State Key Laboratory of Power Grid Safety and Energy Conservation,China Electric Power Research Institute,Beijing,China

The power system is experiencing a higher penetration of renewable energy generations(REGs).The short circuit ratio(SCR)and the grid impedance ratio(GIR)are two indices to quantify the system strength of the power system with REGs.In this paper,the critical short circuit ratio(CSCR)is defined as the corresponding SCR when the system voltage is in the critical stable state.Through static voltage stability analysis,the mathematical expression of the CSCR considering the impact of GIR is derived.The maximum value of CSCR is adopted as the critical value to distinguish the weak power system.Based on the static equivalent circuit analysis,it is proved that the CSCR is still effective to evaluate critical system strength considering the interactive impact among REGs.Finally,we find that the GIR can be neglected and the SCR can be used individually to evaluate the system strength when SCR>2 or GIR>5.The correctness and rationality of the CSCR and its critical value are validated on ADPSS.

A Discussion on the Flexible Regulation Capacity Requirements of China’s Power System

A high proportion of variable renewable energy(VRE)is one of the most significant characteristics of China’s future power system under the"dual carbon"target.However,wind and solar power units are more uncontrollable and less supportive for power system stability than traditional thermal power units,due to their susceptibility to the weather and the grid connection of power electronics.Therefore,as the capacity and generation of VRE grow rapidly and even dominate the power structure,the power system’s ability to deal with disturbances will continue to decrease.

Multi-source heterogeneous data access management framework and key technologies for electric power Internet of Things

The power Internet of Things(IoT)is a significant trend in technology and a requirement for national strategic development.With the deepening digital transformation of the power grid,China’s power system has initially built a power IoT architecture comprising a perception,network,and platform application layer.However,owing to the structural complexity of the power system,the construction of the power IoT continues to face problems such as complex access management of massive heterogeneous equipment,diverse IoT protocol access methods,high concurrency of network communications,and weak data security protection.To address these issues,this study optimizes the existing architecture of the power IoT and designs an integrated management framework for the access of multi-source heterogeneous data in the power IoT,comprising cloud,pipe,edge,and terminal parts.It further reviews and analyzes the key technologies involved in the power IoT,such as the unified management of the physical model,high concurrent access,multi-protocol access,multi-source heterogeneous data storage management,and data security control,to provide a more flexible,efficient,secure,and easy-to-use solution for multi-source heterogeneous data access in the power IoT.

Research on high energy efficiency and low bit-width floating-point type data for abnormal object detection of transmission lines

Achieving a balance between accuracy and efficiency in target detection applications is an important research topic.To detect abnormal targets on power transmission lines at the power edge,this paper proposes an effective method for reducing the data bit width of the network for floating-point quantization.By performing exponent prealignment and mantissa shifting operations,this method avoids the frequent alignment operations of standard floating-point data,thereby further reducing the exponent and mantissa bit width input into the training process.This enables training low-data-bit width models with low hardware-resource consumption while maintaining accuracy.Experimental tests were conducted on a dataset of real-world images of abnormal targets on transmission lines.The results indicate that while maintaining accuracy at a basic level,the proposed method can significantly reduce the data bit width compared with single-precision data.This suggests that the proposed method has a marked ability to enhance the real-time detection of abnormal targets in transmission circuits.Furthermore,a qualitative analysis indicated that the proposed quantization method is particularly suitable for hardware architectures that integrate storage and computation and exhibit good transferability.

