Research on Transmission Line Tower Tilting and Foundation State Monitoring Technology Based onMulti-Sensor Cooperative Detection and Correction

The transmission line tower will be affected by bad weather and artificial subsidence caused by the foundation and other factors in the power transmission.The tower’s tilt and severe deformation will cause the building to collapse.Many small changes caused the tower’s collapse,but the early staff often could not intuitively notice the changes in the tower’s state.In the current tower online monitoring system,terminal equipment often needs to replace batteries frequently due to premature exhaustion of power.According to the need for real-time measurement of power line tower,this research designed a real-time monitoring device monitoring the transmission tower attitude tilting and foundation state based on the inertial sensor,the acceleration of 3 axis inertial sensor and angular velocity raw data to pole average filtering pre-processing,and then through the complementary filtering algorithm for comprehensive calculation of tilt angle,the system meets the demand for inclined online monitoring of power line poles and towers regarding measurement accuracy,with low cost and power consumption.The optimization multi-sensor cooperative detection and correction measured tilt angle result relative accuracy can reach 1.03%,which has specific promotion and application value since the system has the advantages of unattended and efficient calculation.

Low-Frequency Oscillation Analysis of Grid-Connected VSG System Considering Multi-Parameter Coupling

With the increasing integration of new energy generation into the power system and the massive withdrawal of traditional fossil fuel generation,the power system is faced with a large number of stability problems.The phenomenon of low-frequency oscillation caused by lack of damping and moment of inertia is worth studying.In recent years,virtual synchronous generator(VSG)technique has been developed rapidly because it can provide considerable damping and moment of inertia.While improving the stability of the system,it also inevitably causes the problem of active power oscillation,especially the low mutual damping between the VSG and the power grid will make the oscillation more severe.The traditional time-domain state-space method cannot reflect the interaction among state variables and study the interaction between different nodes and branches of the power grid.In this paper,a frequency-domain method for analyzing low-frequency oscillations considering VSG parameter coupling is proposed.First,based on the rotor motion equation of the synchronous generator(SG),a secondorder VSG model and linearized power-frequency control loop model are established.Then,the differences and connections between the coupling of key VSG parameters and low-frequency oscillation characteristics are studied through frequency domain analysis.The path and influencemechanism of a VSG during low-frequency power grid oscillations are illustrated.Finally,the correctness of the theoretical analysis model is verified by simulation.

Dynamic Economic Scheduling with Self-Adaptive Uncertainty in Distribution Network Based on Deep Reinforcement Learning

Traditional optimal scheduling methods are limited to accurate physical models and parameter settings, which aredifficult to adapt to the uncertainty of source and load, and there are problems such as the inability to make dynamicdecisions continuously. This paper proposed a dynamic economic scheduling method for distribution networksbased on deep reinforcement learning. Firstly, the economic scheduling model of the new energy distributionnetwork is established considering the action characteristics of micro-gas turbines, and the dynamic schedulingmodel based on deep reinforcement learning is constructed for the new energy distribution network system with ahigh proportion of new energy, and the Markov decision process of the model is defined. Secondly, Second, for thechanging characteristics of source-load uncertainty, agents are trained interactively with the distributed networkin a data-driven manner. Then, through the proximal policy optimization algorithm, agents adaptively learn thescheduling strategy and realize the dynamic scheduling decision of the new energy distribution network system.Finally, the feasibility and superiority of the proposed method are verified by an improved IEEE 33-node simulationsystem.

Modeling of Large-Scale Hydrogen Storage System Considering Capacity Attenuation and Analysis of Its Efficiency Characteristics

In the existing power system with a large-scale hydrogen storage system,there are problems such as low efficiency of electric-hydrogen-electricity conversion and single modeling of the hydrogen storage system.In order to improve the hydrogen utilization rate of hydrogen storage system in the process of participating in the power grid operation,and speed up the process of electric-hydrogen-electricity conversion.This article provides a detailed introduction to the mathematical and electrical models of various components of the hydrogen storage unit,and also establishes a charging and discharging efficiency model that considers the temperature and internal gas partial pressure of the hydrogen storage unit.These models are of great significance for studying and optimizing gas storage technology.Through these models,the performance of gas storage units can be better understood and improved.These studies are very helpful for improving energy storage efficiency and sustainable development.The factors affecting the charge-discharge efficiency of hydrogen storage units are analyzed.By integrating the models of each unit and considering the capacity degradation of the hydrogen storage system,we can construct an efficiency model for a large hydrogen storage system and power conversion system.In addition,the simulation models of the hydrogen production system and hydrogen consumption system were established in MATLAB/Simulink.The accuracy and effectiveness of the simulation model were proved by comparing the output voltage variation curve of the simulation with the polarization curve of the typical hydrogen production system and hydrogen consumption system.The results show that the charge-discharge efficiency of the hydrogen storage unit increases with the increase of operating temperature,and H2 and O2 partial voltage have little influence on the charge-discharge efficiency.In the process of power conversion system converter rectification operation,its efficiency decreases with the increase of temperature,while in the process of inverter operation,power conversion system efficiency increases with the increase of temperature.Combined with the efficiency of each hydrogen storage unit and power conversion system converter,the upper limit of the capacity loss of different hydrogen storage units was set.The optimal charge-discharge efficiency of the hydrogen storage system was obtained by using the Cplex solver at 36.46%and 66.34%.

