Missing interpolation model for wind power data based on the improved CEEMDAN method and generative adversarial interpolation network

Randomness and fluctuations in wind power output may cause changes in important parameters(e.g.,grid frequency and voltage),which in turn affect the stable operation of a power system.However,owing to external factors(such as weather),there are often various anomalies in wind power data,such as missing numerical values and unreasonable data.This significantly affects the accuracy of wind power generation predictions and operational decisions.Therefore,developing and applying reliable wind power interpolation methods is important for promoting the sustainable development of the wind power industry.In this study,the causes of abnormal data in wind power generation were first analyzed from a practical perspective.Second,an improved complete ensemble empirical mode decomposition with adaptive noise(ICEEMDAN)method with a generative adversarial interpolation network(GAIN)network was proposed to preprocess wind power generation and interpolate missing wind power generation sub-components.Finally,a complete wind power generation time series was reconstructed.Compared to traditional methods,the proposed ICEEMDAN-GAIN combination interpolation model has a higher interpolation accuracy and can effectively reduce the error impact caused by wind power generation sequence fluctuations.

Behavioural analysis and dynamic simulation of the debris flow that occurred in Ganluo County(Sichuan, China) on 30 August 2020

On August 30, 2020, a high-intensity storm that dropped 45.4 mm of rain in 5 hours hit the Heixiluo basin and triggered a landslide-generated debris flow event, causing fatalities and damage. The original source of the debris flow was a large slope collapse on a steep hillside. The fallen debris mass was enlarged through sediment entrainment and slope collapse and ultimately buried a bridge at the gully entrance. Approximately 6.9×10;m;of material, including sediments and collapsed slope deposits in the gullies, was entrained, and the maximum erosion depth reached 17 m. A geomorphological analysis was initially performed based on a detailed field investigation to recognize the liquid and solid sources of the debris flow and the areas subjected to deposition and erosion. A map of the erosiondeposition distribution was obtained based on preand post-event DEMs. Using the rainfall estimated by the nearest rain gauge and the solid source estimated by the DEMs, runoff and debris flow propagation was simulated using a liquid-solid two-phase model that considers the effects of runoff and entrainment. The similarity between the estimated and simulated deposition-erosion volumes was satisfactory. The behaviour of debris flows captured in the simulation is broadly in line with the main features of the observed event.

Blockchain-based Distributed Power Market Trading Mechanism

Distributed power market trading has the characteristics of large number of participants,scattered locations,small single trading scale,and point-to-point trading.The traditional centralized power trading model has the problems of large load,low efficiency,high cost,reliance on third parties and unreliable data.With the characteristics of decentralization and nontampering,blockchain can establish a point-to-point trusted trading environment and provide effective solutions to the above problems.Therefore,this paper proposed a distributed power market trading framework based on blockchain.In this framework,the distributed power supply characteristics and trading needs of each participant are analyzed,a complete distributed trading process based on blockchain is designed.In addition,we have studied the key technologies of distributed power market trading.With the goal of power service reputation and maximum revenue of distributed power providers,we have established a matching degree model,a distributed power market trading optimization model,and designed a smart contract-based power market trading optimization strategy and power trading settlement strategy.Finally,we designed experiments to verify the performance of the proposed framework.

Demand Responsive Market Decision-Makings and Electricity Pricing Scheme Design in Low-Carbon Energy System Environment

The two-way interaction between smart grid and customers will continuously play an important role in enhan-cing the overall efficiency of the green and low-carbon electric power industry and properly accommodating intermittent renewable energy resources.Thus far,the existing electricity pricing mechanisms hardly match the technical properties of smart grid;neither can they facilitate increasing end users participating in the electri-city market.In this paper,several relevant models and novel methods are proposed for pricing scheme design as well as to achieve optimal decision-makings for market participants,in which the mechanisms behind are com-patible with demand response operation of end users in the smart grid.The electric vehicles and prosumers are jointly considered by complying with the technical constraints and intrinsic economic interests.Based on the demand response of controllable loads,the real-time pricing,rewarding pricing and insurance pricing methods are proposed for the retailers and their bidding decisions for the wholesale market are also presented to increase the penetration level of renewable energy.The proposed demand response oriented electricity pricing scheme can provide some useful operational references on the cooperative operation of controllable loads and renewable energy through the feasible retail and wholesale market pricing methods,and thereby enhancing the development of the low-carbon energy system.

