random disturbances during the operation of large-scale interconnected power systems may undermine their stability. To prevent this problem, we propose a damping control method based on robust self-triggered model predictive control. First, we linearize the power system model and determine the controller installation location and feedback signal through geometric measurements. Subsequently, the model order is reduced by applying Schur method for balanced truncation. According to the assumed distribution and boundary range of random disturbance, the multi-cell robust predictive control minimax optimization problem described by the vertex is established. By deriving the upper bound of the maximum problem, the minimax problem is transformed into minimizing the upper bound problem to deal with the uncertain problem, which is transformed into linear matrix inequality for controller design. Finally, we introduce a self-triggered control strategy that avoids solving a constrained optimization problem at every time step. This strategy reduces the number of controller responses and resource requirements for sampling and communication, thereby improving computational efficiency. Selecting the two zone four-machine system as the test system, the simulation results demonstrate that the proposed control strategy can effectively eliminate the effect of random disturbances on the stable operation of power systems, improve the damping characteristics of power systems, and suppress low-frequency oscillations.

Design Scheme of a Docker Container File Isolation against Computer Virus Spreading

With the spread of computers and Internet of Things, the destructive power of viruses gradually becomes stronger, which threaten the daily life of people. In order to effectively restrain the virus spreading and reduce economic losses, humans need to hold the law and control of the virus distribution. Docker has obtained significant attention as a lightweight virtualization container technology. Compared to traditional virtualization technologies, docker possesses the advantages of fast deployment, low resource consumption, and high migration capability. Given that the differences between various virtualization technologies and combining the characteristics in electric power systems, this paper designs a scheme of the file isolation system based on docker containers. The isolation scheme could reduce the highly dependence on the underlying operating system in the current application deployment of electric power systems and facilitate the security access to the file system between containers.

Hybrid Data-Driven Modeling for an AC/DC Power System Considering Renewable Energy Uncertainty

The development of grid-connected renewable energy sources and the widespread use of power electronic devices have exacerbated the uncertain, time-varying, and non-linear characteristics of power systems, making accurate and real-time model design challenging. Modeling for unmodeled dynamics and random characteristics has inherent disadvantages in power system simulation. Conventional converter valve modeling ignores the high-frequency switching condition. This study aims to provide an effective modeling strategy that can accurately characterize the unmodeled dynamics and uncertainty of AC/DC hybrid interconnection systems with significant grid-connected renewable energy capacity. The model-data hybrid-driven modeling concept based on digital twin (DT) enhances the technique’s effectiveness. It models the proportional-integral control link of a voltage source converter (VSC). The time convolution neural network (TCN) algorithm can describe accurately the high-frequency switching state of the switching device and the operation state of renewable energy units that changes dynamically with weather conditions and other variables. The simulation experiments on a real-world power grid demonstrate the proposed modeling method’s efficiency and the hybrid-driven model’s performance.

Transient characteristic analysis for large-scale power system with MMC-MTDC

Modular multi-level converter (MMC)-based multi-terminal dc (MTDC) grid (abbreviated as MMC-MTDC) is promising in the integration and transmission of bulk renewable energy. This paper analyzes the transient characteristic of large-scale power systems with the MMC-MTDC. First, the transient stability-electromagnetic transient (TS-EMT) model of the system is established. The corresponding simulation flowchart is also presented, where the MMC-MTDC grid dynamics are calculated by EMT simulation and the ac grid is simulated by the TS program. Second, based on the mathematical model of the MMC-MTDC grid, the transient characteristics during various faults are analyzed. Third, it analyzes the influences of the controller parameters on the transient characteristics. Test results on the North-China power system with Zhangbei MTDC verifies the correctness of the transient characteristic analyses.

Assessing Potential Scenarios for Achieving New and Renewable Energy Targets in Java-Bali Power System, Indonesia

Geographic circumstances, government policies, and power system characteristics face many countries struggling to achieve their new and renewable energy (NRE). In addition, one characteristic of renewable energy (RE) which cannot be moved is a severe problem for archipelagic countries like Indonesia in achieving their NRE targets. Therefore, this research creates a long-term open-source generation expansion planning (GEP) model that considers renewable energy integration between islands, government policies, and power system characteristics of Indonesia. The model proposes a high voltage direct current (HVDC) line to facilitate abundant energy transfer between islands. The research also included multiple scenario analyses based on the potential strategies that could realistically be applied. Based on the long-term GEP model results, possible alternative routes to achieving NRE targets are mapped and assessed by considering power system characteristics and national energy policies. Specifically, the Java-Bali system of Indonesia is employed as a case study to demonstrate the performance of the proposed long-term GEP model. The optimum planning to achieve the targets produces the generation cost of 7.05 cents USD/kWh and the CO2 emission reduction of 2,297 million tons of CO2.

