Supplements to Invertor Current Mode Controller of Distributed Generation Sources for Stability Task

In the distributed load frequency control (DLFC) scheme, the compromised areas by attackers may endanger the stable and reliable operation of the entire power system. A credibility‐based secure DLFC strategy is in this work proposed to sustain the stable operation of the power system under false data injection attacks. In this secure DLFC method, the gradient‐variation‐based credibility metrics are defined to detect potential attacked measurements. Then, the communication isolation decisions are made based on the adaptive thresholds. To compensate the impact of the communication isolation of misbehaving areas, predictions of future measurements by using the average gradient variation of stored healthy data are feeded back to the area controller. Simulation results of a four‐area power system show the proposed secure DLFC can identify and cut off the communication of the misbehaving areas and still maintain the stability of the power system.

Under the background of the construction of “three types and two networks”, the introduction of a large number of heterogeneous intelligent terminals, ubiquitous open networks, interactive real-time control services and wide area interconnected power systems have transmitted the network security risks to all aspects of the power system. The security defense capability of power system is not only the superposition of security defense equipment, but also the excellent network security team. The continuous improvement of the level of network security is inseparable from the accumulation of network security attack and defense technology and practical experience, as well as practical tools and equipment with the characteristics of the power industry. In order to meet the increasingly severe security protection challenges, actively implement the security protection requirements of the power information system, ensure the safe and stable operation of the power system, build a network shooting range suited to the attributes of the power industry, and continuously improve the ability of network security protection, consolidate the foundation of digital transformation to ensure the safe and stable operation of power system and reliable power supply.The safe and stable operation of the information system needs to carry out comprehensive and in-depth vulnerability troubleshooting. In view of the lack of power business loophole mining and security event verification shooting range environment, this paper studies the power security shooting range construction technology.

The growing share of renewable energy integration poses significant challenges to the secure and stable operation of power systems. Effectively assessing the maximum allowable capacity for renewable energy integration has become a critical issue in renewable energy planning and system operation. Based on the network structure and parameters of actual power systems, this paper evaluates the maximum integration capacity for renewable energy generation under full-power operation, considering both static voltage stability and broadband dynamic stability constraints. The corresponding short-circuit ratio (SCR) requirements for grid connection are also analyzed. The proposed approach provides a more effective method for assessing integration capacity and SCR in renewable energy planning and operational studies. Finally, the effectiveness and accuracy of the proposed evaluation method are verified using a practical case study of a renewable energy plant grid-connected system.

Multi-objective optimal load dispatch of microgrid with stochastic access of electric vehicles

Stable operation of an electric power system is currently among the power industry’s most pressing issues. The problem is connected with a change in the power system dynamic characteristics caused by the development of distributed generation facilities, renewable energy sources, and installations containing power electronics. These circumstances generate the need for further improvement and adaptation of automatic excitation control systems of synchronous generators for securing the power system stability. The article addresses matters concerned with application of an integral law for excitation control of synchronous generators. The subject of the study is a synchronous generator equipped with an automatic excitation controller, which is connected to a power system via a step-up transformer and transmits power through a two-circuit transmission line. The power system receiving end is represented by an infinite bus with constant voltage, frequency, and phase. The electric power system stability conditions were studied using the D-partitioning method and the Mikhailov stability criterion. The study results were tested using a mathematical model in the MATLAB software system with applying the Simulink library package. An example of using an algorithm for selecting the integral controller tuning parameter for the mathematical model test data is given. The variation of the Mikhailov root locus curve at different values of the integration time constant is analyzed. Based on the study results, conclusions have been drawn about the possibility of ensuring small-signal aperiodic and oscillatory stability of a synchronous generator equipped with an integral excitation controller and about the permissibility of applying the integral control law in the power system.

The high frequency oscillation (HFO) of renewable energy integrated into MMC brings serious challenges to the stable operation of power system. This article proposes the mathematical impedance model of MMC with considering control system time delay, sequence component separation, control system. Besides time delay, the main factors of HFO such as SCS, virtual filter of voltage and current, inner-loop controller are derivate in this article. It is proved that SCS may lead to the fluctuation of phase character of MMC high frequency impedance and lead to low damping character of MMC system. Virtual filter of voltage and current can enhance the damping ratio of MMC system. Lower proportional gain of inner-loop control lead to a higher damping character of MMC system. The solutions of HFO are validated in Zhangbei project. The 1550Hz HFO in the project is suppressed by the optimization of control system.

In a modern power system, stable operation of the electrical system is a major concern. For the stable operation of power system, it is desirable to access the effect of unforeseen events and identification of more sensitive nodes. The most outstanding job of distribution engineers is to simulate the power system for corrective action. Probabilistic power flow (PPF) is a tool that can effectively access the performance of power system network over most of its working conditions taking into account the unforeseen events. In this paper, a new PPF model is developed to evaluate power system network taking into account the uncertainty with input random variables, such as wind energy, loads, generation outage, and branch outage. This model is based upon the two well-known methods, Monte Carlo simulation (MCS) and point estimation method (PEM). For the sake of, computational efficiency and results accuracy Box-Muller sampling equation was used with MCS and $2m+1$ concentration scheme was used with PEM. The proposed model was investigated by using modified IEEE 14-bus standard test system.

