Wide-frequency measurement devices can monitor wide-frequency oscillations in the power grid in real time. However， during practical engineering deployment， there is a lack of targeted guidance methods， making it difficult to comprehensively monitor oscillations and their propagation， and challenging to provide reference for oscillation source location. This paper discusses the flaws in current oscillation monitoring point distribution methods， analyzes the differences between optimal phasor measurement unit （PMU） configuration methods and oscillation monitoring point distribution methods， and proposes an improved oscillation monitoring point distribution method based on observable power grid topology. The overall principles， approach， and specific process of the proposed method are discussed， and its feasibility is verified with typical topology case studies. Finally， engineering implementation suggestions and ideas are provided. This method can serve as a reference for monitoring wide-frequency oscillations in modern power systems， displaying propagation paths， and tracing the source of oscillations.

This paper proposes a new reliability assessment method based on chip-level monitoring data. Traditional reliability assessment methods primarily rely on historical data statistics and generic failure rates of electronic components, facing challenges such as difficulty in obtaining reliability data, long testing periods, high costs, and insufficient accuracy due to assumptions. This study starts with chip-level monitoring and establishes a chip operation data acquisition system for secondary equipment in substations on a wide-area scale. By utilizing real-time operational data and combining it with failure data from equipment type tests, a failure threshold calculation method and scoring evaluation system are developed. This enables precise reliability assessment of secondary equipment in substations, providing a scientific basis for improving equipment reliability and optimizing operating conditions.

As the use of high-penetration renewable energy and power electronic devices becomes more widespread, the issue of wide-frequency oscillations has become increasingly prominent. Although industry-developed wide-frequency measurement devices enable real-time, on-site oscillation monitoring, the current oscillation alarm thresholds are based solely on a single parameter, oscillation power, presenting challenges for accurately triggering alarms across the diverse range of oscillation types. This paper proposes a method for setting wide-frequency oscillation alarm thresholds that is tailored to multiple intervals, oscillation types, and characteristic parameters. The method allows for the differential setting of corresponding oscillation alarm thresholds based on the various types of wide-frequency oscillations and includes verification of these thresholds. This approach not only facilitates precise monitoring and identification of wide-frequency oscillations but also offers guidance and reference for on-site oscillation monitoring and alarming, thereby enhancing the overall technical level of power grid operation monitoring and ensuring grid operational safety..

The Wide-Area Measurement System (WAMS) demonstrates significant advantages in power grid monitoring through its high data acquisition density, excellent synchronization performance, and inclusion of phase-angle information. These features effectively support power grid security and stable operation. However, limitations in WAMS data quality have hindered its engineering applications. Current research focuses on data value anomalies and lacks effective methods for identifying time-synchronization errors. This paper proposes a time-stamp anomaly identification method for WAMS data based on disturbance occurrence time detection. By analyzing post-disturbance measurements from Phasor Measurement Units (PMUs), including frequency change rates, active power variations, and frequency deviations, the method identifies disturbance onset moments. Temporal inconsistencies in disturbance occurrence times across wide-area PMU measurements enable the detection of time-stamp anomalies at specific plants and substations. Validation through actual grid disturbance cases confirms the method's effectiveness. This approach provides a valuable reference for addressing time-synchronization anomalies in WAMS data, enhancing the reliability of WAMS for power system monitoring applications

Due to the decrease of inertia caused by the grid-connected large-scale new energy in the new power system, the demand to evaluate the inertia of power system has become urgent, and the on-line monitoring of inertia based on PMU measurement data is considered as an effective method at present. Three typical online monitoring methods are discussed respectively which are ordinary calculation method, integral calculation method and differential calculation method. The theoretical calculation of these three typical methods is presented. Simulation analysis is carried out by IEEE39 nodes with load increase and cutting off of generator respectively, and the characteristics of each inertia calculation method are compared and analyzed, and a conclusion that the error of ordinary calculation method is smallest and most stable among these three methods, which is recommended. It can provide reference for online calculation and analysis of inertia in the future.

