Distributed photovoltaic(PV)is one of the important power sources for building a new power system with new energy as the main body.The rapid development of distributed PV has brought new challenges to the operation of...Distributed photovoltaic(PV)is one of the important power sources for building a new power system with new energy as the main body.The rapid development of distributed PV has brought new challenges to the operation of distribution networks.In order to improve the absorption ability of large-scale distributed PV access to the distribution network,the AC/DC hybrid distribution network is constructed based on flexible interconnection technology,and a coordinated scheduling strategy model of hydrogen energy storage(HS)and distributed PV is established.Firstly,the mathematical model of distributed PV and HS system is established,and a comprehensive energy storage system combining seasonal hydrogen energy storage(SHS)and battery(BT)is proposed.Then,a flexible interconnected distribution network scheduling optimization model is established to minimize the total active power loss,voltage deviation and system operating cost.Finally,simulation analysis is carried out on the improved IEEE33 node,the NSGA-II algorithm is used to solve specific examples,and the optimal scheduling results of the comprehensive economy and power quality of the distribution network are obtained.Compared with the method that does not consider HS and flexible interconnection technology,the network loss and voltage deviation of this method are lower,and the total system cost can be reduced by 3.55%,which verifies the effectiveness of the proposed method.展开更多
There is instability in the distributed energy storage cloud group end region on the power grid side.In order to avoid large-scale fluctuating charging and discharging in the power grid environment and make the capaci...There is instability in the distributed energy storage cloud group end region on the power grid side.In order to avoid large-scale fluctuating charging and discharging in the power grid environment and make the capacitor components showa continuous and stable charging and discharging state,a hierarchical time-sharing configuration algorithm of distributed energy storage cloud group end region on the power grid side based on multi-scale and multi feature convolution neural network is proposed.Firstly,a voltage stability analysis model based onmulti-scale and multi feature convolution neural network is constructed,and the multi-scale and multi feature convolution neural network is optimized based on Self-OrganizingMaps(SOM)algorithm to analyze the voltage stability of the cloud group end region of distributed energy storage on the grid side under the framework of credibility.According to the optimal scheduling objectives and network size,the distributed robust optimal configuration control model is solved under the framework of coordinated optimal scheduling at multiple time scales;Finally,the time series characteristics of regional power grid load and distributed generation are analyzed.According to the regional hierarchical time-sharing configuration model of“cloud”,“group”and“end”layer,the grid side distributed energy storage cloud group end regional hierarchical time-sharing configuration algorithm is realized.The experimental results show that after applying this algorithm,the best grid side distributed energy storage configuration scheme can be determined,and the stability of grid side distributed energy storage cloud group end region layered timesharing configuration can be improved.展开更多
The increasing proportion of distributed photovoltaics(DPVs)and electric vehicle charging stations in low-voltage distribution networks(LVDNs)has resulted in challenges such as distribution transformer overloads and v...The increasing proportion of distributed photovoltaics(DPVs)and electric vehicle charging stations in low-voltage distribution networks(LVDNs)has resulted in challenges such as distribution transformer overloads and voltage violations.To address these problems,we propose a coordinated planning method for flexible interconnections and energy storage systems(ESSs)to improve the accommodation capacity of DPVs.First,the power-transfer characteristics of flexible interconnection and ESSs are analyzed.The equipment costs of the voltage source converters(VSCs)and ESSs are also analyzed comprehensively,considering the differences in installation and maintenance costs for different installation locations.Second,a bilevel programming model is established to minimize the annual comprehensive cost and yearly total PV curtailment capacity.Within this framework,the upper-level model optimizes the installation locations and capacities of the VSCs and ESSs,whereas the lower-level model optimizes the operating power of the VSCs and ESSs.The proposed model is solved using a non-dominated sorting genetic algorithm with an elite strategy(NSGA-II).The effectiveness of the proposed planning method is validated through an actual LVDN scenario,which demonstrates its advantages in enhancing PV accommodation capacity.In addition,the economic benefits of various planning schemes with different flexible interconnection topologies and different PV grid-connected forms are quantitatively analyzed,demonstrating the adaptability of the proposed coordinated planning method.展开更多
Erasure code is widely used as the redundancy scheme in distributed storage system. When a storage node fails, the repair process often requires to transfer a large amount of data. Regenerating code and hierarchical c...Erasure code is widely used as the redundancy scheme in distributed storage system. When a storage node fails, the repair process often requires to transfer a large amount of data. Regenerating code and hierarchical code are two classes of codes proposed to reduce the repair bandwidth cost. Regenerating codes reduce the amount of data transferred by each helping node, while hierarchical codes reduce the number of nodes participating in the repair process. In this paper, we propose a "sub-code nesting framework" to combine them together. The resulting regenerating hierarchical code has low repair degree as hierarchical code and lower repair cost than hierarchical code. Our code can achieve exact regeneration of the failed node, and has the additional property of low updating complexity.展开更多