A New Principle of Fault Identification of on the Same Tower Based on Traveling Wave Reactive Powers

In order to improve the reliability of fault identification of the double-circuit transmission lines on the same tower, a new algorithm for fast protection of double-circuit transmission lines on the same tower based on the reactive powers of traveling wave is proposed. With the implementation of S-transform, the initial traveling wave reactive powers are calculated and the change characteristics of reactive power under different fault conditions are studied. The protection criterion is constructed by analyzing the ratio of the reactive powers of the same end on double-circuit transmission lines and the ratio of the reactive powers at both ends on the same line. According to the ratio of reactive power on the same side of the line and both ends of the same line, it is possible to identify whether the faults of the double-circuit line of the same tower occurred in or out of the protection zone. A large number of simulation results show that the protection performance is sensitive and reliable, and quick to respond. The criterion is simple and is basically not affected by fault initial angles, fault types, and transitional resistances.

Effects of Transformer DC Bias and the Relationship Between UHVDC Grounding Current and Grounding Resistances

Recently years,UHVDC transmission system is paid more attention to in the field of China's power system.It takes key part in the China electrical power development stratagem.But,many problems are caused by UHVDC system,such as DC bias,corrosion of metal underground and so on.DC bias is harm to the transformers nearby UHVDC grounding polar.In this paper,the influences of DC grounding current on transformer are introduced and some suggestions of DC bias solution were provided.And,the relationship between UHVDC Grounding Current and grounding Resistance of Substation was analyzed.Firstly,two-part network circuit was used to equivalent the grounding circuit.Then,an analysis of rules was done between DC bias current and grounding resistance.Finally,the conclusion is given that DC bias current rises fast as DC grounding resistance or AC grounding resistance rises.It drops when resistance of AC transmission line or interaction resistance between DC grounding system and AC grounding system rises.Decreasing AC grounding resistance and DC grounding resistance is important to restrain DC bias current.Increasing resistance of AC transmission line such as adding resistance into transformer neutral-point grounding is a useful way to limit DC bias current.

Data-driven Optimal Dynamic Dispatch for Hydro-PV-PHS Integrated Power Systems Using Deep Reinforcement Learning Approach

To utilize electricity in a clean and integrated manner,a zero-carbon hydro-photovoltaic(PV)-pumped hydro storage(PHS)integrated power system is studied,considering the uncertainties of PV and load demand.It is a challenge for operators to develop a dynamic dispatch mechanism for such a system,and traditional dispatch methods are difficult to adapt to random changes in the actual environment.Therefore,this study proposes a real-time dynamic dispatch strategy considering economic operation and complementary regulatory ability.First,the dynamic dispatch of a hydro-PV-PHS integrated power system is presented as a multi-objective optimization problem and the weight factor between different goals is effectively calculated using information entropy.Afterwards,the dispatch model is converted into the Markov decision process,where the dynamic dispatch decision is formulated as a reinforcement learning framework.Then,a deep deterministic policy gradient(DDPG)is deployed towards the online decision for dispatch in continuous action spaces.Finally,a case study is applied to evaluate the performance of the proposed method based on a real hydroPV-PHS integrated power system in China.Simulations show that the system agent reduces the power volatility of supply by 26.7%after hydropower regulating and further relieves power fluctuation at the point of common coupling(PCC)to the upperlevel grid by 3.28%after PHS participation.The comparison results verify the effectiveness of the proposed method.

