Dynamic Modeling of Key Operating Parameters for Supercritical Circulating Fluidized Bed Units based on Data-Knowledge-Driven Method

To address the pressing need for intelligent and efficient control of circulating fluidized bed(CFB)units,it is crucial to develop a dynamic model for the key operating parameters of supercritical circulating fluidized bed(SCFB)units.Therefore,data-knowledge-driven dynamic model of bed temperature,load,and main steam pressure of the SCFB unit has been proposed.Firstly,a knowledge-driven method is employed to develop a dynamic model for key operating parameters of SCFB units.The model parameters are determined based on the operating data of the unit and continuously optimized in real time.Then,Bidirectional Long Short-Term Memory combined with Convolutional Neural Network and Attention Mechanism is utilized to build the dynamic model of bed temperature,load,and main steam pressure.Finally,a collaboration and integration method based on the critic weight method and the variation coefficient method is proposed to establish data-knowledge-driven model of key operating parameters for SCFB units.The model displays great accuracy and fitting ability compared with other methods and effectively captures the dynamic characteristics,which can provide a research basis for the design of intelligent flexible control mode of SCFB unit.

Assessment Method of Offshore Wind Resource Based on Multi-dimenssiional Indexes System

Traditional assessment indexes could not fully describe offshore wind resources,for the meteorological properties of offshore are more complex than onshore.As a result,the uncertainty of offshore wind power projects would be increased and final economic benefits would be affected.Therefore,a study on offshore wind resource assessment is carried out,including three processes of“studying data sources,conducting multidimensional indexes system and proposing an offshore wind resource assessment method based on analytic hierarchy process(AHP).First,measured wind data and two kinds of reanalysis data are used to analyze the characteristics and reliability of data sources.Second,indexes such as effective wind speed occurrence,affluent level occurrence,coefficient of variation,neutral state occurrence have been proposed to depict availability,richness,and stability of offshore wind resources,respectively.Combined with existing parameters(wind power density,dominant wind direction occurrence,water depth,distance to coast),a multidimensional indexes system has been built and on this basis,an offshore wind energy potential assessment method has been proposed.Furthermore,the proposed method is verified by the annual energy production of five offshore wind turbines and practical operating data of four offshore wind farms in China.This study also compares the ranking results of the AHP model to two multi-criteria decision making(MCDM)models including weighted aggregated sum product assessment(WASPAS)and multi-attribute ideal real comparative analysis(MAIRCA).Results show the proposed method gains well in practical engineering applications,where the economic score values have been considered based on the offshore reasonable utilization hours of the whole life cycle in China.

Energy Management and Optimization of Vehicle-to-grid Systems for Wind Power Integration

An approach to smoothing the fluctuations of largescale wind power is investigated using vehicle-to-grid(V2G)systems.First,an energy management and optimization system is designed and modeled.By using the wavelet packet decomposition method,the target grid-connected wind power,the required electric vehicle(EV)power,and supercapacitor power are determined.The energy management model for EVs is then developed by introducing a knapsack problem that can evaluate the needs of an EV fleet.Furthermore,an optimized dispatch strategy for EVs and wind power is developed by using a dynamic programming method.A case study demonstrates that the energy management and optimization method for V2G systems achieves noticeable performance improvements over benchmark techniques.

Applying Power Margin Tracking Droop Control to Flexible Operation in Multi-terminal DC Collector Systems of Renewable Generation

An emerging multi-terminal looped DC(MTDC)collector system is now advocated for collecting and transferring large-scale renewable generation.However,it remains an open question as to improving the cooperative control capability of looped converter stations for flexible and robust response to renewable grid-connection fluctuation.This paper addresses this problem with a novel Power Margin Tracking(PMT)droop control and its corresponding system-level control strategy from the perspective of optimal dispatch of the power system.By introducing a power margin correction factor into the droop coefficient,the converter station can make self-adaptive regulations according to its actual available power margin.For operation verification,a multi-period optimal operation model and a four-terminal simulation model is built to provide optimal control parameters and real-time operation states of converter stations,where the power flow model of the looped MTDC grid with renewables generation is considered.The case results prove that the proposed control strategy can improve the cooperative operation capability of multiple converter stations,mitigating grid-connected power fluctuation.It can effectively reduce the DC voltage deviation to enhance the operation stability of the MTDC grid.The operational robustness of the proposed control strategy under“N−1”fault cases is verified as well.