A Two-Layer Active Power Optimization and Coordinated Control for Regional Power Grid Partitioning to Promote Distributed Renewable Energy Consumption

With the large-scale development and utilization of renewable energy,industrial flexible loads,as a kind of loadside resource with strong regulation ability,provide new opportunities for the research on renewable energy consumption problem in power systems.This paper proposes a two-layer active power optimization model based on industrial flexible loads for power grid partitioning,aiming at improving the line over-limit problem caused by renewable energy consumption in power grids with high proportion of renewable energy,and achieving the safe,stable and economical operation of power grids.Firstly,according to the evaluation index of renewable energy consumption characteristics of line active power,the power grid is divided into several partitions,and the interzone tie lines are taken as the optimization objects.Then,on the basis of partitioning,a two-layer active power optimization model considering the power constraints of industrial flexible loads is established.The upper-layer model optimizes the planned power of the inter-zone tie lines under the constraint of the minimum peak-valley difference within a day;the lower-layer model optimizes the regional source-load dispatching plan of each resource in each partition under the constraint of theminimumoperation cost of the partition,so as to reduce the line overlimit phenomenon caused by renewable energy consumption and save the electricity cost of industrial flexible loads.Finally,through simulation experiments,it is verified that the proposed model can effectively mobilize industrial flexible loads to participate in power grid operation and improve the economic stability of power grid.

Coordinated Voltage Control of Distribution Network ConsideringMultiple Types of Electric Vehicles

The couple between the power network and the transportation network(TN)is deepening gradually with the increasing penetration rate of electric vehicles(EV),which also poses a great challenge to the traditional voltage control scheme.In this paper,we propose a coordinated voltage control strategy for the active distribution networks considering multiple types of EV.In the first stage,the action of on-load tap changer and capacitor banks,etc.,are determined by optimal power flow calculation,and the node electricity price is also determined based on dynamic time-of-use tariff mechanism.In the second stage,multiple operating scenarios of multiple types of EVs such as cabs,private cars and buses are considered,and the scheduling results of each EV are solved by building an optimization model based on constraints such as queuing theory,Floyd-Warshall algorithm and traffic flow information.In the third stage,the output power of photovoltaic and energy storage systems is fine-tuned in the normal control mode.The charging power of EVs is also regulated in the emergency control mode to reduce the voltage deviation,and the amount of regulation is calculated based on the fair voltage control mode of EVs.Finally,we test the modified IEEE 33-bus distribution system coupled with the 24-bus Beijing TN.The simulation results show that the proposed scheme can mitigate voltage violations well.

Enhancing Autonomy Capability in Regional Power Grids:A Strategic Planning Approach with Multiple Autonomous Evaluation Indexes

After the integration of large-scale DistributedGeneration(DG)into the distribution network,the randomness and volatility of its output result in a reduction of spatiotemporal alignment between power generation and demand in the distribution network,exacerbating the phenomenon of wind and solar power wastage.As a novel power system model,the fundamental concept of Regional Autonomous Power Grids(RAPGs)is to achieve localized management and energy autonomy,thereby facilitating the effective consumption of DGs.Therefore,this paper proposes a distributed resource planning strategy that enhances the autonomy capabilities of regional power grids by considering multiple evaluation indexes for autonomy.First,a regional Energy Storage(ES)configuration strategy is proposed.This strategy can select a suitable reference value for the upper limit of ES configuration based on the regional load andDGoutput to maximize the elimination of source load deviations in the region as the upper limit constraint of ES capacity.Then,a control strategy for regional ES is proposed,the charging and discharging reference line of ES is set,and multiple autonomy and economic indexes are used as objective functions to select different proportions of ES to control the distributed resources of the regional power grid and establish evaluation indexes of the internal regional generation and load power ratio,the proportion of power supply matching hours,new energy consumption rate and tie line power imbalance outside the region to evaluate changes in the regional autonomy capabilities.The final simulation results showthat in the real regional grid example,the planning method in the planning year in the region of the overall power supply matching hour ratio and new energy consumption rate increased by 3.9%and 4.8%on average,and the power imbalance of the tie line decreased by 7.8%on average.The proposed planning approach enables the maximization of regional autonomy while effectively smoothing the fluctuation of power exchange between the regional grid and the higher-level grid.This presents a rational and effective planning solution for the regional grid,facilitating the coordinated development between the region and the distribution network.