Accurate short-term forecasting of photovoltaic power generation is crucial for power dispatching, capacity analysis, and unit commitment. Existing data-driven prediction algorithms have a certain impact on calculation speed and prediction accuracy, but they fail to consider the internal mechanism of photovoltaic power generation and have the risk of generalization. First, the fuzzy C-means clustering (FCM) algorithm method was used for preprocessing of the PV sample set. The sample points with variability were categorized into different sample sets with less variability. Second, the photovoltaic mechanism model is added to the first layer learner of the Stacking framework to form a one-layer learner of the Long Short-Term Memory (LSTM) neural network, Light Gradient Boosting model (LGBM), and mechanism-driven model. The mechanistic model limits PV generation to a reasonable range as a prediction constraint for the data-driven model. The proposed model can seize the useful inherent information from the mechanism model and utilize the ability of data analysis to extract the inexplicit linear relationship. Finally, the PV power and weather observation data collected from photovoltaic power stations located in a certain place in Germany are used to verify the effectiveness of the proposed method.

Wide-frequency oscillations including low-frequency oscillation, sub/super-synchronous oscillation, and high-frequency oscillation have been encountered with the construction of new type power system, which have led to multiple accidents and seriously affected the operational safety of the power grid. Its online monitoring and location is one of the important issues faced by new power systems. Unlike the low-frequency oscillation which is dominated by the traditional synchronous generator, sub/super-synchronous and high-frequency oscillation belong to the category of electromagnetic oscillations, so the existing method is not applicable. A framework for the monitoring and location system of wide-frequency oscillation in the power grid combined with wide-frequency measurement is proposed and application functions are designed in this paper. Based on the characteristics of the oscillations, an oscillation monitoring method combining “FFT+Prony” and master-slave cooperation is proposed to adaptively monitor the oscillation. Further, combined with grid topology, the location method based on dissipating energy flow or active power flow direction is proposed. The effectiveness of the proposed system and method is verified by WECC 240-bus test system and actual grid system.

The interaction between DPMSGs and AC/DC power grids is complex and changeable, which can easily cause broadband oscillations in the system. Impedance analysis has been widely used in power system broadband oscillation analysis in recent years due to its clear physical meaning and other characteristics. This paper first conducts impedance modeling on DPMSGs and verifies the accuracy. Then the stability analysis and calculation formula of impedance sensitivity are given. Finally, the impedance sensitivity of the control parameters of the grid-side converter of the direct-drive wind turbine is discussed.

In order to address the significant impact of cloud cover on photovoltaic (PV) power due to its obscuring effect, and the challenge of accurately mapping the relationship between cloud information and PV power. Traditional PV power prediction methods often overlook the influence of cloud structure and meteorological elements on PV power. A proposed solution is a short-term PV power prediction method that considers satellite cloud imagery. Firstly, standardization and de-biasing processes are applied to visible light cloud images obtained from satellites, eliminating the intraday variability of these images. Subsequently, a gated recurrent neural network is employed to capture the impact features of cloud cover. Finally, by integrating cloud cover features with other influencing factors, a mapping relationship with PV power is established for prediction. Results indicate that the proposed model effectively addresses the intraday variability of cloud images, achieves precise localization of cloud feature regions, and demonstrates good predictive performance. This research provides valuable insights for cloud-based PV power prediction.

The increasing number of wind power plants and the complexity of their integration have caused various changes of power system and generated lots of harmonic and inter-harmonics. Currently, the research focuses on the study of simulation and theory analysis, lacking of real-time monitoring of the inter- and harmonic components. The wide-frequency measurement technology and related device is presented to monitor the harmonics and inter-harmonic characteristics of grid connected with wind power plants, the characteristics of fundamental, harmonic, and inter-harmonics of grid connected with wind power plant is analyzed. The relationship between typical harmonics/inter-harmonic and wind power output is described, the typical harmonic/inter-harmonic distribution rules and characteristics are compared with each other, which can enhance the understanding of the new characteristics of the grid connected with large scale wind power plants. It can provide a reference for the safety and stability of power grid in the future.