Optimal Planning of IDR-integrated Electricity-heat Systems Considering Techno-economic and Carbon Emission Issues

This study presents an optimal electricity-heat system(EHS)planning framework to promote the accommodation of wind power while considering technical,economic and environmental criteria.To this end,integrated demand response(IDR)is introduced as a flexibility resource to complement the inherent fluctuation of renewable energy sources and modeled by using price elasticity theory.Both the timing transferring and energy substitution potentials are considered in the proposed IDR program.Incorporating the effect of IDR into the EHS planning model,a two-stage stochastic programming model can be devised,in which the optimal EHS configuration design and associated operation control techniques are found simultaneously to minimize the system’s total economic and carbon-emission costs over the planning horizon.The multi-scale uncertainties arising from both long-term demand growth and operation-level variability of renewables/load demands are captured collectively by using a scenario-based method.The suggested planning approach is illustrated using a real EHS test case and the results show that it is effective in practical applications.

Surface Charge Accumulation Characteristics on DC GIL Three-post Insulators Considering the Influence of Temperature Gradient

Surface charge accumulation is considered to be a critical factor in flashover failure of three-post insulators.However,surface charge accumulation characteristics on threepost insulators with complex structures and uneven electric fields are still unclear.Furthermore,the temperature gradient field makes charge accumulation more complicated.In this presentation,surface charge profiles of DC three-post insulators under electro-thermal coupling stress are studied by establishing a multi-degree-of-freedom movement measurement system.The abdominal area of the three-post insulator accumulaftes charges of identical polarity as the DC voltage,while the leg area accumulates heteropolar charges.Charge density from the bottom of the leg to the center of the abdomen presents a trimodal distribution pattern,including two homopolar charge peaks and one heteropolar charge peak.Asymmetrical surface conductance distribution arising from the temperature gradient leads to a significant increase in amplitude and distribution range of the homopolar charge peak at the legs of insulator.Increase of the temperature gradient will further magnify the homopolar charge peak at the legs.When DC voltage is 100 kV and conductive pole temperature is 70℃,surface charge density of the three-post insulator can reach 100μC/m^(2).Therefore,surface conductance regulation of the leg region is the key to charge regulation and insulation optimization design of DC three-post insulators.

Dynamics and Small Signal Stability Analysis of PMSG-based Wind Farm with an MMC-HVDC System

The permanent magnet synchronous generator (PMSG)-based wind farm with a modular multilevel converter (MMC) based HVDC system exhibits various oscillations and can experience dynamic instability due to the interactions between different controllers of the wind farm and MMC stations, which have not been properly examined in the existing literatures. This paper presents a dynamic modeling approach for small signal stability analysis of PMSG-based wind farms with a MMC- HVDC system. The small signal model of the study system is validated by the comprehensive electromagnetic transient (EMT) simulations in PSCAD/EMTDC. Then the eigenvalue approach and participation factors analysis are utilized to comprehensively evaluate the impact of different controllers, system’s parameters and the circulating current suppressing controller (CCSC) on the small signal stability of the entire system. From eigenvalue analysis, it is revealed that as the output active power of the wind farm increases within the rated range, the overall system will exhibit a sub-synchronous oscillation (SSO) instability mode, an extremely weak damping mode, and a low frequency oscillation instability mode. From participation factors analysis, it is observed that the SSO mode and weak damping mode are primarily related to the internal dynamics of the MMC, which can be suppressed or improved by CCSC. It is determined that the low frequency oscillation mode is primarily caused by the interactions between the phase locked loop (PLL) control of the wind farm and the voltage and frequency (V-F) control of the MMC station. The analysis also depicts that the larger proportional gain value of the V-F control of the MMC station and smaller PLL bandwidth of the wind farm can enhance the small signal stability of the entire system.

