Economic factors along with legislation and policies to counter harmful pollution apply specifically to maritime drive research for improved power generation and energy storage.Proton exchange membrane fuel cells are ...Economic factors along with legislation and policies to counter harmful pollution apply specifically to maritime drive research for improved power generation and energy storage.Proton exchange membrane fuel cells are considered among the most promising options for marine applications.Switching converters are the most common interfaces between fuel cells and all types of load in order to provide a stable regulated voltage.In this paper,a method using artificial neural networks(ANNs)is developed to control the dynamics and response of a fuel cell connected with a DC boost converter.Its capability to adapt to different loading conditions is established.Furthermore,a cycle-mean,black-box model for the switching device is also proposed.The model is centred about an ANN,too,and can achieve considerably faster simulation times making it much more suitable for power management applications.展开更多
This paper presents detailed design steps of an effective control system aiming to increase the solar energy harvested via photovoltaic power-generation systems.The design of an intelligent maximum power point tracker...This paper presents detailed design steps of an effective control system aiming to increase the solar energy harvested via photovoltaic power-generation systems.The design of an intelligent maximum power point tracker(MPPT)supported by a robust sliding-mode(SM)controller is discussed in this study.The proposed control scheme is designed to track the MPP and provide a smooth system response by removing the overshoot in the load current during any variation in the connected load.Such a system is suitable for DC-DC buck converter applications.The study begins with modelling the buck converter for a continuous current mode operation.The reference voltage of the tracking system is produced by the proposed neural network(NN)algorithm.The proposed intelligent MPPT integrated with an SM controller is simulated in a MATLAB®/Simulink®platform.The simulation results are analysed to investigate and confirm the satisfaction level of the adopted four-serially connected PV-modules system.The system performance is evaluated at a light intensity of 500 W/m^(2) and an ambient temperature of 25°C.Applying only the proposed NN algorithm guarantees the MPP tracking response by delivering 100 W at a resistive load of 13Ω,and 200 W at a load of 6.5Ω,respectively,with 99.77%system efficiency.However,this simultaneously demonstrates a current spike of~0.5 A when the load is varied from 50%to 100%.The integrated SM controller demonstrates a robust and smooth response,eliminating the existing current spike.展开更多
In a translucent network scenario, development of an optical control plane (OCP) that is aware of the location and number of available regenerators and all-optical wavelength converters (AOWCs) is of paramount importa...In a translucent network scenario, development of an optical control plane (OCP) that is aware of the location and number of available regenerators and all-optical wavelength converters (AOWCs) is of paramount importance. However, current generalized multiprotocol label switching (GMPLS) protocol suite does not consider the distribution of regenerator and AOWC availability information to all the network nodes. In this paper, we propose a novel optical control plane (OCP) architecture that 1) disseminates information about network components (i.e. regenerators and AOWCs) to all the network nodes, and 2) evaluates candidate routes which use fewest amounts of network components. Performance of the proposed OCP is compared with a recently proposed hybrid OCP approach in terms of blocking performance, number of deployed components and lightpath establishment setup times. The obtained simulation results show that the proposed OCP approach demonstrates low connection blocking and establishes lightpaths by 1) minimizing the overall network cost owing to the deployment of minimum total number of network components, and 2) demonstrating acceptable lightpath establishment setup times at all traffic loads. Further, the proposed OCP methodology is compatible and suitable for controlling the operations of a novel electro-optical hybrid translucent node which is a latency efficient technology capable of delivering a cost effective implementation suitable for large scale deployment.展开更多
Hybrid AC/DC distribution networks are promising candidates for future applications due to their rapid advancement in power electronics technology.They use interface converters(IFCs)to link DC and AC distribution netw...Hybrid AC/DC distribution networks are promising candidates for future applications due to their rapid advancement in power electronics technology.They use interface converters(IFCs)to link DC and AC distribution networks.However,the networks possess drawbacks with AC voltage and frequency offsets when transferring from grid-tied to islanding modes.To address these problems,this paper proposes a simple but effective strategy based on the reverse droop method.Initially,the power balance equation of the distribution system is derived,which reveals that the cause of voltage and frequency offsets is the mismatch between the IFC output power and the rated load power.Then,the reverse droop control is introduced into the IFC controller.By using a voltage-active power/frequency-reactive power(U-P/f-Q)reverse droop loop,the IFC output power enables adaptive tracking of the rated load power.Therefore,the AC voltage offset and frequency offset are suppressed during the transfer process of operational modes.In addition,the universal parameter design method is discussed based on the stability limitations of the control system and the voltage quality requirements of AC critical loads.Finally,simulation and experimental results clearly validate the proposed control strategy and parameter design method.展开更多