Energy storage (ES) is a form of media that store one form of energy to be utilized at another time. Importance of ES is comprehended while intermittent nature of renewable energy (RE) generation increases and integra...Energy storage (ES) is a form of media that store one form of energy to be utilized at another time. Importance of ES is comprehended while intermittent nature of renewable energy (RE) generation increases and integration into the grid becomes viable in terms of economics and environment. However, technical analysis should be carried out before large scale integration into the grid. Some utilities experienced in Europe and expressed concern about issues in integrating large scale renewable energy in the areas of harmonics, voltage regulation, network protection and islanding. In Australia, distribution network (DN) is not robust compared to the European grid;moreover loads are largely distributed over large geographical areas. Installation of RE such as roof top solar photovoltaic (PV) is increasing in Australia which also boosted by the governments incentives to the individual owners. It is therefore obvious that large scale PV integration into the Australian grid is imminent. The intermittent characteristic of solar PV is expected to have greater impacts on DN in Australia compared to the DN in Europe. Therefore this paper investigated the impacts of solar PV on low voltage (LV) DN where loads connected through distribution transformer (DT) and finally further investigation was conducted with the deployment of ES into the respective load centers. It was found that storage reduced the overall peak load condition on the DT, and also reduced the energy fluctuation in the DN. It was also found that storage improved the voltage regulation on the LV side of DT and stabilized node voltage.展开更多
As part of the ongoing information revolution,smart power grid technology has become a key focus area for research into power systems.Intelligent electrical appliances are now an important component of power systems,p...As part of the ongoing information revolution,smart power grid technology has become a key focus area for research into power systems.Intelligent electrical appliances are now an important component of power systems,providing a smart power grid with increased control,stability,and safety.Based on the secure communication requirements of cloud energy storage systems,this paper presents the design and development of a node controller for a cloud energy storage network.The function division and system deployment processes were carried out to ensure the security of the communication network used for the cloud energy storage system.Safety protection measures were proposed according to the demands of the communication network,allowing the system to run safely and stably.Finally,the effectiveness of the system was verified through a client-side distributed energy storage demonstration project in Suzhou,China.The system was observed to operate safely and stably,demonstrating good peak-clipping and valley filling effects,and improving the system load characteristics.展开更多
Integration of distributed energy storage(DES)is beneficial for mitigating voltage fluctuations in highly distributed generator(DG)-penetrated active distribution networks(ADNs).Based on an accurate physical model of ...Integration of distributed energy storage(DES)is beneficial for mitigating voltage fluctuations in highly distributed generator(DG)-penetrated active distribution networks(ADNs).Based on an accurate physical model of ADN,conventional model-based methods can realize optimal control of DES.However,absence of network parameters and complex operational states of ADN poses challenges to model-based methods.This paper proposes a data-driven predictive voltage control method for DES.First,considering time-series constraints,a data-driven predictive control model is formulated for DES by using measurement data.Then,a data-driven coordination method is proposed for DES and DGs in each area.Through boundary information interaction,voltage mitigation effects can be improved by interarea coordination control.Finally,control performance is tested on a modified IEEE 33-node test case.Case studies demonstrate that by fully utilizing multi-source data,the proposed predictive control method can effectively regulate DES and DGs to mitigate voltage violations.展开更多
With the implementation of China’s carbon-peaking and carbon-neutrality strategy,new energy will achieve leapfrog growth.Due to the good economics of distributed new-energy generation,it can not only save users’own ...With the implementation of China’s carbon-peaking and carbon-neutrality strategy,new energy will achieve leapfrog growth.Due to the good economics of distributed new-energy generation,it can not only save users’own investment,but also help to achieve local consumption of new energy.However,it will also bring about a series of incremental costs to the power grid.This paper first enumerates the concept,development status and scheduling mode of a distributed new-energy storage system.Based on the above,it establishes a new-energy power generation model and an energy storage system charging and discharging model,and proposes a global optimization scheduling model for a distributed new-energy storage system,considering the time-of-use electricity price and taking the lowest total operating cost of the distributed new-energy power generation system as the objective function.Finally,it proposes a distribution network incremental cost analysis model based on the penetration of distributed new energy.The calculation results show that the incremental cost of grid-connected distributed new energy is 1.0849,1.2585 and 1.3473 yuan/kWh,respectively,which indicates that the global dispatching model can optimize the power consumption structure of a distributed power generation system,and has the function of peak shaving and valley filling,but the incremental cost of the distribution network will also increase.展开更多
Distributed photovoltaic generators(DPGs) have been integrated into the medium/low voltage distribution network widely. Due to the randomness and fluctuation of DPG, however, the distribution and direction of power fl...Distributed photovoltaic generators(DPGs) have been integrated into the medium/low voltage distribution network widely. Due to the randomness and fluctuation of DPG, however, the distribution and direction of power flow changed frequently some days. Therefore, more attention is needed to ensure the safe operation of the distribution network. The installation of energy storage systems(ESSs) can help the network withstand thefluctuations caused by DPG. Based on the discrete Fourier transform method, this paper presents an ESS capacity allocation strategy for the medium/low voltage distribution network with DPG. The reliability scenario models are created via Latin hypercube sampling with Cholesky decomposition and scenario reduction. Numerical results show that the proposed strategy can reduce the power flow fluctuation with less ESS capacity, and increase the penetration capacity of DPG in the distribution network while maintaining the quality of the power supply.展开更多