Resilience-oriented Restoration Strategy by Offshore Wind Power Considering Risk

Global climate changes have created intense naturaldisasters such as typhoons, which may cause serious damage topower systems. As an emerging renewable energy resource, offshore wind power has great potential in power systems resilienceenhancement with its rapid start-up capability and developmentof anti-typhoon technology. In this paper, a restoration strategyby offshore wind power considering risk is proposed to speedup the restoration process and enhance system resilience. Specifically, a failure risk model of an individual wind turbine andthen the whole wind farm is built for predicting severe weather’simpact, with focus on failure probability. Further, a quantificationmodel of resilience enhancement and risk cost, based on customerinterruption cost assessment method, is introduced. Then, a twostage optimized decision-making model is proposed to solve thescheme of offshore wind power and conventional power unitsin load restoration process. Case studies are undertaken on amodified IEEE RTS-79 system and results indicate the proposedrestoration strategy can shorten duration of restoration andreduce customers’ economic losses meanwhile ensuring systemsafety.

Study on Clamping Type DC Circuit Breaker with Short Fault Isolation Time and Low Energy Dissipation

The development of DC grids faces challenges from DC fault protection.The conventional DC circuit breaker(DCCB)employs metal-oxide varistor(MOV)to isolate the faulted line,in which the fault isolation process is coupled with the energy dissipation process.In this study,a clamping type DCCB(CTCB)using internal capacitors to clamp the converter voltage is proposed.Thanks to the proposed configuration,fault isolation and energy dissipation are decoupled,resulting in a fast fault isolation and low energy dissipation compared to the conventional DCCB.The working principle of the proposed CTCB is presented and verified in a DC grid simulation model.A comparison is made with the traditional DCCB.The fault isolation time can be reduced by 34.5%.The dissipated energy can be reduced by 17.4%.The energy dissipation power can be reduced by 76.2%.

Multi-microgrid Energy Management Systems: Architecture, Communication, and Scheduling Strategies

The increasing penetration of various distributed and renewable energy resources at the consumption premises,along with the advanced metering,control and communication technologies,promotes a transition on the structure of traditional distribution systems towards cyber-physical multi-microgrids(MMGs).The networked MMG system is an interconnected cluster of distributed generators,energy storage as well as controllable loads in a distribution system.And its operation complexity can be decomposed to decrease the burdens of communi-cation and control with a decentralized framework.Consequently,the multi-microgrid energy management system(MIVIGEIV1S)plays a significant role in improving energy efficiency,power quality and reliability of distribution systems,especially in enhancing system resiliency during contingencies.A comprehensive overview on typical functionalities and architectures of MMGEMS is illustrated.Then,the emerging communication technologies for information monitoring and interaction among MMG clusters are surveyed.Furthermore,various energy scheduling and control strategies of MMGs for interactive energy trading,multi-energy management,and resilient operations are thoroughly analyzed and investigated.Lastly,some challenges with great importance in the future research are presented.

Improved Model Predictive Control with Prescribed Performance for Aggregated Thermostatically Controlled Loads

Aggregate thermostatically controlled loads(AT-CLs)are a suitable candidate for power imbalance on demand side to smooth the power fluctuation of renewable energy.A new control scheme based on an improved bilinear aggregate model of ATCLs is investigated to suppress power imbalance.Firstly,the original bilinear aggregate model of ATCLs is extended by the second-order equivalent thermal parameter model to optimize accumulative error over a long time scale.Then,to ensure the control performance of tracking error,an improved model predictive control algorithm is proposed by integrating the Lyapunov function with the error transformation,and theoretical stability of the proposed control algorithm is proven.Finally,the simulation results demonstrate that the accuracy of the improved bilinear aggregate model is enhanced;the proposed control algorithm has faster convergence speed and better tracking accuracy in contrast with the Lyapunov function-based model predictive control without the prescribed performance.