Numerical simulation and emission analysis of ammonia/oxygen premixed combustion process in micro-combustor with baffle

Ammonia has attracted extensive attention, and its popularization and application in various power equipment has become one of the current hotspots. However, in the combustion-based micro power system, the combustion and emission characteristics of ammonia at micro scale are still unclear. In this paper, the combustion and emission characteristics of ammonia/oxygen in micro burner with baffle were studied by numerical simulation. By changing the length, width, position of the baffle and inlet velocity, the effects of various factors on temperature field, NO emission and radiation efficiency were obtained. The results show that compared with micro conventional burner, the addition of baffle reduces the channel temperature, radiation efficiency and NO emission. As the baffle length increases, the channel maximum temperature and NO emission decrease first and then increase. The mass fraction of NO in the exhaust gas increases as the baffle width increases under constant flow rate. As the baffle moves downstream, NO emission presents a parabolic distribution. When the baffle with length of 5 mm and width of 0.5 mm is placed 3 mm away from the inlet, the radiation and emission performance are the best. The mass fraction of NO decreases by 24.71% compared with micro planar combustor.

Integration of Renewable Based Distributed Generation for Distribution Network Expansion Planning

Electrical energy is critical to a country’s socioeconomic progress. Distribution system expansion planning addresses the services that must be installed for the distribution networks to meet the expected load need, while also meeting different operational and technical limitations. The incorporation of distributed generation sources (DGs) alters the operating characteristics of modern power systems, resulting in major economic and technical benefits, such as simplified distribution network expansion planning, lower power losses, and improved voltage profile. Thus, in this study, an analytical method is used to design the expansion planning of the Addis North distribution network considering the integration of optimal sizes of distributed generations for the projected demand growths. To evaluate the capability of the existing Addis North distribution network and its capability to supply reliable power considering future expansion, the load demand forecast for the years 2020–2030 is done using the least square method. The performance evaluation of the existing and the upgraded network considering the existing and forecasted load demand for the years 2030 is done using ETAP software. Accordingly, the results revealed that the existing networks cannot meet the existing load demand of the town, with major problems of increased power loss and a reduced voltage profile. To mitigate this problem, the Addis North feeder-1 distribution network is upgraded and for each study case, the balanced and positive sequence load flow analysis was executed and the maximum total real and reactive power losses were found at bus 29. The result shows that the upgraded network of bus 29 was the optimal location of DG and its size was 9.93 MW. After the optimal size of DG was placed at this bus, the real and reactive power losses of the upgraded networks were 0.2939 MW and 0.219 MVAr, respectively. At bus 29 the maximum power losses reduction and voltage profile improvements were found. The active and reactive power losses were minimized by 21.285% and 19.633% respectively and the voltage profiles were improved by 8.78%. Thus, in the predicted year 2030, DG power sources could cover 61.12% of the feeder-1 power requirements.

Allocation of Energy Storage Capacity Based on Optimal Power Flow

Under the continuous development of new power system, the double high characteristics become more and more obvious in the characteristics of power system. How to make good use of electrochemical energy storage and participate in the power market has become an urgent problem to be solved. In view of this, based on the day ahead market forecast,this paper establishes a model for the participation of electrochemical energy storage in the operation of the electricity market and sets up three different scenarios with the goal of maximizing gross profit. Finally, it is concluded that the operation strategy of electrochemical energy storage proposed in this paper can effectively improve the benefits of electrochemical energy storage.

Correlation based neuro-fuzzy Wiener type wind power forecasting model by using special separate signals

The wind power system is characterized by complex structures, numerous effect elements, and complicated physical relationships, which bring great difficulties to establish the wind power forecasting model and result in the unsatisfactory prediction accuracy of wind power. In this paper, a correlation based neuro-fuzzy Wiener type wind power forecasting model is proposed by using special separate signals to decouple dynamic linear and static nonlinear characteristics of wind power systems for high-accuracy wind power forecasting. This method introduces an autoregressive exogenous model and fuzzy neural network to explore the underlying distribution characteristics of wind power systems by correlation analysis of the linear and nonlinear information contained in time-series data of the wind power system. In addition, in order to eliminate outliers in the original data set, an abnormal data cleaning approach combining quartile and two-stage clustering algorithm is employed to reduce the computation time and improve the model accuracy. Moreover, the convergence of the Wiener model is proved by the Lyapunov function. Simulation results verify the high accuracy and generalization ability of the proposed model both in the gale and breeze seasons.

Analysis of Ultra-Low Frequency Oscillation Characteristics of Wind Power System Considering Dead Zone of Governor

Analysis of Ultra-Low Frequency Oscillation Characteristics of Wind Power System Considering Dead Zone of Governor