This paper proposes a continuous control set model predictive control(CCS-MPC)algorithm of a modular multilevel matrix converter(M3C)for low-frequency AC transmission(LFAC),via which the offshore wind farm(OWF)is inte...This paper proposes a continuous control set model predictive control(CCS-MPC)algorithm of a modular multilevel matrix converter(M3C)for low-frequency AC transmission(LFAC),via which the offshore wind farm(OWF)is integrated.The M3C is operated with a 16.7 Hz frequency at the OWF side and a 50 Hz frequency at the onshore grid side.The balance of the capacitor voltages and the regulation of circulating currents in the M3C are performed using the proposed CCSMPC algorithm,which is based on the online solution of a cost function with constraints.Simulation and experimental work(with a 5 kW M3C prototype)are provided,showing the performance of the LFAC system to operate with symmetrical and asymmetrical voltage dips,active and reactive power steps,and optimal limitation of currents and voltages using constraints.Unlike previous publications,the predictive control system in this paper allows seamless operation under balanced and unbalanced conditions,for instance,during asymmetrical voltage dips.展开更多
In modern microgrids(MGs)with high penetration of distributed energy resources(DERs),system reconfiguration occurs more frequently and becomes a significant issue.Fixedparameter controllers may not handle these tasks ...In modern microgrids(MGs)with high penetration of distributed energy resources(DERs),system reconfiguration occurs more frequently and becomes a significant issue.Fixedparameter controllers may not handle these tasks effectively,as they lack the ability to adapt to the dynamic conditions in such environments.This paper proposes an intelligence-driven gridforming(GFM)converter control method for islanding MGs us ing a robustness-guided neural network(RNN).To enhance the adaptability of the proposed method,traditional proportional-in tegral controllers in the GFM primary control loops are entire ly replaced by the RNN.The RNN is trained by a robustnessguided strategy to replicate their robust behaviors.All the train ing stages are purely data-driven methods,which means that no system parameters are required for the controller design.Conse quently,the proposed method is an intelligence-driven modelless GFM converter control.Compared with traditional meth ods,the simulation results in all testing scenarios show the clear benefits of the proposed method.The proposed method reduces overshoots by more than 71.24%,which keeps all damping ra tios within the stable region and provides faster stabilization.In comparison to traditional methods,at the highest probability,the proposed method improves damping by over 14.7%and re duces the rates of change of frequency and voltage by over 59.97%.Additionally,the proposed method effectively suppress es the interactions between state variables caused by inverterbased resources,with frequencies ranging from 1.0 Hz to 1.422 Hz.Consequently,these frequencies contribute less than 19.79%to the observed transient responses.展开更多
Recently,electric railways have experienced a rapid development causing an increasing power demand.Due to the flexible installation available at trackside land along railways,photovoltaic(PV)generation is suggested as...Recently,electric railways have experienced a rapid development causing an increasing power demand.Due to the flexible installation available at trackside land along railways,photovoltaic(PV)generation is suggested as an extension to the traction power supply system(TPSS)in railways.First,this paper proposes a three-phase integrated configuration for PV generation connected to a two-phase traction network and the on-site consumption of solar resources alongside railways.In this configuration,another inverse V/V transformer is used to maintain a balanced three-phase low voltage(LV)AC bus from a two-phase traction network.It is more convenient for accessing PV generation units.Then,in order to mitigate the negative sequence currents caused by electric trains,an individual phase current(IPC)control strategy for PV converters is developed for power quality improvement.It can not only supply the locomotive with asymmetrical currents,but also provide feedback to the grid through symmetrical currents.All the implementation and calculations are conducted in the three-phase stationary reference frame without any sequence extracting and power compensations.Finally,simulation results are presented to validate the effectiveness of the proposed IPC control strategy.展开更多
The emerging medium voltage direct current(MVDC)distribution networks are becoming more attractive due to their flexible power flow control and lower losses compared to traditional AC networks.This will significantly ...The emerging medium voltage direct current(MVDC)distribution networks are becoming more attractive due to their flexible power flow control and lower losses compared to traditional AC networks.This will significantly increase the wide uptake of renewable energy sources.The optimum utilization of the existing assets is an important aspect in grid upgrading and planning.One feasible option is to convert existing MVAC lines into MVDC operation.One of the practical demonstrations is the“ANGLE-DC”project which is also the first MVDC link in the UK.This paper highlights the innovative approach,challenges and key benefits delivered by the ANGLE-DC project.展开更多
基金This work has been funded by the Helmholtz Alliance ROBEX–Robotic Exploration of Extreme Environments.The authors would also like to thank the National Science Foundation(NSF)and specifically the Energy,Power,Control and Networks(EPCN)program for their valuable ongoing support in this research within the framework of grant ECCS-1809182‘Collaborative Research:Design and Control of Networked Offshore Hydrokinetic Power-Plants with Energy Storage’.
