Capacity Optimization Configuration of Hydrogen Production System for Offshore Surplus Wind Power

To solve the problem of residual wind power in offshore wind farms,a hydrogen production system with a reasonable capacity was configured to enhance the local load of wind farms and promote the local consumption of residual wind power.By studying the mathematical model of wind power output and calculating surplus wind power,as well as considering the hydrogen production/storage characteristics of the electrolyzer and hydrogen storage tank,an innovative capacity optimization allocation model was established.The objective of the model was to achieve the lowest total net present value over the entire life cycle.The model took into account the cost-benefit breakdown of equipment end-of-life cost,replacement cost,residual value gain,wind abandonment penalty,hydrogen transportation,and environmental value.The MATLAB-based platform invoked the CPLEX commercial solver to solve the model.Combined with the analysis of the annual average wind speed data from an offshore wind farm in Guangdong Province,the optimal capacity configuration results and the actual operation of the hydrogen production system were obtained.Under the calculation scenario,this hydrogen production system could consume 3,800 MWh of residual electricity from offshore wind power each year.It could achieve complete consumption of residual electricity from wind power without incurring the penalty cost of wind power.Additionally,it could produce 66,500 kg of green hydrogen from wind power,resulting in hydrogen sales revenue of 3.63 million RMB.It would also reduce pollutant emissions from coal-based hydrogen production by 1.5 tons and realize an environmental value of 4.83 million RMB.The annual net operating income exceeded 6 million RMB and the whole life cycle NPV income exceeded 50 million RMB.These results verified the feasibility and rationality of the established capacity optimization allocation model.The model could help advance power system planning and operation research and assist offshore wind farm operators in improving economic and environmental benefits.

Carbon efficiency evaluation method for urban energy system with multiple energy complementary

Urban energy systems(UESs)play a pivotal role in the consumption of clean energy and the promotion of energy cascade utilization.In the context of the construction and operation strategy of UESs with multiple complementary energy resources,a comprehensive assessment of the energy efficiency is of paramount importance.First,a multi-dimensional evaluation system with four primary indexes of energy utilization,environmental protection,system operation,and economic efficiency and 21 secondary indexes is constructed to comprehensively portray the UES.Considering that the evaluation system may contain a large number of indexes and that there is overlapping information among them,an energy efficiency evaluation method based on data processing,dimensionality reduction,integration of combined weights,and gray correlation analysis is proposed.This method can effectively reduce the number of calculations and improve the accuracy of energy efficiency assessments.Third,a demonstration project for a UES in China is presented.The energy efficiency of each scenario is assessed using six operational scenarios.The results show that Scenario 5,in which parks operate independently and investors build shared energy-storage equipment,has the best results and is best suited for green and low-carbon development.The results of the comparative assessment methods show that the proposed method provides a good energy efficiency assessment.This study provides a reference for the optimal planning,construction,and operation of UESs with multiple energy sources.

A Cascading Fault Path Prediction Method for Integrated Energy Distribution Networks Based on the Improved OPA Model under Typhoon Disasters

In recent times,the impact of typhoon disasters on integrated energy active distribution networks(IEADNs)has received increasing attention,particularly,in terms of effective cascading fault path prediction and enhanced fault recovery performance.In this study,we propose a modified ORNL-PSerc-Alaska(OPA)model based on optimal power flow(OPF)calculation to forecast IEADN cascading fault paths.We first established the topology and operational model of the IEADNs,and the typical fault scenario was chosen according to the component fault probability and information entropy.The modified OPA model consisted of two layers:An upper-layer model to determine the cascading fault location and a lower-layer model to calculate the OPF by using Yalmip and CPLEX and provide the data to update the upper-layer model.The approach was validated via the modified IEEE 33-node distribution system and two real IEADNs.Simulation results showed that the fault trend forecasted by the novel OPA model corresponded well with the development and movement of the typhoon above the IEADN.The proposed model also increased the load recovery rate by>24%compared to the traditional OPA model.