Coordinated Control of DC Circuit Breakers in Multilink HVDC Grids

High voltage DC grids are developing in more terminals and with larger transmission capacity,thus the re-quirements for DC circuit breakers(DCCB)will continue to rise.Conventional methods only use the faulty line DCCB to withstand the fault stress,and therefore this paper presents a coordination method of multiple DCCBs to protect the system.As many adjacent DCCBs are tripped to interrupt the fault current,the fault energy is shared,and the requirement for the faulty line DCCB is reduced.Moreover,the adjacent DCCBs are actively controlled to help system recovery.The primary protection,backup protection,and reclosing logic of multiple DCCBs are studied.Simulations confirm that the proposed control reduces the energy dissipation requirement of faulty line DCCB by approximately 30%-42%,the required current rating for IGBTs is reduced,and the system recovery time is also reduced by 20-40 ms.

Influence of Parasitic Parameters on Dynamic Threshold Voltage Hysteresis of Silicon Carbide MOSFETs

Threshold voltage (V_(TH)) hysteresis affects the dynamic characteristics of silicon carbide (SiC) MOSFETs, whichin turn affects reliability of a device. In this paper, a dynamichysteresis curve is proposed as an evaluation method of theinfluence of V_(TH) hysteresis on the switching characteristics ofSiC MOSFETs. This method can eliminate the impact of triggerlevel and obtain the dynamic V_(TH). Furthermore, the influence ofparasitic parameters on dynamic V_(TH) hysteresis is theoreticallyanalyzed. Double pulse tests under different parasitic parametersare performed on three SiC MOSFETs with different gatestructures to verify the analysis. Results show that gate resistance(R_(G)) and source inductance (L_(S)) have more significant effectson dynamic V_(TH) hysteresis compared with gate inductance anddrain inductance. V_(TH) hysteresis phenomenon weakens withincrease of R_(G) or L_(S), which is related to device structure.The results presented in this paper can provide guidance forthe design of circuit parasitic parameters of SiC MOSFETs toregulate V_(TH) hysteresis.

Intelligent Breakage Assessment of Composite Insulators on Overhead Transmission Lines by Ellipse Detection Based on IRHT

With the development of unmanned aerial vehicle(UAV)technology,visible images are playing an important role in the maintenance of power systems.To achieve the shed breakage evaluation of composite insulators by UAV visible images,an intelligent fault assessment method is proposed.First,the composite insulators in visible light images are identified by Faster-RCNN.After image preprocessing,the image is enhanced and the noise is removed.Then,a canny operator is used to extract the edge of the sheds.An Improved Randomized Hough Transform(IRHT)is used to detect the ellipses in the edge image.The parameters of the detected ellipse,length of major axes and minor axes,center coordinates and deflection angle of major axes,are used to realize the segmentation of the composite insulator.Finally,the number of pixel points in the ellipse and the distance between the points and the ellipse boundary are used to judge whether there are breakage or cracks on the sheds.The area ratio of the breakage to the whole shed is calculated based on the number of pixel points inside the broken area.This method can be realized without a large amount of training dataset of the specific fault type and provides a technical basis for the online fault assessment of a composite insulator on overhead transmission lines.

