This study addresses the critical challenge of reconfiguration in unbalanced power distribution networks(UPDNs),focusing on the complex 123-Bus test system.Three scenarios are investigated:(1)simultaneous power loss r...This study addresses the critical challenge of reconfiguration in unbalanced power distribution networks(UPDNs),focusing on the complex 123-Bus test system.Three scenarios are investigated:(1)simultaneous power loss reduction and voltage profile improvement,(2)minimization of voltage and current unbalance indices under various operational cases,and(3)multi-objective optimization using Pareto front analysis to concurrently optimize voltage unbalance index,active power loss,and current unbalance index.Unlike previous research that oftensimplified system components,this work maintains all equipment,including capacitor banks,transformers,and voltage regulators,to ensure realistic results.The study evaluates twelve metaheuristic algorithms to solve the reconfiguration problem(RecPrb)in UPDNs.A comprehensive statistical analysis is conducted to identify the most efficient algorithm for solving the RecPrb in the 123-Bus UPDN,employing multiple performance metrics and comparative techniques.The Artificial Hummingbird Algorithm emerges as the top-performing algorithm and is subsequently applied to address a multi-objective optimization challenge in the 123-Bus UPDN.This research contributes valuable insights for network operators and researchers in selecting suitable algorithms for specific reconfiguration scenarios,advancing the field of UPDN optimization and management.展开更多
In order to quickly and accurately locate the fault location of the distribution network and increase the stability of the distribution network,a fault recovery method based on multi-objective optimization algorithm i...In order to quickly and accurately locate the fault location of the distribution network and increase the stability of the distribution network,a fault recovery method based on multi-objective optimization algorithm is proposed.The optimization of the power distribution network fault system based on multiagent technology realizes fast recovery of multi-objective fault,solve the problem of network learning and parameter adjustment in the later stage of particle swarm optimization algorithm falling into the local extreme value dilemma,and realize the multi-dimensional nonlinear optimization of the main grid and the auxiliary grid.The system proposed in this study takes power distribution network as the goal,applies fuzzy probability algorithm,simplifies the calculation process,avoids local extreme value,and finally realizes the energy balance between each power grid.Simulation results show that the Multi-Agent Technology enjoys priority in restoring important load,shortening the recovery time of power grid balance,and reducing the overall line loss rate of power grid.Therefore,the power grid fault self-healing system can improve the safety and stability of the important power grid,and reduce the economic loss rate of the whole power grid.展开更多
The models, methods and their application experiences of a practical GIS(geographic information system)-based computer decision-making support system of urban power distribution network planning with seven subsystems,...The models, methods and their application experiences of a practical GIS(geographic information system)-based computer decision-making support system of urban power distribution network planning with seven subsystems,termed CNP,are described.In each subsystem there is at least one or one set of practical mathematical methobs.Some new models and mathematical methods have been introduced.In the development of CNP the idea of cognitive system engineering has been insisted on,which claims that human and computer intelligence should be combined together to solve the complex engineering problems cooperatively.Practical applications have shown that not only the optimal plan can be automatically reached with many complicated factors considered, but also the computation,analysis and graphic drawing burden can be released considerably.展开更多
A new combined model is proposed to obtain predictive data value applied in state estimation for radial power distribution networks. The time delay part of the model is calculated by a recursive least squares algorith...A new combined model is proposed to obtain predictive data value applied in state estimation for radial power distribution networks. The time delay part of the model is calculated by a recursive least squares algorithm of system identification, which can gradually forget past information. The grey series part of the model uses an equal dimension new information model (EDNIM) and it applies 3 points smoothing method to preprocess the original data and modify remnant difference by GM(1,1). Through the optimization of the coefficient of the model, we are able to minimize the error variance of predictive data. A case study shows that the proposed method achieved high calculation precision and speed and it can be used to obtain the predictive value in real time state estimation of power distribution networks.展开更多