A Fuzzy Probability-based Markov Chain Model for Electric Power Demand Forecasting of Beijing, China

In this study, a fuzzy probability-based Markov chain model is developed for forecasting regional long-term electric power demand. The model can deal with the uncertainties in electric power system and reflect the vague and ambiguous during the process of power load forecasting through allowing uncertainties expressed as fuzzy parameters and discrete intervals. The developed model is applied to predict the electric power demand of Beijing from 2011 to 2019. Different satisfaction degrees of fuzzy parameters are considered as different levels of detail of the statistic data. The results indicate that the model can reflect the high uncertainty of long term power demand, which could support the programming and management of power system. The fuzzy probability Markov chain model is helpful for regional electricity power system managers in not only predicting a long term power load under uncertainty but also providing a basis for making multi-scenarios power generation/development plans.

Design scheme for fast charging station for electric vehicles with distributed photovoltaic power generation

The demand for fast charging is increasing owing to the rapid expansion of the market for electric vehicles. In addition, the power generation technology for distributed photovoltaic has matured. This paper presents a design scheme for a fast charging station for electric vehicles equipped with distributed photovoltaic power generation system taking the area with certain conditions in Beijing as an example construction site. The technical indexes and equipment lectotype covering the general framework and subsystems of the charging station are determined by analyzing the charging service demand of fast charging stations. In this study, the layout of the station is developed and the operation benefits of the station is analyzed. The design scheme realizes the design objective of "rationalization, modularization and intelligentization" of the fast charging station and can be used as reference for the construction of a fast charging network in urban area.

Development in Researches on Reradiation Interference from UHV Power Lines

Reradiation interference(RRI) from ultra high voltage(UHV) power lines has become a hotspot for researches in electromagnetic(EM) interference between UHV power grids and adjacent radio stations.The mechanism of RRI,numerical simulations,methods of protecting distance calculation,and resonance characteristics of RRI are reviewed in this paper using results of works reported by IEEE and Chinese publications.We conclude in this review that RRI at short and medium wavelengths can be simulated using method of moment(MoM) and two commonly used models,the wire model and the surface model,which have different applicable conditions.We indicate that the accurate simulation of RRI at higher frequencies using uniform geometrical theory of diffraction is still beyond our capability because it requires studies of the relative simulation methods.We also suggest that further researches of the mechanism of RRI and the prediction of resonance frequencies above 1.7 MHz are necessary for dealing with the interference between the existing power lines and radio stations because resonance frequencies proposed by IEEE are less than 1.7 MHz.

Research and application of artificial intelligence service platform for the power field

Conventional analysis methods cannot fully meet the business needs of power grids.At present,several artificial intelligence (AI) projects in a single business field are competing with each other,and the interfaces between the systems lack unified specifications.Therefore,it is imperative to establish a comprehensive service platform.In this paper,an AI platform framework for power fields is proposed;it adopts the deep learning technology to support natural language processing and computer vision services.On one hand,it can provide an algorithm,a model,and service support for power-enterprise applications,and on the other hand,it can provide a large number of heterogeneous data processing,algorithm libraries,intelligent services,model managements,typical application scenarios,and other services for different levels of business personnel.The establishment of the platform framework could break data barrier,improve portability of technology,avoid the investment waste caused by repeated constructions,and lay the foundation for the construction of "platform + application + service" ecological chain.

Research on the Sub-synchronous Oscillation in Wind Power Connected to Series Compensated Power System and its Influencing Factors

When wind farms,which is based on double fed induction generator(DFIG),are connected to the series compensation power system,the phenomenon of sub-synchronous oscillation(SSO)may occur.In order to study the sub-synchronous oscillation in wind power connected to series compensated power system and its influencing factors,we used RT-LAB to establish a simulation model concerning wind power connected to series-compensation power system.This model take a wind power connected to series compensation power system in north China as prototype.All influence factors of wind power SSO are simulated and analyzed by using time domain analysis method.The simulation results show that the effects of wind speed,series compensation degree and proportional control coefficient of rotor side converter(RSC)are most obvious.