Generalized Predictive Control for Superheated Steam Temperature Regulation in a Supercritical Coal-fired Power Plant

The design and implementation of a Generalized Predictive Control(GPC)strategy for the superheated steam temperature regulation in a supercritical(SC)coal-fired power plant is presented.A Controlled Auto-Regressive MovingAverage(CARMA)model of the plant is derived from using the experimental data to approximately predict the plant’s future behavior.This model is required by the GPC algorithm to calculate the future control inputs.A new GPC controller is designed and its performance is tested through extensive simulation studies.Compared with the performance of the plant using a conventional PID controller,the steam temperature controlled by the GPC controller is found to be more stable.The stable steam temperature leads to more efficient plant operation and energy saving,as demonstrated by the simulation results.Plant performance improvement is also tested while the plant experiences the load demand changes and disturbances resulting from the malfunctioning of coal mills.

A DC Chopper Topology to Mitigate Commutation Failure of Line Commutated Converter Based High Voltage Direct Current Transmission

To reduce the probability of commutation failure(CF)of a line commutated converter based high-voltage direct current(LCC-HVDC)transmission,a DC chopper topology composed of power consumption sub-modules based on thyristor full-bridge module(TFB-PCSM)is proposed.Firstly,the mechanism of the proposed topology to mitigate CF is analyzed,and the working modes of TFB-PCSM in different operation states are introduced.Secondly,the coordinated control strategy between the proposed DC chopper and LCC-HVDC is designed,and the voltage-current stresses of the TFB-PCSMs are investigated.Finally,the ability to mitigate the CF issues and the fault recovery performance of LCC-HVDC system are studied in PSCAD/EMTDC.The results show that the probability of CF of LCC-HVDC is significantly reduced,and the performances of fault recovery are effectively improved by the proposed DC chopper.

User Decision-based Analysis of Urban Electric Vehicle Loads

The grid load attributable to electric vehicles (EVs)is affected by the choice behaviors of EV users. To analyze theeffects of factors such as travel demand and electricity priceson user behavior, a logit discrete choice model is introducedto simulate the users decisions to charge/travel. Based on aquasi-steady-state traffic network, a model for cluster electricvehicles considering the user’s behavior is designed to obtain theprobability distribution of the user’s behavior and the chargeand discharge curves of cluster EVs under various scenarios. Thevalidity of the proposed model is verified using an IEEE 9-nodetraffic network case and an urban traffic network case. Furthermore,the impact of the electricity price, traffic conditions, andother factors on the load curves of urban EVs is analyzed.

SSO Risk Evaluation for a Grid-connected PMSG-based Wind Farm Based on Sequential Monte Carlo Simulation

In a grid-connected wind farm based on permanent magnet synchronous generators(PMSGs),the wind speed and the number of operating PMSGs are the two most important influencing factors along with the stochastic nature of sub-synchronous oscillation(SSO)from the point view of the farm.This paper proposes a method of unstable SSO risk evaluation for grid-connected PMSG-based wind farms based on the sequential Monte Carlo simulation(SMCS).The determination of critical wind speed(CWS)of SSO and the sequential simulation strategy of wind speed states and PMSG states in a wind farm at the same wind speed(S-WF),as well as in a wind farm at different wind speeds(D-WF),are studied.Five indices evaluating the expectation,duration,frequency and energy loss of SsO risk are proposed.Moreover,a strategy to reduce SsO risk by adjusting the cut-in wind speed is discussed.The effectiveness of the discussed issues in this paper are proved by the case studies of a 750-PMSG wind farm based on the actual wind speed data collected.

Spatio-temporal Granularity Co-optimization Based Monthly Electricity Consumption Forecasting

Monthly electricity consumption forecasting(ECF)plays an important role in power system operation and electricity market trading.Widespread popularity of smart meters enables collection of fine-grained load data,which provides an opportunity for improvement of monthly ECF accuracy.In this letter,a spatio-temporal granularity co-optimization-based monthly ECF framework is proposed,which aims to find an optimal combination of temporal granularity and spatial clusters to improve monthly ECF accuracy.The framework is formulated as a nested bi-layer optimization problem.A grid search method combined with a greedy clustering method is proposed to solve the optimization problem.Superiority of the proposed method has been verified on a real smart meter dataset.