Two-stage distributionally robust optimization-based coordinated scheduling of integrated energy system with electricity-hydrogen hybrid energy storage

A coordinated scheduling model based on two-stage distributionally robust optimization(TSDRO)is proposed for integrated energy systems(IESs)with electricity-hydrogen hybrid energy storage.The scheduling problem of the IES is divided into two stages in the TSDRO-based coordinated scheduling model.The first stage addresses the day-ahead optimal scheduling problem of the IES under deterministic forecasting information,while the sec-ond stage uses a distributionally robust optimization method to determine the intraday rescheduling problem under high-order uncertainties,building upon the results of the first stage.The scheduling model also considers col-laboration among the electricity,thermal,and gas networks,focusing on economic operation and carbon emissions.The flexibility of these networks and the energy gradient utilization of hydrogen units during operation are also incor-porated into the model.To improve computational efficiency,the nonlinear formulations in the TSDRO-based coordinated scheduling model are properly linearized to obtain a Mixed-Integer Linear Programming model.The Column-Constraint Generation(C&CG)algorithm is then employed to decompose the scheduling model into a mas-ter problem and subproblems.Through the iterative solution of the master problem and subproblems,an efficient analysis of the coordinated scheduling model is achieved.Finally,the effectiveness of the proposed TSDRO-based coordinated scheduling model is verified through case studies.The simulation results demonstrate that the proposed TSDRO-based coordinated scheduling model can effectively accomplish the optimal scheduling task while consider-ing the uncertainty and flexibility of the system.Compared with traditional methods,the proposed TSDRO-based coordinated scheduling model can better balance conservativeness and robustness.

Research on On-Line Coordinated Control Strategy to Improve the Voltage Vulnerability after Disturbance

The on-line coordinated control strategy among multi-voltage controls is important to keep voltage security in post-fault systems. Based on the wide area measuring information, the energy function, which can qualify the impacts of the different control actions on voltage of different nodes, is proposed. And then, considering the impacts of different control actions on the node voltage being treated as a weight matrix, the energy margin is used as the objective function and the reactive power margin is innovatively used as the constraint to regulate the control actions globally according to the weight values. At last, the objective functions are solved to get the optimal global coordinated control strategies. The proposed method is identified in an IEEE-30 Bus system and the simulation results show that it effectively improves the voltage stability.

Research on the Prevention and Control Methods for Forest Disasters in China's Forestry Ecological Environment Construction

With the development of economy,China has gradually begun to pay attention to the protection of the natural environment.Under the concept of"lucid waters and lush mountains are invaluable assets",importance has been attached to the development of forestry economy.The protection of forest resources and the prevention and control of disasters are important contents and necessary components in the construction of China's forestry ecological environment.Through the analysis and research on the types of forest disasters(forest fires,biological disasters,meteorological disasters,geological disasters,deforestation)and disaster-causing factors,some basic countermeasures were put forward with the aim to enhance the production capacity of forest resources,improve the ecological environment of forest resources and prevent forest resource disasters.

Non-intrusive Load Monitoring Based on Graph Total Variation for Residential Appliances

Non-intrusive load monitoring is a technique for monitoring the operating conditions of electrical appliances by collecting the aggregated electrical information at the household power inlet.Despite several studies on the mining of unique load characteristics,few studies have extensively considered the high computational burden and sample training.Based on lowfrequency sampling data,a non-intrusive load monitoring algorithm utilizing the graph total variation(GTV)is proposed in this study.The algorithm can effectively depict the load state without the need for prior training.First,the combined Kmeans clustering algorithm and graph signals are used to build concise and accurate graph structures as load models.The GTV representing the internal structure of the graph signal is introduced as the optimization model and solved using the augmented Lagrangian iterative algorithm.The introduction of the difference operator reduces the computing cost and addresses the inaccurate reconstruction of the graph signal.With low-frequency sampling data,the algorithm only requires a little prior data and no training,thereby reducing the computing cost.Experiments conducted using the reference energy disaggregation dataset and almanac of minutely power dataset demonstrated the stable superiority of the algorithm and its low computational burden.