Distribution networks are commonly used to demonstrate low-voltage problems.A new method to improve voltage quality is using battery energy storage stations(BESSs),which has a four-quadrant regulating capacity.In this...Distribution networks are commonly used to demonstrate low-voltage problems.A new method to improve voltage quality is using battery energy storage stations(BESSs),which has a four-quadrant regulating capacity.In this paper,an optimal dispatching model of a distributed BESS considering peak load shifting is proposed to improve the voltage distribution in a distribution network.The objective function is to minimize the power exchange cost between the distribution network and the transmission network and the penalty cost of the voltage deviation.In the process,various constraints are considered,including the node power balance,single/two-way power flow,peak load shifting,line capacity,voltage deviation,photovoltaic station operation,main transformer capacity,and power factor of the distribution network.The big M method is used to linearize the nonlinear variables in the objective function and constraints,and the model is transformed into a mixed-integer linear programming problem,which significantly improves the model accuracy.Simulations are performed using the modified IEEE 33-node system.A typical time period is selected to analyze the node voltage variation,and the results show that the maximum voltage deviation can be reduced from 14.06%to 4.54%.The maximum peak-valley difference of the system can be reduced from 8.83 to 4.23 MW,and the voltage qualification rate can be significantly improved.Moreover,the validity of the proposed model is verified through simulations.展开更多
An economic and environmental evaluation of active distribution networks containing lithium ion batteries(Li-ion),sodium sulfur batteries(NaS)and vanadium redox flow batteries(VRB)was carried out using the EnergyPLAN ...An economic and environmental evaluation of active distribution networks containing lithium ion batteries(Li-ion),sodium sulfur batteries(NaS)and vanadium redox flow batteries(VRB)was carried out using the EnergyPLAN software.The prioritization schemes of the combination of energy storage systems and intermittent energy systems were studied technically and economically based on some specific situations of the grid integrated with wind power.The results suggest that the technical and economic optimal intermittent energy-storage capacity ratio was 2:1 in predetermined energy system scenarios.Liion batteries storage system performed the best in critical excess electricity production(CEEP)absorption,energy saving and emission reduction while NaS batteries storage system was the most competitive among the three due to its cheaper costs.展开更多
Increasing amounts of distributed generation(DG)connected to distribution networks may lead to the violation of voltage and thermal limits.This paper proposes a virtual energy storage system(VESS)to provide voltage co...Increasing amounts of distributed generation(DG)connected to distribution networks may lead to the violation of voltage and thermal limits.This paper proposes a virtual energy storage system(VESS)to provide voltage control in distribution networks in order to accommodate more DG.A VESS control scheme coordinating the demand response and the energy storage system was developed.The demand response control measures the voltage of the connected bus and changes the power consumption of the demand to eliminate voltage violations.The response of energy storage systems was used to compensate for the uncertainty of demand response.The voltage control of the energy storage system is a droop control with droop gain values determined by applying voltage sensitivity factors.The control strategy of the VESS was applied to a medium-voltage network and the results show that the control of the VESS not only facilitates the accommodation of higher DG capacity in the distribution network without voltage violations or network reinforcements but also prolongs the lifetime of the transformer’s on-load tap changer.展开更多
Energy storage systems (ESSs) are acknowledged to be a promising option to cope with issues in high penetration of renewable energy and guarantee a highly reliable power supply. In this paper, a two-step optimal alloc...Energy storage systems (ESSs) are acknowledged to be a promising option to cope with issues in high penetration of renewable energy and guarantee a highly reliable power supply. In this paper, a two-step optimal allocation model is proposed to obtain the optimal allocation (location and size) of stationary ESSs (SESSs) and mobile ESSs (MESSs) in the resilient distribution networks (DNs). In the first step, a mixed-integer linear programming (MILP) problem is formulated to obtain the preselected location of ESSs with consideration of different scenarios under normal operation conditions. In the second step, a two-stage robust optimization model is established to get the optimal allocation results of ESSs under failure operation conditions which are solved by column-and-constraint generation (C&CG) algorithm. A hybrid ESS allocation strategy based on the subjective and objective weight analysis is proposed to give the final allocation scheme of SESSs and MESSs. Finally, the proposed two-step optimal allocation model is demonstrated on a modified IEEE 33-bus system to show its effectiveness and merits.展开更多
In distributed storage systems,file access efficiency has an important impact on the real-time nature of information forensics.As a popular approach to improve file accessing efficiency,prefetching model can fetches d...In distributed storage systems,file access efficiency has an important impact on the real-time nature of information forensics.As a popular approach to improve file accessing efficiency,prefetching model can fetches data before it is needed according to the file access pattern,which can reduce the I/O waiting time and increase the system concurrency.However,prefetching model needs to mine the degree of association between files to ensure the accuracy of prefetching.In the massive small file situation,the sheer volume of files poses a challenge to the efficiency and accuracy of relevance mining.In this paper,we propose a massive files prefetching model based on LSTM neural network with cache transaction strategy to improve file access efficiency.Firstly,we propose a file clustering algorithm based on temporal locality and spatial locality to reduce the computational complexity.Secondly,we propose a definition of cache transaction according to files occurrence in cache instead of time-offset distance based methods to extract file block feature accurately.Lastly,we innovatively propose a file access prediction algorithm based on LSTM neural network which predict the file that have high possibility to be accessed.Experiments show that compared with the traditional LRU and the plain grouping methods,the proposed model notably increase the cache hit rate and effectively reduces the I/O wait time.展开更多