Research on key technologies of deduction of multinational power trading in the context of Global Energy Interconnection

When transnationalized electricity trade is conducted in the context of Global Energy Interconnection(GEI),the transaction settlement usually has a long cycle and high cost and is influenced by the volatility of the exchange rate.It is thus necessary to overcome the problems associated with the transaction settlement,change in the trading model data,and trading strategy in the transnational transaction deduction.To overcome the problem of trade settlement,this paper proposes the use of a digital currency(energy currency)for the cross-border electricity trading settlement based on the special drawing rights of the International Monetary Fund,which is controlled by the Global Energy Interconnection Development and Cooperation Organization(GEIDCO),to enable the proposed currency to become a stable digital currency.The traders can use the energy coins as a unit of currency for quotes,combined with the data pertaining to the changes in the energy information obtained from the GEI framework and data regarding the optimally extrapolated reference trading indicators.To realize the implementation of the multi-trader concurrent transaction deduction using a microservice architecture,this paper proposes a method of computing the microservice and synchronous interaction among the traders,based on the database table data,because the large amount of computation is required to be accomplished asynchronously with a single process.The key technology behind these cross-national electricity trading simulations can not only enable the GEI transnational traders to performed daily real-time trading,but it also demonstrates the advantages of the rapid settlement of the energy currency and the realization of a stable payment in the global energy interconnection cross-border electricity trading.

Automated deep learning system for power line inspection image analysis and processing: architecture and design issues

The continuous growth in the scale of unmanned aerial vehicle (UAV) applications in transmission line inspection has resulted in a corresponding increase in the demand for UAV inspection image processing. Owing to its excellent performance in computer vision, deep learning has been applied to UAV inspection image processing tasks such as power line identification and insulator defect detection. Despite their excellent performance, electric power UAV inspection image processing models based on deep learning face several problems such as a small application scope, the need for constant retraining and optimization, and high R&D monetary and time costs due to the black-box and scene data-driven characteristics of deep learning. In this study, an automated deep learning system for electric power UAV inspection image analysis and processing is proposed as a solution to the aforementioned problems. This system design is based on the three critical design principles of generalizability, extensibility, and automation. Pre-trained models, fine-tuning (downstream task adaptation), and automated machine learning, which are closely related to these design principles, are reviewed. In addition, an automated deep learning system architecture for electric power UAV inspection image analysis and processing is presented. A prototype system was constructed and experiments were conducted on the two electric power UAV inspection image analysis and processing tasks of insulator self-detonation and bird nest recognition. The models constructed using the prototype system achieved 91.36% and 86.13% mAP for insulator self-detonation and bird nest recognition, respectively. This demonstrates that the system design concept is reasonable and the system architecture feasible .

Research on Total Electric Field for DC Lines Converted from Double-Circuit AC Lines

With rapid growth of power demand, transmission capacity is also in urgent need of upgrading. In some cases, converting existing AC transmission lines to DC lines can Improve the transmission capacity and reduce the construction investment. In this paper, the upstream finite element method was expanded to calculate the total electric field of same tower multi-circuit DC lines converted from double-circuit AC lines, and the validity of the algorithm was confirmed by experiments. Taking a DC line converted from a typical same tower 500 kV double-circuit AC transmission line as an example, the surface electric field and the ground total electric field in different pole conductor arrangement schemes were calculated and analyzed, and the critical height of pole conductors for DC lines in residential and non-residential area were determined. Then, the corridor width of DC and AC lines at critical height in residential and non-residential areas before and after AC-DC line transformation were compared. The results indicate that for DC lines converted from common 500 kV double-circuit AC lines, the ground total electric field can meet the requirements of corresponding standard with appropriate pole conductor arrangement schemes.