Optimal Scheduling Method of Cogeneration System with Heat Storage Device Based on Memetic Algorithm

Electric-heat coupling characteristics of a cogeneration system and the operating mode of fixing electricity with heat are the main reasons for wind abandonment during the heating season in the Three North area.To improve the wind-power absorption capacity and operating economy of the system,the structure of the system is improved by adding a heat storage device and an electric boiler.First,aiming at the minimum operating cost of the system,the optimal scheduling model of the cogeneration system,including a heat storage device and electric boiler,is constructed.Second,according to the characteristics of the problem,a cultural gene algorithm program is compiled to simulate the calculation example.Finally,through the system improvement,the comparison between the conditions before and after and the simulation solutions of similar algorithms prove the effectiveness of the proposed scheme.The simulation results show that adding the heat storage device and electric boiler to the scheduling optimization process not only improves the wind power consumption capacity of the cogeneration system but also reduces the operating cost of the system by significantly reducing the coal consumption of the unit and improving the economy of the system operation.The cultural gene algorithm framework has both the global evolution process of the population and the local search for the characteristics of the problem,which has a better optimization effect on the solution.

Deep Reinforcement Learning Empowered Edge Collaborative Caching Scheme for Internet of Vehicles

With the development of internet of vehicles,the traditional centralized content caching mode transmits content through the core network,which causes a large delay and cannot meet the demands for delay-sensitive services.To solve these problems,on basis of vehicle caching network,we propose an edge colla-borative caching scheme.Road side unit(RSU)and mobile edge computing(MEC)are used to collect vehicle information,predict and cache popular content,thereby provide low-latency content delivery services.However,the storage capa-city of a single RSU severely limits the edge caching performance and cannot handle intensive content requests at the same time.Through content sharing,col-laborative caching can relieve the storage burden on caching servers.Therefore,we integrate RSU and collaborative caching to build a MEC-assisted vehicle edge collaborative caching(MVECC)scheme,so as to realize the collaborative caching among cloud,edge and vehicle.MVECC uses deep reinforcement learning to pre-dict what needs to be cached on RSU,which enables RSUs to cache more popular content.In addition,MVECC also introduces a mobility-aware caching replace-ment scheme at the edge network to reduce redundant cache and improving cache efficiency,which allows RSU to dynamically replace the cached content in response to the mobility of vehicles.The simulation results show that the pro-posed MVECC scheme can improve cache performance in terms of energy cost and content hit rate.

Multi-energy Storage System Model Based on Electricity Heat and Hydrogen Coordinated Optimization for Power Grid Flexibility

Based on decreasing the flexibility of the power grid through the integration of large-scale renewable energy,a multi-energy storage system architectural model and its coor-dination operational strategy with the same flexibility as in the pumped storage power station and battery energy storage system(BESS)are studied.According to the new energy fluctuation characteristics and the different peak valley parameters in the power grid,this paper proposes a electricity heat hydrogen multi-energy storage system(EHH-MESS)and its coordination and optimization operational model to reduce the curtailment of wind power and photovoltaic(PV)to the power grid and improve the flexibility of the power grid.Finally,this paper studied the simulation model of an energy storage optimization control strategy after the multi-energy storage system is connected to the distribution networks,and analyzed three operational modes of the multi-energy storage system.The simulation results show that the EHH-MESS proposed in this paper has a better power grid regulation flexibility and economy,and can be used to replace the battery energy storage system based on MATLAB.