A Compact UHF Antenna Based on Hilbert Fractal Elements and a Serpentine Arrangement for Detecting Partial Discharg

Efforts to protect electric power systems from faults have commonly relied on the use of ultra-high frequency(UHF)antennas for detecting partial discharge(PD)as a common precursor to faults.However,the effectiveness of existing UHF antennas suffers from a number of challenges such as limited bandwidth,relatively large physical size,and low detection sensitivity.The present study addresses these issues by proposing a compact microstrip patch antenna with fixed dimensions of 100 mm×100 mm×1.6 mm.The results of computations yield an optimized antenna design consisting of 2nd-order Hilbert fractal units positioned within a four-layer serpentine arrangement with a fractal unit connection distance of 3.0 mm.Specifically,the optimized antenna design achieves a detection bandwidth for which the voltage standing wave ratio is less than 2 that is approximately 97.3%of the UHF frequency range(0.3–3 GHz).Finally,a prototype antenna is fabricated using standard printed circuit board technology,and the results of experiments demonstrate that the proposed antenna is capable of detecting PD signals at a distance of 8 m from the discharge source.

交直流混合输电线路空间电场分析(英文)

As the transmission line corridors become more and more rare in China,it is now inevitable for people to construct HVAC-HVDC hybrid transmission lines.The research on the electric field around the transmission lines plays an important role in evaluating the electromagnetic environment nearby.However,few existing research now considered the mutual effect of HVAC-HVDC hybrid transmission lines.Thus,this research designed a program based on windows,which calculated the surface voltage gradient on the transmission lines and the electric field at ground level respectively.This research calculated the surface voltage gradient on the transmission lines by applying the improved method of successive images.For the electric field at ground level under AC transmission line,simulation charge method is used,while for the electric field at the ground level under DC transmission lines,deutsch assumption method is used.Comparing the results generated by the calculation with those in published literature,the program is reliable.Taking 500 kV transmission lines as an example,when considering the mutual effect of the HVAC-HVDC lines,the amplitude of the surface voltage gradient will increase by about 10%and the amplitude of the electric field at ground level will increase by about 8%,making the mutual effect of the AC and DC lines unneglectable. Larger part of the electric field at ground level under hybrid lines is produced by the DC line.Thus,in order to control the electric field at ground level under hybrid lines,it should pay more attention on that produced by the DC line.

Building a Cloud-Based Energy Storage System through Digital Transformation of Distributed Backup Battery in Mobile Base Stations

Battery energy storage systems(ESS) have been widely used in mobile base stations(BS) as the main backup power source. Due to the large number of base stations, massive distributed ESSs have largely stayed in idle and very difficult to achieve high asset utilization. In recent years, the fast-paced development of digital energy storage(DES) technology has revolutionized the traditional operation and maintenance of ESSs by transforming them into digital assets, further enabling battery energy storage services, raising up a new way to achieve a much higher utilization of such kind of largely idle ESS resources. In this paper, the disruptive DES technology will be introduced and its application under the context of mobile BSs will be studied, and then a cloud-based energy storage(CES) platform is proposed based on a large scale distributed DESs to provide a new cyber-enabled energy storage service to the local utility company. A real-world case study shows the effectiveness and efficiency of the CES platform.

Fault diagnosis of electric transformers based on infrared image processing and semi-supervised learning

It is crucial to maintain the safe and stable operation of distribution transformers,which constitute a key part of power systems.In the event of transformer failure,the fault type must be diagnosed in a timely and accurate manner.To this end,a transformer fault diagnosis method based on infrared image processing and semi-supervised learning is proposed herein.First,we perform feature extraction on the collected infrared-image data to extract temperature,texture,and shape features as the model reference vectors.Then,a generative adversarial network(GAN)is constructed to generate synthetic samples for the minority subset of labelled samples.The proposed method can learn information from unlabeled sample data,unlike conventional supervised learning methods.Subsequently,a semi-supervised graph model is trained on the entire dataset,i.e.,both labeled and unlabeled data.Finally,we test the proposed model on an actual dataset collected from a Chinese electricity provider.The experimental results show that the use of feature extraction,sample generation,and semi-supervised learning model can improve the accuracy of transformer fault classification.This verifies the effectiveness of the proposed method.

Correlation knowledge extraction based on data mining for distribution network planning

Traditional distribution network planning relies on the professional knowledge of planners,especially when analyzing the correlations between the problems existing in the network and the crucial influencing factors.The inherent laws reflected by the historical data of the distribution network are ignored,which affects the objectivity of the planning scheme.In this study,to improve the efficiency and accuracy of distribution network planning,the characteristics of distribution network data were extracted using a data-mining technique,and correlation knowledge of existing problems in the network was obtained.A data-mining model based on correlation rules was established.The inputs of the model were the electrical characteristic indices screened using the gray correlation method.The Apriori algorithm was used to extract correlation knowledge from the operational data of the distribution network and obtain strong correlation rules.Degree of promotion and chi-square tests were used to verify the rationality of the strong correlation rules of the model output.In this study,the correlation relationship between heavy load or overload problems of distribution network feeders in different regions and related characteristic indices was determined,and the confidence of the correlation rules was obtained.These results can provide an effective basis for the formulation of a distribution network planning scheme.