Butler matrix enabled multi-beam optical phased array for two-dimensional beam-steering and ranging

Based on the wavelength transparency of the Butler matrix(BM)beamforming network,we demonstrate a multibeam optical phased array(MOPA)with an emitting aperture composed of grating couplers at a 1.55μm pitch for wavelength-assisted two-dimensional beam-steering.The device is capable of simultaneous multi-beam operation in a field of view(FOV)of 60°×8°in the phased-array scanning axis and the wavelength-tuning scanning axis,respectively.The typical beam divergence is about 4°on both axes.Using multiple linearly chirped lasers,multibeam frequency-modulated continuous wave(FMCW)ranging is realized with an average ranging error of 4 cm.A C-shaped target is imaged for proof-of-concept 2D scanning and ranging.

Improving thermal stability of LiNbO_(3)based electro-optical electric field sensor by depositing a TiO_(2)film

Electro-optic electric field sensors based on LiNbO3 are widely used for the measurement of electric fields or transient voltages.However,the working bias of the sensor is influenced by the temperature due to the thermo-optic effect of LiNbO_(3).An athermal electrooptic electric field sensor was demonstrated by coating a thin layer of TiO_(2)film which has a negative thermo-optic coefficient,on the common-path interferometer based sensor to compensate LiNbO_(3)'s positive thermo-optic coefficient.Both calculation and experimental studies were conducted.The experimental results reasonably agree well with the calculated values,and the results show the sensor coated with a 640 nm thick TiO_(2)film has a much smaller temperature dependence of 0.011°/℃compared to the initial value of 0.1°/℃.

Fast Solution Method for the Large-scale Unit Commitment Problem with Long-term Storage

Long-term storage(LTS)can provide various services to address seasonal fluctuations in variable renewable energy by reducing energy curtailment.However,long-term unit commitment(UC)with LTS involves mixed-integer programming with large-scale coupling constraints between consecutive intervals(state-of-charge(SOC)constraint of LTS,ramping rate,and minimum up/down time constraints of thermal units),resulting in a significant computational burden.Herein,an iterative-based fast solution method is proposed to solve the long-term UC with LTS.First,the UC with coupling constraints is split into several sub problems that can be solved in parallel.Second,the solutions of the sub problems are adjusted to obtain a feasible solution that satisfies the coupling constraints.Third,a decoupling method for long-term time-series coupling constraints is proposed to determine the global optimization of the SOC of the LTS.The price-arbitrage model of the LTS determines the SOC boundary of the LTS for each sub problem.Finally,the sub problem with the SOC boundary of the LTS is iteratively solved independently.The proposed method was verified using a modified IEEE 24-bus system.The results showed that the computation time of the unit combination problem can be reduced by 97.8%,with a relative error of 3.62%.

Multi-stage sizing approach for development of utility-scale BESS considering dynamic growth of distributed photovoltaic connection

The battery energy storage system(BESS)is regarded as one of the most promising address operational challenges caused by distributed generations.This paper proposes a novel multi-stage sizing model for utility-scale BESS,to optimize the BESS development strategies for distribution networks with increasing penetration levels and growth patterns of dispersed photovoltaic(PV)panels.Particularly,an integrated model is established in order to accommodate dispersed PVs in short-term operation scale while facilitating appropriate profits in long-term planning scale.Clusterwise reduction is adopted to extract the most representative operating scenarios with PVs and BESS integration,which is able to decrease the computing complexity caused by scenario redundancy.The numerical studies on IEEE 69-bus distribution system verify the feasibility of the proposed multi-stage sizing approach for the utility-scale BESS.

Scenario-based analysis and probability assessment of sub-synchronous oscillation caused by wind farms with direct-driven wind generators

Recently, explanations of the sub-synchronous oscillation(SSO) caused by wind farms based on directdriven wind generators(DDWGs) have been published in the literatures, in which the controller parameters of DDWGs and the system equivalent parameters play an important role. However, more than one set of parameters can cause weakly damped sub-synchronous modes. The most vulnerable and highly possible scenario is still unknown. To find scenarios that have potential oscillation risks, this paper proposes a small disturbance model of wind farms with DDWGs connected to the grid using a state-space modeling technique. Taguchi’s orthogonal array testing is introduced to generate different scenarios.Multiple scenarios with different parameter settings that may lead to SSOs are found. A probabilistic analysis method based on the Gaussian mixture model is employed to evaluate the consistency of these scenarios with the actual accidents. Electromagnetic transient simulations are performed to verify the findings.