Remote data auditing becomes critical to ensure the storage reliability in distributed cloud storage.Recently,Le et al proposed an efficient private data auditing scheme NC-Audit designed for regenerating codes,which ...Remote data auditing becomes critical to ensure the storage reliability in distributed cloud storage.Recently,Le et al proposed an efficient private data auditing scheme NC-Audit designed for regenerating codes,which claimed that NC-Audit can effectively realize privacy-preserving data auditing for distributed storage systems.However,our analysis shows that NC-Audit is not secure for that the adversarial cloud can forge some illegal blocks to cheat the auditor successfully with a high probability even without storing the user’s whole data,when the coding field is large enough.展开更多
The upscaling requirements of energy transition highlight the urgent need for ramping up renewables and boosting system efficiencies.However,the stochastic nature of excessive renewable energy resources has challenged...The upscaling requirements of energy transition highlight the urgent need for ramping up renewables and boosting system efficiencies.However,the stochastic nature of excessive renewable energy resources has challenged stable and efficient operation of the power system.Battery energy storage systems(BESSs)have been identified as critical to mitigate random fluctuations,unnecessary green energy curtailment and load shedding with rapid response and flexible connection.On the other hand,an AC/DC hybrid distribution system can offer merged benefits in both AC and DC subsystems without additional losses during AC/DC power conversion.Therefore,configuring BESSs on an AC/DC distribution system is wellpositioned to meet challenges brought by carbon reductions in an efficient way.A bi-level optimization model of BESS capacity allocation for AC/DC hybrid distribution systems,considering the flexibility of voltage source converters(VSCs)and power conversion systems(PCSs),has been established in this paper to address the techno-economic issues that hindered wide implementation.The large-scale nonlinear programming problem has been solved utilizing a genetic algorithm combined with second-order cone programming.Rationality and effectiveness of the model have been verified by setting different scenarios through case studies.Simulation results have demonstrated the coordinated operation of BESS and AC/DC hybrid systems can effectively suppress voltage fluctuations and improve the cost-benefit of BESSs from a life cycle angle.展开更多
Battery energy storage systems(BESSs)are expected to play a crucial role in the operation and control of active distribution networks(ADNs).In this paper,a holistic state estimation framework is developed for ADNs wit...Battery energy storage systems(BESSs)are expected to play a crucial role in the operation and control of active distribution networks(ADNs).In this paper,a holistic state estimation framework is developed for ADNs with BESSs integrated.A dynamic equivalent model of BESS is developed,and the state transition and measurement equations are derived.Based on the equivalence between the correction stage of the iterated extended Kalman filter(IEKF)and the weighted least squares(WLS)regression,a holistic state estimation framework is proposed to capture the static state variables of ADNs and the dynamic state variables of BESSs,especially the state of charge(SOC).A bad data processing method is also presented.The simulation results show that the proposed holistic state estimation framework improves the accuracy of state estimation as well as the capability of bad data detection for both ADNs and BESSs,providing comprehensive situational awareness for the whole system.展开更多
Vehicular Ad hoc Networks(VANETs)become a very crucial addition in the Intelligent Transportation System(ITS).It is challenging for a VANET system to provide security services and parallelly maintain high throughput b...Vehicular Ad hoc Networks(VANETs)become a very crucial addition in the Intelligent Transportation System(ITS).It is challenging for a VANET system to provide security services and parallelly maintain high throughput by utilizing limited resources.To overcome these challenges,we propose a blockchain-based Secured Cluster-based MAC(SCB-MAC)protocol.The nearby vehicles heading towards the same direction will form a cluster and each of the clusters has its blockchain to store and distribute the safety messages.The message which contains emergency information and requires Strict Delay Requirement(SDR)for transmission are called safety messages(SM).Cluster Members(CMs)sign SMs with their private keys while sending them to the blockchain to confirm authentication,integrity,and confidentiality of the message.A Certificate Authority(CA)is responsible for physical verification,key generation,and privacy preservation of the vehicles.We implemented a test scenario as proof of concept and tested the safety message transmission(SMT)protocol in a real-world platform.Computational and storage overhead analysis shows that the proposed protocol for SMT implements security,authentication,integrity,robustness,non-repudiation,etc.while maintaining the SDR.Messages that are less important compared to the SMs are called non-safety messages(NSM)and vehicles use RTS/CTS mechanism for NSM transmission.Numerical studies show that the proposed NSM transmission method maintains 6 times more throughput,2 times less delay and 125%less Packet Dropping Rate(PDR)than traditional MAC protocols.These results prove that the proposed protocol outperforms the traditional MAC protocols.展开更多
文摘Distributed photovoltaic(PV)is one of the important power sources for building a new power system with new energy as the main body.The rapid development of distributed PV has brought new challenges to the operation of distribution networks.In order to improve the absorption ability of large-scale distributed PV access to the distribution network,the AC/DC hybrid distribution network is constructed based on flexible interconnection technology,and a coordinated scheduling strategy model of hydrogen energy storage(HS)and distributed PV is established.Firstly,the mathematical model of distributed PV and HS system is established,and a comprehensive energy storage system combining seasonal hydrogen energy storage(SHS)and battery(BT)is proposed.Then,a flexible interconnected distribution network scheduling optimization model is established to minimize the total active power loss,voltage deviation and system operating cost.Finally,simulation analysis is carried out on the improved IEEE33 node,the NSGA-II algorithm is used to solve specific examples,and the optimal scheduling results of the comprehensive economy and power quality of the distribution network are obtained.Compared with the method that does not consider HS and flexible interconnection technology,the network loss and voltage deviation of this method are lower,and the total system cost can be reduced by 3.55%,which verifies the effectiveness of the proposed method.