Space Charge Characteristics of Oil-paper Insulation with New Paper and Aged Oil

Oil-paper compound insulation has been widely used in power transformers for quite a long time because of its good performances. The insulation gradually degrades under combined thermal, electrical and chemical stresses during routine operations, mainly because of space charges inside. This work investigated the space charge characteristics in oil-paper insulation under oil aging circumstance. New trans- former oil samples are thermally aged to obtain different aging states, and their physical and chemical properties are analyzed. New Kraft papers are dried in vacuum and fully immersed in these different aged oil samples, and three kinds of oil-paper samples are obtained. We use the pulsed electro-acoustic (PEA) method to measure space charge under both DC voltage-on and voltage-off conditions at room temperature. The effect of oil aging state on characteristics of space charge injection, accumulation, and decay is analyzed and discussed. The results show that comparing with the DC voltage-off condition, more charges are injected into samples at the interface of electrode and dielectric when DC voltage is on. When the oil-aged state gets worse, more charges are induced at both cathode and anode, more space charges are accumulated in the bulk, the area of negative charges is larger, and local electric field is distorted more seriously. Moreover, for the voltage-off condition, aged oil is good for space charge decay, and trapped positive space charges decay faster than trapped negative charges.

Statistical Characteristics of Partial Discharge Caused by Typical Defects in Cable Joint under Oscillating Voltage

The oscillating voltage test is a nondestructive detection method for partial discharge of XLPE （cross linked polyethylene） cable and has been applied recently. This paper made three kinds of varying severity artificial defect models of cable joints in 10 kV XLPE cable. Oscillating voltage is applied to the model, by use of pulse current method to detect partial discharge signals. In order to study the statistical characteristics of partial discharge of cable joint under the oscillating voltage, three-dimensional statistical map has been made. The results show that for the same kind of defects, with the increases of the defect severity, the discharge interval extended, the magnitude and the number of partial discharge increase, for different kinds of defects, obvious differences exist among the maps, this may established a foundation for the further study of the partial discharge pattern recognition of XLPE cable under oscillating voltage.

Distributed and Risk-averse ADP Algorithm for Stochastic Economic Dispatch of Power System with Multiple Offshore Wind Farms

With more and more offshore wind power being increasingly connected to power grids,fluctuations in offshore wind speeds result in risks of high operation costs.To mitigate this problem,a risk-averse stochastic economic dispatch(ED)model of power system with multiple offshore wind farms(OWFs)is proposed in this paper.In this model,a novel GlueVaR method is used to measure the tail risk of the probability distribution of operation cost.The weighted sum of the expected operation cost and the GlueVaR is used to reflect the risk of operation cost,which can consider different risk requirements including risk aversion and risk neutrality flexibly by adjusting parameters.Then,a risk-averse approximate dynamic programming(ADP)algorithm is designed for solving the proposed model,in which multi-period ED problem is decoupled into a series of single-period ED problems.Besides,GlueVaR is introduced into the approximate value function training process for risk aversion.Finally,a distributed and risk-averse ADP algorithm is constructed based on the alternating direction method of multipliers,which can further decouple single-period ED between transmission system and multiple OWFs for ensuring information privacy.Case studies on the modified IEEE 39-bus system with an OWF and an actual provincial power system with four OWFs demonstrate correctness and efficiency of the proposed model and algorithm.

A Day-ahead Economic Dispatch Method Considering Extreme Scenarios Based on Wind Power Uncertainty

As the intermittency of wind power is a growing concern in the day-ahead economic dispatch,this paper proposes a day-ahead economic dispatch method considering extreme scenarios of wind power by using an uncertainty set.The uncertainty set inspired by robust optimization is used to describe wind power intermittency in this paper.Four extreme scenarios based on the uncertainty set are formulated to represent the worst cases of wind power fluctuation.An economic dispatch method considering the costs of both load shedding and wind curtailment is proposed.The economic dispatch model can be easily solved by a quadratic programming method owing to the introduction of four extreme scenarios and the uncertainty set of wind power.Simulation is done using the IEEE 30-bus system and the results verify the effectiveness of the proposed method.