Research on the Model of Long Term Generation Planning in Power Market Reform

With the deepening of China’s power market, bilateral transactions will continue to grow in large scale. The release of bilateral transactions locked more regulatory resources of the power grid, will directly affect the operation mode of the unit and the implementation of planned electricity. In the paper, considering the large-scale bilateral trade effect on the peak regulation of power grid, energy saving and emission reduction, power system security and other factors, and then putting forward the method of long term generation planning and annual planning model to adapt to the safe operation of power grid in China. In the model, the target is minimizing the monthly load rate deviation and the annual electric quantity deviation rate, the latter includes the capacity factor. In addition, the constraints include the monthly quantity of electricity, adjustable utilization rate deviation, load rate, reserve and key sections, etc. Through an example to verify the correctness of the model, the planning and power transaction results can satisfy the peak regulation of load, energy saving and emission reduction and safety operation of the power grid requirements.

Research on Security Assessment Index System for Operating Reserve in Large Interconnected Power Grid

Optimization and placement of spinning reserve is an important issue in power system planning and operation. Systematic way for security assessment of operating reserve needs to study. A security assessment index system for operating reserve in large interconnected power grids is presented in this paper. Firstly, classification and determination methods of operating reserve at home and abroad are investigated, and operating reserve is divided into transient state operating reserve and quasi-steady state operating reserve from the view of security assessment. Secondly, assessment indexes and optimization methods for transient state operating reserve are studied. Thirdly, optimization model, deterministic and probabilistic optimization methods for quasi-steady state operating reserve are explored. Finally, some principles for determination of operating reserve are suggested, and a security assessment index system is put forward. The proposed index system, considering both transient and quasi-steady state, both deterministic and probabilistic methods, provides a systematic way to assessment and arrangement of operating reserve.

Research on Multi-Scale Modeling of Grid-Connected Distributed Photovoltaic Power Generation

The complexity of distribution network model mainly depends on the model scale of grid-connected distributed photovoltaic (PV) power generation. Therefore, the simulation performance of multi-scale PV model is the key factor of the simulation accuracy in the specific operating scenarios of distribution network. In this paper, a multi-scale model of grid connected PV distributed generation system is proposed based on the mathematical model of grid-connected distributed PV power generation. It is analyzed that differences of simulation performance, such as adaptability of simulation step size, accuracy of output and the effect on voltage profile of distribution network, between PV models with different scales in IEEE 33 node example. Simulation results indicate that the multi-scale model is effective in improving the accuracy and efficiency of simulation under different operating conditions of distribution network.

Research on the Effects of the Most Used Market Power Mitigation Mechanisms Considering Different Market Environments

The market power mitigation method of the supply-side has become one of the key points affecting the stability of the electricity spot market.Different mitigation mechanisms are used in the current mature electricity markets of the world.However,the same market power mitigation mechanism shows different effects in different market environments.Every market operator in the world needs the most efficient way to mitigate market power.Considering that there is no relevant literature discussing the market power effects of different mitigation methods in detail,the mitigation effects need to be discussed and further researched.So,we analyze the effects of the most utilized market power mitigation mechanisms while considering different market environments.Firstly,we establish a Nash-Stackelberg interactive game model to simulate the competitive strategies of power suppliers.Secondly,the different market power mitigation approaches are modeled.Then,a multi-agent system(MAS)genetic interior-point algorithm is proposed to solve the problem of suppliers.Finally,through the simulation analysis,the market power mitigation effects of different mechanisms while considering three operation states of the system in two market structures are all analyzed.

A Survey on Research of Power System Transient Stability Based on Wide-Area Measurement Information

Although the power system is designed to withstand disturbances such as faults,loss of major transmission lines,loss of generators or large changes in loads,system instability may occur sometimes.In order to maintain the system operating on a high level of stability,special attentions are paid.In recently years,the presence of wide area measurement system based on phasor measurement units provides new methods for the research on system instability which involves rotor angle,frequency or voltage instability.