基金supported by State Grid Corporation Limited Science and Technology Project Funding(Contract No.SGCQSQ00YJJS2200380).
文摘There is instability in the distributed energy storage cloud group end region on the power grid side.In order to avoid large-scale fluctuating charging and discharging in the power grid environment and make the capacitor components showa continuous and stable charging and discharging state,a hierarchical time-sharing configuration algorithm of distributed energy storage cloud group end region on the power grid side based on multi-scale and multi feature convolution neural network is proposed.Firstly,a voltage stability analysis model based onmulti-scale and multi feature convolution neural network is constructed,and the multi-scale and multi feature convolution neural network is optimized based on Self-OrganizingMaps(SOM)algorithm to analyze the voltage stability of the cloud group end region of distributed energy storage on the grid side under the framework of credibility.According to the optimal scheduling objectives and network size,the distributed robust optimal configuration control model is solved under the framework of coordinated optimal scheduling at multiple time scales;Finally,the time series characteristics of regional power grid load and distributed generation are analyzed.According to the regional hierarchical time-sharing configuration model of“cloud”,“group”and“end”layer,the grid side distributed energy storage cloud group end regional hierarchical time-sharing configuration algorithm is realized.The experimental results show that after applying this algorithm,the best grid side distributed energy storage configuration scheme can be determined,and the stability of grid side distributed energy storage cloud group end region layered timesharing configuration can be improved.
基金supported by the Science and Technology Support Program of Guizhou Province([2022]General 012)the Key Science and Technology Project of China Southern Power Grid Corporation(GZKJXM20220043)。
文摘The increasing proportion of distributed photovoltaics(DPVs)and electric vehicle charging stations in low-voltage distribution networks(LVDNs)has resulted in challenges such as distribution transformer overloads and voltage violations.To address these problems,we propose a coordinated planning method for flexible interconnections and energy storage systems(ESSs)to improve the accommodation capacity of DPVs.First,the power-transfer characteristics of flexible interconnection and ESSs are analyzed.The equipment costs of the voltage source converters(VSCs)and ESSs are also analyzed comprehensively,considering the differences in installation and maintenance costs for different installation locations.Second,a bilevel programming model is established to minimize the annual comprehensive cost and yearly total PV curtailment capacity.Within this framework,the upper-level model optimizes the installation locations and capacities of the VSCs and ESSs,whereas the lower-level model optimizes the operating power of the VSCs and ESSs.The proposed model is solved using a non-dominated sorting genetic algorithm with an elite strategy(NSGA-II).The effectiveness of the proposed planning method is validated through an actual LVDN scenario,which demonstrates its advantages in enhancing PV accommodation capacity.In addition,the economic benefits of various planning schemes with different flexible interconnection topologies and different PV grid-connected forms are quantitatively analyzed,demonstrating the adaptability of the proposed coordinated planning method.
基金Supported by 973 Project of China (No. 2012CB315803)Research Fund for the Doctoral Program of Higher Education of China (No. 20100002110033)Open research Fund of National Mobile Communications Research Laboratory, Southeast University (No. 2011D11)
文摘Erasure code is widely used as the redundancy scheme in distributed storage system. When a storage node fails, the repair process often requires to transfer a large amount of data. Regenerating code and hierarchical code are two classes of codes proposed to reduce the repair bandwidth cost. Regenerating codes reduce the amount of data transferred by each helping node, while hierarchical codes reduce the number of nodes participating in the repair process. In this paper, we propose a "sub-code nesting framework" to combine them together. The resulting regenerating hierarchical code has low repair degree as hierarchical code and lower repair cost than hierarchical code. Our code can achieve exact regeneration of the failed node, and has the additional property of low updating complexity.