Real-Time Energy Management for Net-Zero Power Systems Based on Shared Energy Storage

Battery energy storage systems(BESSs)serve a crucial role in balancing energy fluctuations and reducing carbon emissions in net-zero power systems.However,the efficiency and cost performance have remained significant challenges,which hinders the widespread adoption and development of BESSs.To address these challenges,this paper proposes a real-time energy management scheme that considers the involvement of prosumers to support net-zero power systems.The scheme is based on two shared energy storage models,referred to as energy storage sale model and power line lease model.The energy storage sale model balances real-time power deviations by energy interaction with the goal of minimizing system costs while generating revenue for shared energy storage providers(ESPs).Additionally,power line lease model supports peer-to-peer(P2P)power trading among prosumers through the power lines laid by ESPs to connect each prosumer.This model allows ESP to earn profits from the use of power lines while balancing power deviations and better consuming renewable energy.Experimental results validate the effectiveness of the proposed scheme,ensuring stable power supply for net-zero power systems and providing benefits for both the ESP and prosumers.

Availability estimation of wind power forecasting and optimization of day-ahead unit commitment

Due to the uncertainty of the accuracy of wind power forecasting,wind turbines cannot be accurately equated with dispatchable units in the preparation of a dayahead dispatching plan for power grid.A robust optimization model for the uncertainty of wind power forecasting with a given confidence level is established.Based on the forecasting value of wind power and the divergence function of forecasting error,a robust evaluation method for the availability of wind power forecasting during given load peaks is established.A simulation example is established based on a power system in Northeast China and an IEEE 39-node model.The availability estimation parameters are used to calculate the equivalent value of wind power of the conventional unit to participate in the dayahead dispatching plan.The simulation results show that the model can effectively handle the challenge of uncertainty of wind power forecasting,and enhance the consumption of wind power for the power system.

GA-iForest: An Efficient Isolated Forest Framework Based on Genetic Algorithm for Numerical Data Outlier Detection

With the development of data age,data quality has become one of the problems that people pay much attention to.As a field of data mining,outlier detection is related to the quality of data.The isolated forest algorithm is one of the more prominent numerical data outlier detection algorithms in recent years.In the process of constructing the isolation tree by the isolated forest algorithm,as the isolation tree is continuously generated,the difference of isolation trees will gradually decrease or even no difference,which will result in the waste of memory and reduced efficiency of outlier detection.And in the constructed isolation trees,some isolation trees cannot detect outlier.In this paper,an improved iForest-based method GA-iForest is proposed.This method optimizes the isolated forest by selecting some better isolation trees according to the detection accuracy and the difference of isolation trees,thereby reducing some duplicate,similar and poor detection isolation trees and improving the accuracy and stability of outlier detection.In the experiment,Ubuntu system and Spark platform are used to build the experiment environment.The outlier datasets provided by ODDS are used as test.According to indicators such as the accuracy,recall rate,ROC curves,AUC and execution time,the performance of the proposed method is evaluated.Experimental results show that the proposed method can not only improve the accuracy and stability of outlier detection,but also reduce the number of isolation trees by 20%-40%compared with the original iForest method.

Day-ahead Optimal Dispatch Model for Coupled System Considering Ladder-type Ramping Rate and Flexible Spinning Reserve of Thermal Power Units

In northern China,thermal power units(TPUs)are important in improving the penetration level of renewable energy.In such areas,the potentials of coordinated dispatch of renewable energy sources(RESs)and TPUs can be better realized,if RESs and TPUs connected to the power grid at the same point of common coupling(PCC)are dispatched as a coupled system.Firstly,the definition of the coupled system is introduced,followed by an analysis on its characteristics.Secondly,based on the operation characteristics of deep peak regulation(DPR)of TPUs in the coupled system,the constraint of the ladder-type ramping rate applicable for day-ahead dispatch is proposed,and the corresponding flexible spinning reserve constraint is further established.Then,considering these constraints and peak regulation ancillary services,a day-ahead optimal dispatch model of the coupled system is established.Finally,the operational characteristics and advantages of the coupled system are analyzed in several case studies based on a real-world power grid in Liaoning province,China.The numerical results show that the coupled system can further improve the economic benefits of RESs and TPUs under the existing policies.

Dispatch Model for Integrated Heat and Power Systems Considering Internal Composition of CHP Plants

An integrated heat and power system(IHPS)is a promising approach for alleviating wind curtailment problems.In an IHPS,the combined heat and power(CHP)plant is the key component,which supplies both heat and electric loads,and couples the thermal system and power system.However,existing research commonly ignores or simplifies the internal composition of CHP plants,which could lead to some unavoidable errors.This paper focuses on the internal composition of CHP plants,and models the physical processes in different components and flexible resources in the CHP plant.Furthermore,a joint dispatch problem of an IHPS with the above CHP plant models is formulated,and an iterative algorithm is developed to handle the nonlinearity in this problem.Case studies are performed based on a real CHP plant in Northern China,and the results indicate that the synergistic effect of different energy resources in the CHP plant is realized by the joint dispatch model,which promotes wind power accommodation and reduces fossil fuel consumption.