To address the problem of data duplication and isolated data caused by the binding of substation-specific data to equipment and the independent construction of various systems, this article focuses on the interaction data flow between substation equipment. Based on the differences in real-time data, data structure, and processing performance indicators, the data transmission path is optimized. The existing multi-end duplicate data collection is divided into partitioned transmission. By using cross-zone real-time bus synchronization technology, the data of primary and secondary equipment as well as auxiliary equipment are shared comprehensively at the station control level, supporting the integration and optimization of substation secondary system functions and equipment. This achieves the integration of primary and auxiliary equipment for comprehensive monitoring.

In order to meet the demand of high-precision harmonic sampling in electronics power grid, and further improve the performance of secondary equipment such as substation measurement and control, PMU and broadband measurement, the application scenarios and performance requirements of high-performance hardware platform are analyzed, and the technical status of domestic chips in mass production is investigated. The hardware platform scheme of heterogeneous SoC chips is adopted, and the dual-system software architecture based on Linux and RTOS system is adopted, We have designed a large-capacity real-time data parallel processing and layered drive technology scheme, fully developed the computing potential of heterogeneous multi-core chips, improved the performance of hardware platform based on domestic chips, and completed the development and testing of the hardware platform of broadband measurement device prototype. Finally, the feasibility of the hardware platform technology scheme based on heterogeneous SoC chips is verified through the comparison of various performance tests.

The substation is the core facility of the power system. The interaction and coordination of different equipment in the protection and monitoring system(PMS) directly affects the working efficiency and stable operation of the system. However, the current protection and monitoring system of substation(SPMS) generally lacks evaluation method for collaboration. To the above problems, this paper proposes an evaluation method for collaboration in S-PMS based on the G1 method. Firstly, according to the requirements of the coordination for PMS, the corresponding indicators are proposed to form the index system for evaluating the coordination. Then, combined with G1 method, a comprehensive collaboration evaluation model is constructed. Finally, the coordination of two different structures of substations is evaluated and analyzed, and the feasibility of the evaluation method is verified.

The large-scale integration of new energy sources has brought a series of new types of oscillations to the power grid, and the oscillations gradually develop to high frequencies. The existing WAMS-based oscillation monitoring technology can only monitor sub-synchronous oscillation below 50Hz, and cannot cope with wide-frequency oscillations above 50Hz. The existing monitoring methods can only passively respond to the oscillation after the oscillation occurs, and lack active early warning and intervention methods. Based on wide-frequency measurement technology, this paper proposes an engineering method for wide-frequency oscillation risk assessment and early warning of oscillation. Firstly, it discusses the functions and characteristics of wide-frequency measurement technology and devices, and proposes an overall scheme for oscillation risk assessment and early warning based on wide-frequency measurement data. Then, the method of oscillation risk assessment and early warning is discussed in detail from two aspects, which are the statistical analysis of historical data and real-time monitoring data, it can provide guidance and reference for the early warning and analysis of power grid wide-frequency oscillation in the future, and promote oscillation monitoring from passive response to active prevention and intervention.

A large-scale integration of renewable energy of grid has introduced a large number of power electronic equipment, which introduced a lot of inter-harmonics and harmonic signals into the grid, and has shown the trend of power electronics. The existing measurement technology only focuses on 50Hz power frequency signal, and cannot meet the real-time measurement requirements of inter-harmonic and harmonic. Wide-frequency measurement device can realize the unified monitoring of the fundamental wave, inter-harmonic and harmonic of the power grid, but a large amount of data cannot be transmitted to the master station in real time, and it needs to be processed and analyzed locally. Firstly, this article analyzes the type of wide-frequency measurement data, the data filtering mechanism. Secondly, it discusses the preprocessing and analysis of the wide-frequency measurement data and oscillation information on substation level, focusing on the substation-level steady-state real-time data preprocessing analysis and alarm event analysis. Thirdly, this paper discusses the realization of the preprocessing analysis report and alarm event analysis report, and then discusses the transmission and engineering application of the analysis reports. It can provide guidance and reference for the wide-frequency monitoring and engineering application of the power electronics dominated power system in future.