文摘Energy storage (ES) is a form of media that store one form of energy to be utilized at another time. Importance of ES is comprehended while intermittent nature of renewable energy (RE) generation increases and integration into the grid becomes viable in terms of economics and environment. However, technical analysis should be carried out before large scale integration into the grid. Some utilities experienced in Europe and expressed concern about issues in integrating large scale renewable energy in the areas of harmonics, voltage regulation, network protection and islanding. In Australia, distribution network (DN) is not robust compared to the European grid;moreover loads are largely distributed over large geographical areas. Installation of RE such as roof top solar photovoltaic (PV) is increasing in Australia which also boosted by the governments incentives to the individual owners. It is therefore obvious that large scale PV integration into the Australian grid is imminent. The intermittent characteristic of solar PV is expected to have greater impacts on DN in Australia compared to the DN in Europe. Therefore this paper investigated the impacts of solar PV on low voltage (LV) DN where loads connected through distribution transformer (DT) and finally further investigation was conducted with the deployment of ES into the respective load centers. It was found that storage reduced the overall peak load condition on the DT, and also reduced the energy fluctuation in the DN. It was also found that storage improved the voltage regulation on the LV side of DT and stabilized node voltage.
基金supported by the Technical Project of the State Grid Corporation of China(research and demonstration application of key technology of energy storage cloud for mobile energy storage application of electric vehicles 5419-201971217a-0-0-00)。
文摘As part of the ongoing information revolution,smart power grid technology has become a key focus area for research into power systems.Intelligent electrical appliances are now an important component of power systems,providing a smart power grid with increased control,stability,and safety.Based on the secure communication requirements of cloud energy storage systems,this paper presents the design and development of a node controller for a cloud energy storage network.The function division and system deployment processes were carried out to ensure the security of the communication network used for the cloud energy storage system.Safety protection measures were proposed according to the demands of the communication network,allowing the system to run safely and stably.Finally,the effectiveness of the system was verified through a client-side distributed energy storage demonstration project in Suzhou,China.The system was observed to operate safely and stably,demonstrating good peak-clipping and valley filling effects,and improving the system load characteristics.
基金supported by the National Key R&D Program of China(2020YFB0906000,2020YFB0906001).
文摘Integration of distributed energy storage(DES)is beneficial for mitigating voltage fluctuations in highly distributed generator(DG)-penetrated active distribution networks(ADNs).Based on an accurate physical model of ADN,conventional model-based methods can realize optimal control of DES.However,absence of network parameters and complex operational states of ADN poses challenges to model-based methods.This paper proposes a data-driven predictive voltage control method for DES.First,considering time-series constraints,a data-driven predictive control model is formulated for DES by using measurement data.Then,a data-driven coordination method is proposed for DES and DGs in each area.Through boundary information interaction,voltage mitigation effects can be improved by interarea coordination control.Finally,control performance is tested on a modified IEEE 33-node test case.Case studies demonstrate that by fully utilizing multi-source data,the proposed predictive control method can effectively regulate DES and DGs to mitigate voltage violations.
基金supported by the Science and Technology Project of State Grid Xinjiang Electric Power Co.,Ltd.(Analysis model of the influence of multi-dimensional and different proportion penetration of new energy on the incremental cost of the system,SGXJ0000FCJS2310224).
文摘With the implementation of China’s carbon-peaking and carbon-neutrality strategy,new energy will achieve leapfrog growth.Due to the good economics of distributed new-energy generation,it can not only save users’own investment,but also help to achieve local consumption of new energy.However,it will also bring about a series of incremental costs to the power grid.This paper first enumerates the concept,development status and scheduling mode of a distributed new-energy storage system.Based on the above,it establishes a new-energy power generation model and an energy storage system charging and discharging model,and proposes a global optimization scheduling model for a distributed new-energy storage system,considering the time-of-use electricity price and taking the lowest total operating cost of the distributed new-energy power generation system as the objective function.Finally,it proposes a distribution network incremental cost analysis model based on the penetration of distributed new energy.The calculation results show that the incremental cost of grid-connected distributed new energy is 1.0849,1.2585 and 1.3473 yuan/kWh,respectively,which indicates that the global dispatching model can optimize the power consumption structure of a distributed power generation system,and has the function of peak shaving and valley filling,but the incremental cost of the distribution network will also increase.
基金supported by National Natural Science Foundation of China(No.51367004)National Basic Research Program of China(973 Program)(No.2013CB228205)
文摘Distributed photovoltaic generators(DPGs) have been integrated into the medium/low voltage distribution network widely. Due to the randomness and fluctuation of DPG, however, the distribution and direction of power flow changed frequently some days. Therefore, more attention is needed to ensure the safe operation of the distribution network. The installation of energy storage systems(ESSs) can help the network withstand thefluctuations caused by DPG. Based on the discrete Fourier transform method, this paper presents an ESS capacity allocation strategy for the medium/low voltage distribution network with DPG. The reliability scenario models are created via Latin hypercube sampling with Cholesky decomposition and scenario reduction. Numerical results show that the proposed strategy can reduce the power flow fluctuation with less ESS capacity, and increase the penetration capacity of DPG in the distribution network while maintaining the quality of the power supply.