Grid-scale energy storage systems provide effective solutions to address challenges such as supply-load imbalances and voltage violations resulting from the non-coinciding nature of renewable energy generation and pea...Grid-scale energy storage systems provide effective solutions to address challenges such as supply-load imbalances and voltage violations resulting from the non-coinciding nature of renewable energy generation and peak demand incidents.While battery and hydrogen storage are commonly used for peak shaving,ice-based thermal energy storage systems(TESSs)offer a direct way to reduce cooling loads without electrical conversion.This paper presents a multi-objective planning framework that optimizes TESS dispatch,network topology,and photovoltaic(PV)inverter reactive power support to address operational issues in active distribution networks.The objectives of the proposed scheme include minimizing peak demand,voltage deviations,and PV inverter VAr dependency.The mixed-integer nonlinear programming problem is solved using a Pareto-based multi-objective particle swarm optimization(MOPSO)method.The MATLAB-OpenDSS simulations for a modified IEEE-123 bus system show a 7.1%reduction in peak demand,a 13%reduction in voltage deviation,and a 52%drop in PV inverter VAr usage.The obtained solutions confirm minimal operational stress on control devices such as switches and PV inverters.Thus,unlike earlier studies,this work combines all three strategies to offer an effective solution for the operational planning of the active distribution network.展开更多
This study examines various issues arising in three-phase unbalanced power distribution networks(PDNs)using a comprehensive optimization approach.With the integration of renewable energy sources,increasing energy dema...This study examines various issues arising in three-phase unbalanced power distribution networks(PDNs)using a comprehensive optimization approach.With the integration of renewable energy sources,increasing energy demands,and the adoption of smart grid technologies,power systems are undergoing a rapid transformation,making the need for efficient,reliable,and sustainable distribution networks increasingly critical.In this paper,the reconfiguration problem in a 37-bus unbalanced PDN test system is solved using five different popular metaheuristic algorithms.Among these advanced search algorithms,the Bonobo Optimizer(BO)has demonstrated superior performance in handling the complexities of unbalanced power distribution network optimization.The study is structured around four distinct scenarios:(Ⅰ)improving mean voltage profile and minimizing active power loss,(Ⅱ)minimizing Voltage Unbalance Index(VUI)and Current Unbalance Index(CUI),(Ⅲ)optimizing key reliability indices using both Line Oriented Reliability Index(LORI)and Customer Oriented Reliability Index(CORI)approaches,and(Ⅳ)employing multi-objective optimization using the Pareto front technique to simultaneously minimize active power loss,average CUI,and System Average Interruption Duration Index(SAIDI).The study aims to contribute to the development of more efficient,reliable,and sustainable energy systems by addressing voltage profiles,power losses,reduction of imbalance,and the enhancement of reliability together.展开更多
Owing to potential regulation capacities from flexible resources in energy coupling,storage,and consumption links,central energy stations(CESs)can provide additional support to power distribution network(PDN)in case o...Owing to potential regulation capacities from flexible resources in energy coupling,storage,and consumption links,central energy stations(CESs)can provide additional support to power distribution network(PDN)in case of power disruption.However,existing research has not explicitly revealed the emergency response of PDN with leveraging multiple CESs.This paper proposes a decentralized self-healing strategy of PDN to minimize the entire load loss,in which multi-area CESs’potentials including thermal storage and building thermal inertia,as well as the flexible topology of PDN,are reasonably exploited for service recovery.For sake of privacy preservation,the co-optimization of PDN and CESs is realized in a decentralized manner using adaptive alternating direction method of multipliers(ADMM).Furtherly,bilateral risk management with conditional value-at-risk(CVaR)for PDN and risk constraints for CESs is integrated to deal with uncertainties from outage duration.Case studies are conducted on a modified IEEE 33-bus PDN with multiple CESs.Numerical results illustrate that the proposed strategy can fully utilize the potentials of multi-area CESs for coordinated load restoration.The effectiveness of the performance and behaviors’adaptation against random risks is also validated.展开更多