Carbon emission impact on the operation of virtual power plant with combined heat and power system

A virtual power plant （VPP） can realize the aggregation of distributed generation in a certain region, and represent distributed generation to participate in the power market of the main grid. With the expansion of VPPs and ever-growing heat demand of consumers, managing the effect of fluctuations in the amount of available renewable resources on the operation of VPPs and maintaining an economical supply of electric power and heat energy to users have been important issues. This paper proposes the allocation of an electric boiler to realize wind power directly converted for supplying heat, which can not only overcome the limitation of beat output from a combined heat and power （CHP） unit, but also reduce carbon emissions from a VPP. After the electric boiler is considered in the VPP operation model of the combined heat and power system, a multi-objective model is built, which includes the costs of carbon emissions, total operation of the VPP and the electricity traded between the VPP and the main grid. The model is solved by the CPLEX package using the fuzzy membership function in Matlab, and a case study is presented. The power output of each unit in the case study is analyzed under four scenarios. The results show that after carbon emission is taken into account, the output of low carbon units is significantly increased, and the allocation of an electric boiler can facilitate the maximum absorption of renewable energy, which also reduces carbon emissions from the VPP.

The Averaged-value Model of a Flexible Power Electronics Based Substation in Hybrid AC/DC Distribution Systems

The concept of a flexible power electronics substation(FPES)was first applied in the Zhangbei DC distribution network demonstration project.As a multi-port power electronics transformer(PET)with different AC and DC voltage levels,the FPES has adopted a novel topology integrating modular multilevel converter(MMC)and four-winding medium frequency transformer(FWMFT)based multiport DC-DC converter,which can significantly reduce capacitance in each sub-module(SM)of a MMC and also save space and cost.In this paper,in order to accelerate speed of electromagnetic transient(EMT)simulations of FPES based hybrid AC/DC distribution systems,an averaged-value model(AVM)is proposed for efficient and accurate representation of FPES.Assume that all SM capacitor voltages are perfectly balanced in the MMC,then the MMC behavior can be modeled using controlled voltage sources based on modulation voltages from control systems.In terms of the averaged current transfer characteristics among the windings of the FWMFT,we consider that all multiport DC-DC converters are controlled with the same dynamics,a lumped averaged model using controlled current and voltage sources has been developed for these four-port DC-DC converters connected to the upper or lower arms of the MMC.The presented FPES AVM model has been tested and validated by comparison with a detailed IGBT-based EMT model.Results show that the AVM is significantly more efficient while maintaining its accuracy in an EMT simulation.

Stochastic Accelerated Alternating Direction Method of Multipliers for Hedging Communication Noise in Combined Heat and Power Dispatch

Combined heat and power dispatch(CHPD)opens a new window for increasing operational flexibility and reducing wind power curtailment.Electric power and district heating systems are independently controlled by different system operators;therefore,a decentralized solution paradigm is necessary for CHPD,in which only minor boundary information is required to be exchanged via a communication network.However,a nonideal communication environment with noise could lead to divergence or incorrect solutions of decentralized algorithms.To bridge this gap,this paper proposes a stochastic accelerated alternating direction method of multipliers(SA-ADMM)for hedging communication noise in CHPD.This algorithm provides a general framework to address more types of constraint sets and separable objective functions than the existing stochastic ADMM.Different from the single noise sources considered in the existing stochastic approximation methods,communication noise from multiple sources is addressed in both the local calculation and the variable update stages.Case studies of two test systems validate the effectiveness and robustness of the proposed SAADMM.

Scenario-based Optimal Real-time Charging Strategy of Electric Vehicles with Bayesian Long Short-term Memory Networks

Joint operation optimization for electric vehicles(EVs)and on-site or adjacent photovoltaic generation(PVG)are pivotal to maintaining the security and economics of the operation of the power system concerned.Conventional offline optimization algorithms lack real-time applicability due to uncertainties involved in the charging service of an EV charging station(EVCS).Firstly,an optimization model for real-time EV charging strategy is proposed to address these challenges,which accounts for environmental uncertainties of an EVCS,encompassing EV arrivals,charging demands,PVG outputs,and the electricity price.Then,a scenario-based two-stage optimization approach is formulated.The scenarios of the underlying uncertain environmental factors are generated by the Bayesian long short-term memory(B-LSTM)network.Finally,numerical results substantiate the efficacy of the proposed optimization approach,and demonstrate superior profitability compared with prevalent approaches.