基金This work was supported by the Science and Technology Project of State Grid Corporation of China“Intelligent Coordination Control and Energy Optimization Management of Super-large Scale Battery Energy Storage Power Station Based on Information Physics Fusion-Simulation Model and Transient Characteristics of Super-large Scale Battery Energy Storage Power Station”(No.DG71-18-009).
文摘Distribution networks are commonly used to demonstrate low-voltage problems.A new method to improve voltage quality is using battery energy storage stations(BESSs),which has a four-quadrant regulating capacity.In this paper,an optimal dispatching model of a distributed BESS considering peak load shifting is proposed to improve the voltage distribution in a distribution network.The objective function is to minimize the power exchange cost between the distribution network and the transmission network and the penalty cost of the voltage deviation.In the process,various constraints are considered,including the node power balance,single/two-way power flow,peak load shifting,line capacity,voltage deviation,photovoltaic station operation,main transformer capacity,and power factor of the distribution network.The big M method is used to linearize the nonlinear variables in the objective function and constraints,and the model is transformed into a mixed-integer linear programming problem,which significantly improves the model accuracy.Simulations are performed using the modified IEEE 33-node system.A typical time period is selected to analyze the node voltage variation,and the results show that the maximum voltage deviation can be reduced from 14.06%to 4.54%.The maximum peak-valley difference of the system can be reduced from 8.83 to 4.23 MW,and the voltage qualification rate can be significantly improved.Moreover,the validity of the proposed model is verified through simulations.
基金This work was supported by the National High Technology Research and Development Program of China(863 Program)(No.2012AA050212).
文摘An economic and environmental evaluation of active distribution networks containing lithium ion batteries(Li-ion),sodium sulfur batteries(NaS)and vanadium redox flow batteries(VRB)was carried out using the EnergyPLAN software.The prioritization schemes of the combination of energy storage systems and intermittent energy systems were studied technically and economically based on some specific situations of the grid integrated with wind power.The results suggest that the technical and economic optimal intermittent energy-storage capacity ratio was 2:1 in predetermined energy system scenarios.Liion batteries storage system performed the best in critical excess electricity production(CEEP)absorption,energy saving and emission reduction while NaS batteries storage system was the most competitive among the three due to its cheaper costs.
基金The work is supported in part by the Higher Committee for Education Development in Iraq(HCED)the RESTORES project under the grant(No.EP/L 014351/1)of the UK-EPSRC+1 种基金the JUICE project under the grant(No.EP/P003605/1)the P2P-SmarTest project under the grant of EU commission.
文摘Increasing amounts of distributed generation(DG)connected to distribution networks may lead to the violation of voltage and thermal limits.This paper proposes a virtual energy storage system(VESS)to provide voltage control in distribution networks in order to accommodate more DG.A VESS control scheme coordinating the demand response and the energy storage system was developed.The demand response control measures the voltage of the connected bus and changes the power consumption of the demand to eliminate voltage violations.The response of energy storage systems was used to compensate for the uncertainty of demand response.The voltage control of the energy storage system is a droop control with droop gain values determined by applying voltage sensitivity factors.The control strategy of the VESS was applied to a medium-voltage network and the results show that the control of the VESS not only facilitates the accommodation of higher DG capacity in the distribution network without voltage violations or network reinforcements but also prolongs the lifetime of the transformer’s on-load tap changer.
基金This work was supported by the Science and Technology Project of State Grid Corporation of China“Research on resilience technology and application foundation of intelligent distribution network based on integrated energy system”(No.52060019001H).
文摘Energy storage systems (ESSs) are acknowledged to be a promising option to cope with issues in high penetration of renewable energy and guarantee a highly reliable power supply. In this paper, a two-step optimal allocation model is proposed to obtain the optimal allocation (location and size) of stationary ESSs (SESSs) and mobile ESSs (MESSs) in the resilient distribution networks (DNs). In the first step, a mixed-integer linear programming (MILP) problem is formulated to obtain the preselected location of ESSs with consideration of different scenarios under normal operation conditions. In the second step, a two-stage robust optimization model is established to get the optimal allocation results of ESSs under failure operation conditions which are solved by column-and-constraint generation (C&CG) algorithm. A hybrid ESS allocation strategy based on the subjective and objective weight analysis is proposed to give the final allocation scheme of SESSs and MESSs. Finally, the proposed two-step optimal allocation model is demonstrated on a modified IEEE 33-bus system to show its effectiveness and merits.
基金This work is supported by‘The Fundamental Research Funds for the Central Universities(Grant No.HIT.NSRIF.201714)’‘Weihai Science and Technology Development Program(2016DXGJMS15)’‘Key Research and Development Program in Shandong Provincial(2017GGX90103)’.