Background:The increasing penetration of a massive number of plug-in electric vehicles(PEVs)and distributed generators(DGs)into current power distribution networks imposes obvious challenges on power distribution netw...Background:The increasing penetration of a massive number of plug-in electric vehicles(PEVs)and distributed generators(DGs)into current power distribution networks imposes obvious challenges on power distribution network operation.Methods:This paper presents an optimal temporal-spatial scheduling strategy of PEV charging demand in the presence of DGs.The solution is designed to ensure the reliable and secure operation of the active power distribution networks,the randomness introduced by PEVs and DGs can be managed through the appropriate scheduling of the PEV charging demand,as the PEVs can be considered as mobile energy storage units.Results:As a result,the charging demands of PEVs are optimally scheduled temporally and spatially,which can improve the DG utilization efficiency as well as reduce the charging cost under real-time pricing(RTP).Conclusions:The proposed scheduling strategy is evaluated through a series of simulations and the numerical results demonstrate the effectiveness and the benefits of the proposed solution.展开更多
In this work,a novel performance analysis method for evaluating the robustness of emerging power distribution networks(PDNs),which involve deployable renewable energy sources,is proposed.This is realized with the aid ...In this work,a novel performance analysis method for evaluating the robustness of emerging power distribution networks(PDNs),which involve deployable renewable energy sources,is proposed.This is realized with the aid of the outage probability(OP)criterion in the context of cooperative communications,which is widely considered in modern wireless communication systems.The main usefulness of this method is that it allows the involved components to communicate to each-other by means of a robust and flexible wireless sensor network architecture.In this context,any conventional medium voltage(MV)bus of the PDN is represented as a wireless relay node where data signals gathered from each MV bus can be forwarded reliably to a control station for the subsequent processing.The received signals at wireless nodes are decoded and then forwarded to ensure minimal errors and maximal robustness at the receiving site.The considered OP analysis denotes the probability that the power of a received information signal drops below a pre-defined threshold which satisfies the acceptable Quality of Service requirements of a reliable signal reception.To this end,simple closed-form expressions are proposed for the OP of a regenerative cooperative-based PDN in the presence of various multipath fading effects,which degrade information signals during wireless transmission.The offered results are rather simple and provide meaningful insights for the design and deployment of smart grid systems.展开更多
Like others countries of the world, in Niger also, we are witnessing an increasing use of non-linear electric loads in the domestic, hospital and industrial sectors. However, these loads degrade the shape of the elect...Like others countries of the world, in Niger also, we are witnessing an increasing use of non-linear electric loads in the domestic, hospital and industrial sectors. However, these loads degrade the shape of the electrical signal and cause disastrous effects to the equipment of the distribution system and the devices which are connected to the network. This article highlights the presence of electric harmonics in the distribution network in Niamey city. In order to do this, measurements were taken at the secondary level of the substations using an energy quality analyze r (FLUKE 1735). By using this measuring instrument, we quantified the voltage and current Total Harmonic Distortion (THD) in the three substations. The results obtained show that, although the statutable rates set by the standards are not exceeded for phase conductors, the neutral contains a very critical percentage of distortion on the residential and hospital substations. Moreover, this assessment made it possible to observe the variation of harmonics in the presence of voltage drops.展开更多
This paper introduces the problems emerged in the developing process of Nanning Medium-voltage distribution network to adapt the progress of HV network. These problems are: (1) unreasonable structure (large amount of ...This paper introduces the problems emerged in the developing process of Nanning Medium-voltage distribution network to adapt the progress of HV network. These problems are: (1) unreasonable structure (large amount of radical type 10 kV lines); (2) one 10 kV line for each customer (causing difficulties for line corridors); (3) circuit breaker are widely used for MV customers (result in complicated substation structure); (4) lots of overhead 10 kV lines in urban area. Ring circuit, insulated cables, load break switches, and fast acting fuses etc. advanced technologies are proposed for the retrofit of urban distribution network.展开更多