文摘Economic factors along with legislation and policies to counter harmful pollution apply specifically to maritime drive research for improved power generation and energy storage.Proton exchange membrane fuel cells are considered among the most promising options for marine applications.Switching converters are the most common interfaces between fuel cells and all types of load in order to provide a stable regulated voltage.In this paper,a method using artificial neural networks(ANNs)is developed to control the dynamics and response of a fuel cell connected with a DC boost converter.Its capability to adapt to different loading conditions is established.Furthermore,a cycle-mean,black-box model for the switching device is also proposed.The model is centred about an ANN,too,and can achieve considerably faster simulation times making it much more suitable for power management applications.
文摘This paper presents detailed design steps of an effective control system aiming to increase the solar energy harvested via photovoltaic power-generation systems.The design of an intelligent maximum power point tracker(MPPT)supported by a robust sliding-mode(SM)controller is discussed in this study.The proposed control scheme is designed to track the MPP and provide a smooth system response by removing the overshoot in the load current during any variation in the connected load.Such a system is suitable for DC-DC buck converter applications.The study begins with modelling the buck converter for a continuous current mode operation.The reference voltage of the tracking system is produced by the proposed neural network(NN)algorithm.The proposed intelligent MPPT integrated with an SM controller is simulated in a MATLAB®/Simulink®platform.The simulation results are analysed to investigate and confirm the satisfaction level of the adopted four-serially connected PV-modules system.The system performance is evaluated at a light intensity of 500 W/m^(2) and an ambient temperature of 25°C.Applying only the proposed NN algorithm guarantees the MPP tracking response by delivering 100 W at a resistive load of 13Ω,and 200 W at a load of 6.5Ω,respectively,with 99.77%system efficiency.However,this simultaneously demonstrates a current spike of~0.5 A when the load is varied from 50%to 100%.The integrated SM controller demonstrates a robust and smooth response,eliminating the existing current spike.
文摘In a translucent network scenario, development of an optical control plane (OCP) that is aware of the location and number of available regenerators and all-optical wavelength converters (AOWCs) is of paramount importance. However, current generalized multiprotocol label switching (GMPLS) protocol suite does not consider the distribution of regenerator and AOWC availability information to all the network nodes. In this paper, we propose a novel optical control plane (OCP) architecture that 1) disseminates information about network components (i.e. regenerators and AOWCs) to all the network nodes, and 2) evaluates candidate routes which use fewest amounts of network components. Performance of the proposed OCP is compared with a recently proposed hybrid OCP approach in terms of blocking performance, number of deployed components and lightpath establishment setup times. The obtained simulation results show that the proposed OCP approach demonstrates low connection blocking and establishes lightpaths by 1) minimizing the overall network cost owing to the deployment of minimum total number of network components, and 2) demonstrating acceptable lightpath establishment setup times at all traffic loads. Further, the proposed OCP methodology is compatible and suitable for controlling the operations of a novel electro-optical hybrid translucent node which is a latency efficient technology capable of delivering a cost effective implementation suitable for large scale deployment.
基金This work was supported by the National Key R&D Program of China(2018YFB0904700).
文摘Hybrid AC/DC distribution networks are promising candidates for future applications due to their rapid advancement in power electronics technology.They use interface converters(IFCs)to link DC and AC distribution networks.However,the networks possess drawbacks with AC voltage and frequency offsets when transferring from grid-tied to islanding modes.To address these problems,this paper proposes a simple but effective strategy based on the reverse droop method.Initially,the power balance equation of the distribution system is derived,which reveals that the cause of voltage and frequency offsets is the mismatch between the IFC output power and the rated load power.Then,the reverse droop control is introduced into the IFC controller.By using a voltage-active power/frequency-reactive power(U-P/f-Q)reverse droop loop,the IFC output power enables adaptive tracking of the rated load power.Therefore,the AC voltage offset and frequency offset are suppressed during the transfer process of operational modes.In addition,the universal parameter design method is discussed based on the stability limitations of the control system and the voltage quality requirements of AC critical loads.Finally,simulation and experimental results clearly validate the proposed control strategy and parameter design method.