Analysis of Strain Clamp Failure on 500 kV Transmission Line

In this work, the main reasons for the breakage of 500 kV transmission line are studied. Under low temperature condition, the coverage of the ice results in the disconnection between the aluminum tube and the steel anchor of strain clamp. Using macroscopic analysis, structure stress analysis, force analysis and mechanical property test, the fractured strain clamps are investigated. The crimping of the aluminum tube on the polished rod not on the grooves of the steel anchor leads to the damage of the strain clamps, which is defined as improper crimping. When improper crimping emerges, there will be only friction force between the aluminum tube and the steel anchor without shear force, and the tension of the conductor will be mainly supported by the steel strands which should be supported by both the aluminum tube and steel stands. Therefore, the breaking force of the strain clamp will greatly decrease. The failure analysis helps to promote the proper hydraulic crimping process and the safe operation of the transmission line.

Ready-to-implement low-carbon retrofit of coal-fired power plants in China:Optimal scenarios selection based on sludge and photovoltaic utilization

Currently the flexible demand for high proportion penetration of renewable energy depends on coal-fired units(CFUs),and the large-scale phase-out of CFUs in a short time is not realistic in China.Due to urban expansion,approximately 458 Chinese coal-fired power plants(CFPPs)are now located in cities.Limited by space,urban CFUs face difficulty in becoming equipped with carbon capture and storage systems.This presents a sizeable challenge for the low-carbon transition of urban CFPPs and carbon neutral processes.Here,we present a ready-to-implement method to reduce the carbon emission of CFPPs in limited space:roof photovoltaic-assisted power generation combined with sludge cocombustion for coal-fired power generation systems(PVSCs).We also consider nonurban CFPPs with the method of roof photovoltaic-assisted power generation(PVs)only.Based on remaining life cycle analysis,we find that the PVSCs could save 28.47 Mt of coal,reduce CO_(2)emissions by 69.76 Mt,treat 125.70 Mt of sludge,and also generate 12.08 billion RMB worth of electricity revenue per year.In addition,our scenario analysis shows that PVSCs are more profitable when choosing an urban CFU with a remaining life of more than 12 years and while the sludge treatment subsidy is set at 100 RMB t
1.Under strict and lenient CFU decommissioning policies,CFUs with a remaining life of between 19 and 30 years and between 13 and 24 years should be selected for PVs,respectively.Thus,we conclude that PVSCs can not only generate economic benefits but also facilitate carbon reduction and solid waste treatment.

Research on practical power system stability analysis algorithm based on modified SVM

Stable and safe operation of power grids is an important guarantee for economy development.Support Vector Machine(SVM)based stability analysis method is a significant method started in the last century.However,the SVM method has several drawbacks,e.g.low accuracy around the hyperplane and heavy computational burden when dealing with large amount of data.To tackle the above problems of the SVM model,the algorithm proposed in this paper is optimized from three aspects.Firstly,the gray area of the SVM model is judged by the probability output and the corresponding samples are processed.Therefore the clustering of the samples in the gray area is improved.The problem of low accuracy in the training of the SVM model in the gray area is improved,while the size of the sample is reduced and the efficiency is improved.Finally,by adjusting the model of the penalty factor in the SVM model after the clustering of the samples,the number of samples with unstable states being misjudged as stable is reduced.Test results on the IEEE 118-bus test system verify the proposed method.

Hierarchical Dispatch Method for Integrated Heat and Power Systems Based on a Feasible Region of Boundary Variables

Fully utilizing the flexibility provided by a district heating system(DHS)can promote wind power accommodation for an electric power system(EPS).However,for privacy or communication reasons,existing power and heat dispatch methods are not suitable for practical application.In this paper,a general math formulation of the hierarchical dispatch method is proposed to coordinate EPS and DHS operators based on the feasible region of boundary variables(FRBV),and a method based on the simplicial approximation approach is proposed to obtain a conservative FRBV approximation of a DHS.A simulation based on a real 41-node DHS is constructed to determine the factors that may impact the boundaries of the FRBV,and then the performance of the simplicial approximation approach is displayed by visualizing the approximation process for the FRBV,and finally three dispatch methods are compared to show the advantages of the proposed hierarchical dispatch method.