Measurement-based solution for low frequency oscillation analysis

This paper presents a measurement-based solution for low frequency oscillation(LFO) analysis in both real time monitoring and off-line case study. An online LFO property discrimination method is developed first,which alternately uses empirical mode decomposition(EMD)/Hilbert transform(HT) and square calculation to process the measurement data. The method magnifies the variation trend of oscillating variables to accurately discriminate the property of the oscillation. Subsequently, an oscillation source locating method for the forced oscillation(FO) and a strongly correlated generator identification method for the weak damping oscillation(WDO) are proposed. Finally, numerical study results on a test system of the isolated Changdu grid in Tibet validate the proposed methods.

Longer conserved alpine forests ecosystem exhibits higher stability to climate change on the Tibetan Plateau

Aims Vegetation dynamics are simultaneously regulated by climate change and anthropogenic activities.Since the 1980s,climate has been warming on the Tibetan Plateau(TP)at a rate higher than North Hemisphere average.Anthropogenic activities,including grazing,farming,and urbanization,are also influencing the alpine ecosystem on the TP.Especially,an ensemble of large engineering projects,such as power transported from west to east by State Grid,has been in operation on the TP.While studies disentangling effects of climate and anthropogenic activities interference are still lacking for the forest ecosystems on the TP.The overarching objectives of this study were to separate effects of natural climates and human interferences on forest ecosystem dynamics on the TP.Methods We compared vegetation activities of two typical natural reserves(Gongbu natural reserve,GNR,and Yarlung zangbo river grand canyon natural reserve,YNR)and their surroundings in southeastern Tibet(outside of the natural reserves,ONR)using long-term satel-lite normalized difference vegetation index(NDVI)dataset.Linear regression and partial correlation analyses were constructed for the relationship between vegetation activity and climates to evaluate the distinct climate effects on the two natural reserves.Important Findings The two natural reserves were established at different time,which were related to anthropogenic activities impact durations.The results showed that the annual mean NDVI fluctuated between 0.5 and 0.6 in the relatively longer reserved YNR,which was re-markably higher than those in other regions(with NDVI lower than 0.45).The vegetation vigor in the YNR showed neither a sig-nificant temporal trend nor significant relationship with climate.Nevertheless,vegetation vigor exhibited a significant increasing trend during the last three decades(0.012/decade)at the GNR.The inter-decadal analysis turned out positive relationships between vegetation vigor and annual temperature since late 1990s until early 2000s when the GNR was officially established.This study underlined the importance of considering human interference duration when assessing the relationships between vegetation dy-namics and climates.

Torsion Failure Analysis of Galvanized Steel Wires for Transmission and Distribution Lines Based on ANSYS Numerical Simulation

This study provides a detailed failure analysis of galvanized steel wires(3 mm in diameter) for a 35 k V transmission and distribution line, which was carried out by combining the conventional material analysis methods with the finite element method(FEM). It is found that the failed material had good plasticity(5% in elongation),and under the soft torsion loading condition(0.75 in stress state soft coefficient), the ductile fracture should occur on the material. Additionally, the theoretical number of torsions calculated by the FEM was 26.2 times, while the actual number of torsions achieved by the test was only 2.2 times and the local fracture surface exhibited brittle fracture characteristics. The results showed that the local torsion brittle fracture of the material with good plasticity was caused by triaxial stress in the torsion condition, which led to the formation of cavity in the pulling stress area in the material’s center, and the finite element calculation results indicated that the stress state soft coefficient at the cavity was distributed between 0.31 and 0.38, and the stress concentration at the cavity was more than twice the normal value. Besides, the Widmanstatten structure formed as the improper hot working process is the corresponding structural reason.