The interaction between a large number of high proportion renewable energy and high proportion power electronic devices connected to AC power grid has caused a new type of subsynchronous oscillation (SSO), which puts forward severe requirements for the stable operation and control of power system. However, previous studies on the mechanism and suppression methods of SSO have ignored the propagation and distribution path of SSO. Therefore, this paper first proposes a new time-domain simulation method and verifies its accuracy in a single- machine infinite bus system. Secondly, the time domain simulation method is applied to the multi-machine system to monitor the key nodes to obtain the propagation and distribution path of SSO voltage in the power grid. And the effects of frequency and electrical distance on SSO are studied.

Micro compressed air energy storage (M-CAES) has the characteristics of pollution-free, high comprehensive utilization of energy, and the ability of combined cooling, heating, and electrical power, which can better meet the energy application in many areas. Considering that the business models restrict the development of M-CAES, business models analysis for M-CAES considering the comprehensive cost in its life-cycle is studied. Firstly, this paper analyzes possible investment models of M-CAES projects with multiple market participants, and then the business models of the M-CAES system are designed. Secondly, a scheme of life-cycle cost/benefit assessment is proposed for M-CAES investment, including the construction cost and the operation cost of the M-CAES. Finally, the economic benefits of different business models are analyzed by the 1MWh M-CAES. The results show that they can provide theoretical reference and engineering instruction for the research and engineering application of M-CAES.

As a new type of mechanical energy storage, compressed air energy storage (CAES) has attracted wide attention in recent years. This paper studies the optimal sizing problem of CAES in power distribution network (PDN). CAES plays a role in shaving the peak and filling the valley at demand side and thus reduces the operation cost of PDN to purchase electricity from the main grid. A multi-parametric linear programming (MP-LP) model is formulated where the power and energy capacities of CAES are regarded as parameters; the parameterized optimal value function (OVF) provides a graphical tool to describe the impact on operation cost of CAES configuration, which helps determine the planning strategy in a visual manner. The visualized results reveal not only the optimal solution, but also some useful information, like the sensitivity of operation cost to parameters. Case studies conducted on the IEEE 33-bus distribution system verifies the effectiveness of the proposed method.

Due to the expansion of China’s power grid scale, low-frequency oscillations and sub-synchronous oscillations frequently affect the safe and stable operation of the power grid. It is of great practical significance to research and analyze these two oscillations. Wide frequency measurement provides technical means for simultaneous monitoring of low frequency oscillations and sub-synchronous oscillations. Based on wide frequency signals, an appropriate algorithm can be used to analyze the oscillation mode. The Prony algorithm is commonly used to identify the oscillation mode parameters, but the length of the time window and order have a greater impact on the identification results. In this paper, the time window length selection method and the order determination method without threshold value based on SVD are proposed to determine the two values adaptively. Then the comparison of the algorithms before and after improved are given. Finally, applying low-frequency oscillation measured data and four-machine two-area system and IEEE first standard model simulation data to verify the applicability of the improved algorithm to low-frequency oscillation and sub-synchronous oscillation identification.

Dynamic load model is of great value in analysis and simulation of power grid, while the composition of load has an important influence on the characteristic and accuracy of load model. There is mass of load equipment in power grid, so it is usually necessary to classify the load equipment according to their different characteristic first, then establish a suitable load model separately, and synthesize them into a composite model according to their proportion. Only the power value of load can be measured when power grid operates in a normal and steady state, and their dynamic response characteristics are unknown. Therefore, it is difficult to obtain sufficient information for load classification. However, frequency characteristics of load are distinguished and easy to obtain, so it is useful for load classification indirectly. Firstly, several elector-magnetism models of typical load are established, and their harmonic curves and frequency characteristic are simulated and analyzed separately. Then, cluster analysis is carried out to obtain the typical characteristics and the membership degree which can represent the contents of load overall. Finally, a classification method combined with Neural Network is adopted, and the computation speed is also improved.