文摘In distributed storage systems,file access efficiency has an important impact on the real-time nature of information forensics.As a popular approach to improve file accessing efficiency,prefetching model can fetches data before it is needed according to the file access pattern,which can reduce the I/O waiting time and increase the system concurrency.However,prefetching model needs to mine the degree of association between files to ensure the accuracy of prefetching.In the massive small file situation,the sheer volume of files poses a challenge to the efficiency and accuracy of relevance mining.In this paper,we propose a massive files prefetching model based on LSTM neural network with cache transaction strategy to improve file access efficiency.Firstly,we propose a file clustering algorithm based on temporal locality and spatial locality to reduce the computational complexity.Secondly,we propose a definition of cache transaction according to files occurrence in cache instead of time-offset distance based methods to extract file block feature accurately.Lastly,we innovatively propose a file access prediction algorithm based on LSTM neural network which predict the file that have high possibility to be accessed.Experiments show that compared with the traditional LRU and the plain grouping methods,the proposed model notably increase the cache hit rate and effectively reduces the I/O wait time.
基金Supported by the National Natural Science Foundation of China(61872088)the Science and Technology Plan Project of Xi’an(2020KJWL02,2017CGWL35)the China National Study Abroad Fund。
文摘Remote data auditing becomes critical to ensure the storage reliability in distributed cloud storage.Recently,Le et al proposed an efficient private data auditing scheme NC-Audit designed for regenerating codes,which claimed that NC-Audit can effectively realize privacy-preserving data auditing for distributed storage systems.However,our analysis shows that NC-Audit is not secure for that the adversarial cloud can forge some illegal blocks to cheat the auditor successfully with a high probability even without storing the user’s whole data,when the coding field is large enough.
基金supported in part by the National Natural Science Foundation of China(No.51777134)in part by a joint project of NSFC of China and EPSRC of UK(No.52061635103 and EP/T021969/1).
文摘The upscaling requirements of energy transition highlight the urgent need for ramping up renewables and boosting system efficiencies.However,the stochastic nature of excessive renewable energy resources has challenged stable and efficient operation of the power system.Battery energy storage systems(BESSs)have been identified as critical to mitigate random fluctuations,unnecessary green energy curtailment and load shedding with rapid response and flexible connection.On the other hand,an AC/DC hybrid distribution system can offer merged benefits in both AC and DC subsystems without additional losses during AC/DC power conversion.Therefore,configuring BESSs on an AC/DC distribution system is wellpositioned to meet challenges brought by carbon reductions in an efficient way.A bi-level optimization model of BESS capacity allocation for AC/DC hybrid distribution systems,considering the flexibility of voltage source converters(VSCs)and power conversion systems(PCSs),has been established in this paper to address the techno-economic issues that hindered wide implementation.The large-scale nonlinear programming problem has been solved utilizing a genetic algorithm combined with second-order cone programming.Rationality and effectiveness of the model have been verified by setting different scenarios through case studies.Simulation results have demonstrated the coordinated operation of BESS and AC/DC hybrid systems can effectively suppress voltage fluctuations and improve the cost-benefit of BESSs from a life cycle angle.
文摘Battery energy storage systems(BESSs)are expected to play a crucial role in the operation and control of active distribution networks(ADNs).In this paper,a holistic state estimation framework is developed for ADNs with BESSs integrated.A dynamic equivalent model of BESS is developed,and the state transition and measurement equations are derived.Based on the equivalence between the correction stage of the iterated extended Kalman filter(IEKF)and the weighted least squares(WLS)regression,a holistic state estimation framework is proposed to capture the static state variables of ADNs and the dynamic state variables of BESSs,especially the state of charge(SOC).A bad data processing method is also presented.The simulation results show that the proposed holistic state estimation framework improves the accuracy of state estimation as well as the capability of bad data detection for both ADNs and BESSs,providing comprehensive situational awareness for the whole system.
文摘Vehicular Ad hoc Networks(VANETs)become a very crucial addition in the Intelligent Transportation System(ITS).It is challenging for a VANET system to provide security services and parallelly maintain high throughput by utilizing limited resources.To overcome these challenges,we propose a blockchain-based Secured Cluster-based MAC(SCB-MAC)protocol.The nearby vehicles heading towards the same direction will form a cluster and each of the clusters has its blockchain to store and distribute the safety messages.The message which contains emergency information and requires Strict Delay Requirement(SDR)for transmission are called safety messages(SM).Cluster Members(CMs)sign SMs with their private keys while sending them to the blockchain to confirm authentication,integrity,and confidentiality of the message.A Certificate Authority(CA)is responsible for physical verification,key generation,and privacy preservation of the vehicles.We implemented a test scenario as proof of concept and tested the safety message transmission(SMT)protocol in a real-world platform.Computational and storage overhead analysis shows that the proposed protocol for SMT implements security,authentication,integrity,robustness,non-repudiation,etc.while maintaining the SDR.Messages that are less important compared to the SMs are called non-safety messages(NSM)and vehicles use RTS/CTS mechanism for NSM transmission.Numerical studies show that the proposed NSM transmission method maintains 6 times more throughput,2 times less delay and 125%less Packet Dropping Rate(PDR)than traditional MAC protocols.These results prove that the proposed protocol outperforms the traditional MAC protocols.