基金supported by ANID BECAS/DOCTORADO NACIONAL 21230608supported by the Projects Fondecyt Nr.1221392,Anillo grant ATE230035,and Basal project FB0008(AC3E)supported by Fondecyt Nr.1230596 and Fondequip EQM200234.
文摘This paper proposes a continuous control set model predictive control(CCS-MPC)algorithm of a modular multilevel matrix converter(M3C)for low-frequency AC transmission(LFAC),via which the offshore wind farm(OWF)is integrated.The M3C is operated with a 16.7 Hz frequency at the OWF side and a 50 Hz frequency at the onshore grid side.The balance of the capacitor voltages and the regulation of circulating currents in the M3C are performed using the proposed CCSMPC algorithm,which is based on the online solution of a cost function with constraints.Simulation and experimental work(with a 5 kW M3C prototype)are provided,showing the performance of the LFAC system to operate with symmetrical and asymmetrical voltage dips,active and reactive power steps,and optimal limitation of currents and voltages using constraints.Unlike previous publications,the predictive control system in this paper allows seamless operation under balanced and unbalanced conditions,for instance,during asymmetrical voltage dips.
基金supported by King Mongkut’s Institute of Technology Ladkrabang,Thailand(No.2567-02-01-065)。
文摘In modern microgrids(MGs)with high penetration of distributed energy resources(DERs),system reconfiguration occurs more frequently and becomes a significant issue.Fixedparameter controllers may not handle these tasks effectively,as they lack the ability to adapt to the dynamic conditions in such environments.This paper proposes an intelligence-driven gridforming(GFM)converter control method for islanding MGs us ing a robustness-guided neural network(RNN).To enhance the adaptability of the proposed method,traditional proportional-in tegral controllers in the GFM primary control loops are entire ly replaced by the RNN.The RNN is trained by a robustnessguided strategy to replicate their robust behaviors.All the train ing stages are purely data-driven methods,which means that no system parameters are required for the controller design.Conse quently,the proposed method is an intelligence-driven modelless GFM converter control.Compared with traditional meth ods,the simulation results in all testing scenarios show the clear benefits of the proposed method.The proposed method reduces overshoots by more than 71.24%,which keeps all damping ra tios within the stable region and provides faster stabilization.In comparison to traditional methods,at the highest probability,the proposed method improves damping by over 14.7%and re duces the rates of change of frequency and voltage by over 59.97%.Additionally,the proposed method effectively suppress es the interactions between state variables caused by inverterbased resources,with frequencies ranging from 1.0 Hz to 1.422 Hz.Consequently,these frequencies contribute less than 19.79%to the observed transient responses.
基金supported in part by the National Natural Science Foundation of China(51807182)。
文摘Recently,electric railways have experienced a rapid development causing an increasing power demand.Due to the flexible installation available at trackside land along railways,photovoltaic(PV)generation is suggested as an extension to the traction power supply system(TPSS)in railways.First,this paper proposes a three-phase integrated configuration for PV generation connected to a two-phase traction network and the on-site consumption of solar resources alongside railways.In this configuration,another inverse V/V transformer is used to maintain a balanced three-phase low voltage(LV)AC bus from a two-phase traction network.It is more convenient for accessing PV generation units.Then,in order to mitigate the negative sequence currents caused by electric trains,an individual phase current(IPC)control strategy for PV converters is developed for power quality improvement.It can not only supply the locomotive with asymmetrical currents,but also provide feedback to the grid through symmetrical currents.All the implementation and calculations are conducted in the three-phase stationary reference frame without any sequence extracting and power compensations.Finally,simulation results are presented to validate the effectiveness of the proposed IPC control strategy.
基金ANGLE-DC,The Office of Gas and Electricity Markets(Ofgem)of UK Government funded Network Innovation Competition(NIC)project.
文摘The emerging medium voltage direct current(MVDC)distribution networks are becoming more attractive due to their flexible power flow control and lower losses compared to traditional AC networks.This will significantly increase the wide uptake of renewable energy sources.The optimum utilization of the existing assets is an important aspect in grid upgrading and planning.One feasible option is to convert existing MVAC lines into MVDC operation.One of the practical demonstrations is the“ANGLE-DC”project which is also the first MVDC link in the UK.This paper highlights the innovative approach,challenges and key benefits delivered by the ANGLE-DC project.