Reduced-order Modeling and Dynamic Stability Analysis of MTDC Systems in DC Voltage Control Timescale

An equivalent source-load MTDC system including DC voltage control units,power control units and interconnected DC lines is considered in this paper,which can be regarded as a generic structure of low-voltage DC microgrids,mediumvoltage DC distribution systems or HVDC transmission systems with a common DC bus.A reduced-order model is proposed with a circuit structure of a resistor,inductor and capacitor in parallel for dynamic stability analysis of the system in DC voltage control timescale.The relationship between control parameters and physical parameters of the equivalent circuit can be found,which provides an intuitive insight into the physical meaning of control parameters.Employing this model,a second-order characteristic equation is further derived to investigate system dynamic stability mechanisms in an analytical approach.As a result,the system oscillation frequency and damping are characterized in a straight forward manner,and the role of electrical and control parameters and different system-level control strategies in system dynamic stability in DC voltage control timescale is defined.The effectiveness of the proposed reduced-order model and the correctness of the theoretical analysis are verified by simulation based on PSCAD/EMTDC and an experiment based on a hardware low-voltage MTDC system platform.

Application status and development trends for intelligent perception of distribution network

Intelligent perception is the cornerstone of digitalisation of power grid.Due to the closest connection with users,the information perception ability of distribution network directly affects the reliability of power supply.Distribution network has a wide range of geographical distribution and equipment types.The application of intelligent perception is with high complexity and dynamics under the limitation of both technology and management.Therefore,the study first sorts out the current application status of intel-ligent perception technology and equipment in distribution network from three appli-cation fields including distribution automation,metering systems,and inspection.Then,the constraints of existing intelligent perception applications and the key points of further research are pointed out.Finally,the development trends of intelligent perception technology in distribution network are presented from the three aspects of basic tech-nology,perception equipment,and advanced applications.With the improvement of sensing,communication,energy acquisition,chips and perception equipments,the depth and breadth of advanced applications in distribution network will be expanded.The research results can provide references for the follow‐up research and practice of intel-ligent perception in distribution networks.

Dynamic ageing research of cross‐linked polyethylene cable insulation based on temporal‐spatial dimension under combined electro‐thermal effect

Dynamic ageing process of cross‐linked polyethylene(XLPE)cable insulation under combined electro‐thermal effect is investigated by the construction of theoretical analysis model and the practice of operation‐simulated ageing test.Firstly,theoretical analysis model is constructed from time and spatial dimensions.From the time dimension,in the light of the impeding trend of internal stress to external stress,the XLPE ageing process of Steady state‐Transition state‐Steady state(STS)is proposed to illustrate the dynamic ageing process of XLPE.From the spatial dimension,the insulation is divided into three scales to quantify the ageing.Secondly,to practice the theoretical analysis model,an operation‐simulated ageing test was conducted on two high voltage alternating current cables with service years of 15 and 30 for 540 days.Subsequently,relevant diagnostic measurements were applied to analyse the influence of physicochemical characteristics on the dielectric and heat transfer performances of the cables.The results show that the degradation of the actual operating cable is an extremely slow process.On the one hand,the response in physical changes of morphology counterbalances the external stress,maintaining the stability.On the other hand,once the chemical changes occur,negative feedback mechanism tends to impede the occurrence of further degradation by regulating fields distribution.

Evaluation Method and Probabilistic Index of Voltage Sag Severity Considering Point-on-wave

The impact of voltage sag on sensitive devices is related to the time when the sag occurs.However,the point-on-wave of a sag is uncertain.Therefore,this paper presents a nov-el approach to evaluate the voltage sag severity considering a random point-on-wave.First,the uncertainty of equipment malfunction is revealed.Second,under a given residual voltage,the relationship between the point-on-wave and the duration that the device can withstand is described with a fitting curve.Third,a voltage sag probabilistic index is proposed to describe the severity.The evaluation procedure is also presented.Finally,three types of releasers are tested and analyzed to determine the effectiveness of the proposed method.The evaluation method can help instruct electrical engineers establish more well-grounded sag mitigation proposals.