The damage of arc to gas insulation protection will affect the safe and stable operation of power system seriously in the field of high voltage insulation. Therefore, it is a great theoretical value and practical significance to study the mechanism of gas discharge and find out the law of gas discharge under different conditions for ensuring the safe and stable operation of power system. In order to study the variation law of arc channel complexity under different voltage levels, this paper adopts the discharging experiment of needle-plate electrode, adds different high voltage to the needle-plate electrode under other conditions unchanged, carries out many experiments, and collects five groups of discharging channel plans of needle-plate gap under different voltage. The are discharge channel image in the experiment is restored to the three-dimensional image from the space angle, and the fractal dimension of arc discharge channel under different voltage pressure is calculated by box dimension method of fractal dimension. The results show that the complexity of discharge channel decreases with the increase of voltage level, that is, the lower the voltage level and the larger the fractal dimension.

As power big data plays an increasingly important role in the operation, maintenance, and management of power systems, complex and covert false data attacks pose a serious threat to the safe and stable operation of the power system. This article first explores the characteristics of new power systems, and the challenges posed by false data attacks. The application of big data technology in power production optimization, energy consumption analysis, and user service improvement is then investigated. The article classifies typical attacks against the four stages of power big data systems in detail and analyzes the characteristics of the attack types. It comprehensively summarizes the attack detection technologies used in the four key stages of power big data, including state estimation, machine learning, and data-driven attack detection methods in the data collection stage; clock synchronization monitoring and defense strategies in the data transmission stage; data processing and analysis, data integrity verification and protection measures of blockchain technology in the third stage; and traffic supervision, statistics and elastic computing measures in the control and response stage. Finally, the limitations of attack detection mechanisms are proposed and discussed from three dimensions: research problems, existing solutions, and future research directions. It aims to provide useful references and inspiration for researchers in power big data security to promote technological progress in the safe and stable operation of power systems.

The deep adjustment of power grid structure puts forward new requirements for power system emergency control technology. Aiming at the problem that traditional transient stability control methods only consider power angle stability constraints, resulting in low control accuracy and unable to guarantee the transient voltage stability of power grid, a hybrid model based on deep learning is proposed for power system emergency control. Firstly, the power system emergency control margin model of random forest is established to accurately judge the stability of the system and avoid improper decision-making due to the failure of the model. Secondly, the long short-term memory network is used for real-time power curve prediction to provide accurate implementation scheme of machine and load shedding, so as to realize the stable operation of power system. Finally, simulation analysis is carried out in IEEE 16 machine 68 bus interconnected system. The results show that our method has better system stability judgment accuracy than the comparison method, and the emergency control method can effectively ensure the stable operation of the system after failure.

Guest Editorial: Situational awareness of integrated energy systems

In order to alleviate the serious pollution problems caused by traditional thermal power generation, it is an inevitable trend to incorporate clean and renewable energy sources such as wind power into power system dispatching. However, the unpredictability and volatility of wind power posed enormous challenges for the stable operation of power systems. Therefore, it is a popular research topic to improve the traditional scheduling strategy and maintain the stable economic operation of the power system. This paper studied the joint optimization scheduling problem of power system with wind power, hydropower and thermal power, and discussed the effect of hydropower on system scheduling with different adjustment capabilities.

With the goal of “carbon peaking and carbon neutral”, the power system will be connected to a large number of renewable energy sources with random and volatile characteristics, which will bring great challenges to the safe and stable operation of the power system. The current power system control schemes are often based on conventional simulation models, and the generation of control strategies based on inaccurate simulation data and models will lead to differences between the control effects of control strategies and the real state of the actual power system, among which component parameter errors are considered to be the main factor leading to inconsistencies between dynamic simulation results and measured data. Therefore, it is necessary to continuously calibrate the power system model parameters so that the simulation trajectory gradually approximates the measured trajectory and improves the credibility of the simulation system. In this paper, we first study the hybrid dynamic simulation method, which locks the errors into the system to be studied by incorporating the measured data into the simulation system without introducing the errors caused by external system modeling. Then a current-controlled three-phase voltage source inverter is proposed to equate the external system, and the hybrid dynamic simulation is performed by outputting a given amount of active and reactive power to the power system, thus narrowing the error traceability region. Finally, the accuracy and reliability of the proposed current-controlled three-phase voltage source inverter injection method are verified in the Guangzhou Conghua system.

To address the impact of ice storms on the stable operation of power system, this paper proposes a full-cycle resilience enhancement strategy for power system involving the whole time of ice storms. First, failure models of power system components under ice storms are established, and the classic failure scenario is derived using the Shannon information entropy method, with system resilience evaluated via proposed indexes. Second, a full-cycle (pre-disaster preventive, in-disaster response, post-disaster restorative) resilience enhancement model is constructed to minimize the total cost of power supply and load shedding. Finally, the operation simulation of the resilience enhancement strategy scenario is carried out to verify its effectiveness. Comprehensive case studies using IEEE RTS 79-bus system validate that the proposed full-cycle resilience enhancement strategy can effectively reduce the economic losses caused by ice storms to power systems.

The electric power system is one of the indispensable infrastructures in modern society, and its stable operation is crucial for guaranteeing economic development and social security. By calculating the correlation coefficient and drawing the correlation heat map, we find that there is a correlation between the voltage at each location and the occurrence of electrical faults, and at the same time, there is also a certain correlation between various types of electrical faults and the voltage at each location. These results indicate that there are complex and close interrelationships between different locations and between different types in the power system. In order to better identify and classify different types of electrical faults, we used the random forest model for prediction. The model is used to classify whether an electrical fault occurs or not and to determine its category. The prediction results show that the Random Forest achieved 99.63% in classifying whether an electrical fault occurred or not, and 91.26% in classifying the category of electrical faults. This shows that the Random Forest algorithm model is able to detect electrical faults well, as well as judge the category of electrical faults. In summary, this paper provides insight into the operation of the power system by studying the correlation between the voltage at various locations in the power system and the different types of electrical faults and using the random forest model to make predictions. These findings are of great significance in ensuring the stable operation of power systems.