Effect of particle size on the thermal performance of NaNO3/SiC)2/C composite phase-change materials

Storage of thermal energy is a key technology for energy conservation and application of renewable energy sources. In this paper, the thermal performance of inorganic composite phase-change materials (PCMs;NaNO3/SiO2/C) is studied under extreme thermal conditions and the effect of raw particle size is examined. We designed a thermal shock test platform with a diffusive combustion system and in-situ infrared thermal imaging. The influences of the heat flux magnitude and exposure time on the performance of the PCMs were examined under vertical thermal shock conditions. Leakage of molten salt in the composite PCMs was observed as the heat flux reached a threshold point. The morphology and thermal properties were characterized by ex-situ SEM, XRD, DSC, and BET. Raw particles with sizes in the range of 105-500 μm were used to synthesize the composite material and examine its role in thermal shock behavior. Our experiments showed that deterioration of the thermal storage density was slowed as the particle size was increased. This work provides useful guidance for improving the anti-thermal shock ability of future material designs.

Intelligent service function chain mapping framework for cloud-and-edge-collaborative IoT

With the rapid development of Internet of thing(IoT) technology, it has become a challenge to deal with the increasing number and diverse requirements of IoT services. By combining burgeoning network function virtualization(NFV) technology with cloud computing and mobile edge computing(MEC), an NFV-enabled cloud-and-edge-collaborative IoT(CECIoT) architecture can efficiently provide flexible service for IoT traffic in the form of a service function chain(SFC) by jointly utilizing edge and cloud resources. In this promising architecture, a difficult issue is how to balance the consumption of resource and energy in SFC mapping. To overcome this challenge, an intelligent energy-and-resource-balanced SFC mapping scheme is designed in this paper. It takes the comprehensive deployment consumption as the optimization goal, and applies a deep Q-learning(DQL)-based SFC mapping(DQLBM) algorithm as well as an energy-based topology adjustment(EBTA) strategy to make efficient use of the limited network resources, while satisfying the delay requirement of users. Simulation results show that the proposed scheme can decrease service delay, as well as energy and resource consumption.

An improved strategy for out-of-step oscillation separation devices based on apparent impedance angle applied to a series compensated line

Out-of-step oscillation separation devices based on apparent impedance angle trajectory are widely used in the power grid in China,and their reliability is of great importance.In this paper,the influence mechanism of series compensation on apparent impedance angle trajectory is analyzed.It reveals that series compensation capacitors reduce the equivalent impedance angle and consequently the apparent impedance angle cannot pass through all four zones,resulting in the risk of failure for the separation devices.A revised method of apparent impedance angle based on compensation principle is discussed,and then an improved out-of-step oscillation detection criterion is proposed.In view of the fact that the apparent impedance angle at the moment of maximum current is equal to the equivalent impedance angle during an oscillation process,a practical algorithm based on the compensated apparent impedance angle is proposed.RTDS tests are conducted to verify the effectiveness of the new criterion,considering transmission lines with a high series compensation level.

Study on the influence of mechanism dispersion on transient recovery voltage distribution of modular DC vacuum circuit breakers

A simulation analysis and an experiment are carried out to investigate how the gap difference between the breaks of a direct current vacuum circuit breakers with multi-breaks(MB-DC VCB)caused by the mechanism dispersion of the breaker influences the distribution of TRV among the breaks.An interruption model of MB-DC VCB,combining the continuous transition model,is established to analyse the rising rate of transient recovery voltage and the dielectric strength recovery speed of the breaks for MB-DC VCB under different gap difference conditions.Based on the experimental platform of dual break DC vacuum circuit breaker breaking,the correctness of the simulation model is verified on a DC VCB with the double-breaks interruption experimental platform.Moreover,a model is applied to the non-synchronous interruption simulation of a DC VCB with three-breaks.The relationship between the TRVs of the breaks under different gap difference conditions is analysed using the comparative analysis method,obtaining the maximum gap difference at the moment of breaking failure.The results of this study show that large-gap breaks have a higher TRV than small-gap breaks(the fracture of the action delay module),with double fractures reaching 1.4 times and triple fractures reaching a maximum of 1.52 times;the ability of small-gap breaks to withstand TRV is weak,giving rise to re-breakdown or even interruption failure;as the number of fractures increases,the maximum gap difference also increases.Improving the synchronous interruption ability of the MB-DC VCB is conducive to improving the interruption performance and interruption success rate of this type of a circuit breaker.