The proliferation of distributed energy resources(DERs)and the large-scale electrification of transportation are driving forces behind the ongoing evolution for transforming traditionally passive consumers into prosum...The proliferation of distributed energy resources(DERs)and the large-scale electrification of transportation are driving forces behind the ongoing evolution for transforming traditionally passive consumers into prosumers(both consumers and producers)in coordinated power distribution network(PDN)and urban transportation network(UTN).In this new paradigm,peer-to-peer(P2P)energy trading is a promising energy management strategy for dynamically balancing the supply and demand in elec-tricity markets.In this paper,we propose the application of Blockchain(BC)to electric vehicle charging station(EVCS)op-erations to optimally transact energy in a hierarchical P2P framework.In the proposed framework,a decentralised privacy-preserving clearing mechanism is implemented in the transactive energy market(TEM)in which BC's smart contracts are applied in a coordinated PDN and UTN operation.The effectiveness of the proposed TEM and its solution approach are validated via numerical simulations which are performed on a modified IEEE 123-bus PDN and a modified Sioux Falls UTN.展开更多
With the proliferation of advanced communication technologies and the deepening interdependence between cyber and physical components,power distribution networks are subject to miscellaneous security risks induced by ...With the proliferation of advanced communication technologies and the deepening interdependence between cyber and physical components,power distribution networks are subject to miscellaneous security risks induced by malicious attackers.To address the issue,this paper proposes a security risk assessment method and a risk-oriented defense resource allocation strategy for cyber-physical distribution networks(CPDNs)against coordinated cyber attacks.First,an attack graph-based CPDN architecture is constructed,and representative cyber-attack paths are drawn considering the CPDN topology and the risk propagation process.The probability of a successful coordinated cyber attack and incurred security risks are quantitatively assessed based on the absorbing Markov chain model and National Institute of Standards and Technology(NIST)standard.Next,a risk-oriented defense resource allocation strategy is proposed for CPDNs in different attack scenarios.The tradeoff between security risk and limited resource budget is formulated as a multi-objective optimization(MOO)problem,which is solved by an efficient optimal Pareto solution generation approach.By employing a generational distance metric,the optimal solution is prioritized from the optimal Pareto set of the MOO and leveraged for subsequent atomic allocation of defense resources.Several case studies on a modified IEEE 123-node test feeder substantiate the efficacy of the proposed security risk assessment method and risk-oriented defense resource allocation strategy.展开更多
为了应对海量分布式资源分层分布接入柔性配电网给无功优化引入的不确定性,提出了基于概率场景驱动的柔性配电网分布式无功优化方法。首先,以最小化系统损耗为目标建立了柔性配电网无功优化模型,其次,综合考虑1-范数和∞-范数的置信约束...为了应对海量分布式资源分层分布接入柔性配电网给无功优化引入的不确定性,提出了基于概率场景驱动的柔性配电网分布式无功优化方法。首先,以最小化系统损耗为目标建立了柔性配电网无功优化模型,其次,综合考虑1-范数和∞-范数的置信约束,构建基于概率场景模糊集的柔性配电网分布鲁棒无功优化模型。在此基础上,以分布式优化模型为外部框架,采用一致性加速梯度交替方向乘子法(alternating direction method of multipliers,ADMM)进行全局协调与更新迭代求解,以各子区域分布鲁棒优化模型为内部框架,采用列与约束生成(column and constraint generation,CCG)算法求解。基于改进的IEEE-33节点系统的算例仿真结果表明,所提出的柔性配电网分布式无功优化方法具有较好的收敛性,兼顾了经济性和鲁棒性的平衡。展开更多
为应对分布式光伏(photovoltaic,PV)出力和负荷需求的随机性给电力系统的经济运行造成的影响,文中提出了一种考虑多主体互动的虚拟电厂(virtual power plant,VPP)合作博弈鲁棒优化策略。文中在电能交易和无功辅助服务市场下,分别建立基...为应对分布式光伏(photovoltaic,PV)出力和负荷需求的随机性给电力系统的经济运行造成的影响,文中提出了一种考虑多主体互动的虚拟电厂(virtual power plant,VPP)合作博弈鲁棒优化策略。文中在电能交易和无功辅助服务市场下,分别建立基于价格配额曲线的配电网优化运行模型和基于点对点(peer to peer,P2P)能量交换的VPP优化运行模型,基于KL(kullback-leibler)散度的分布鲁棒优化下,以配电网制定的电价和VPP确定的上网功率为交互变量,通过配电网和VPP间的互动实现不同市场主体间的利润分配平衡,在此基础上,根据配电网和VPP互动得到的决策信息,基于纳什议价模型对各VPP进行利益分配,并采用一致性交替方向乘子法(alternating direction method of multipliers,ADMM)进行分布式求解,实现多VPP间的合作博弈,在某城区配电系统上进行的算例仿真验证了文中所提策略的有效性。展开更多
In this paper,a distributed chunkbased optimization algorithm is proposed for the resource allocation in broadband ultra-dense small cell networks.Based on the proposed algorithm,the power and subcarrier allocation pr...In this paper,a distributed chunkbased optimization algorithm is proposed for the resource allocation in broadband ultra-dense small cell networks.Based on the proposed algorithm,the power and subcarrier allocation problems are jointly optimized.In order to make the resource allocation suitable for large scale networks,the optimization problem is decomposed first based on an effective decomposition algorithm named optimal condition decomposition(OCD) algorithm.Furthermore,aiming at reducing implementation complexity,the subcarriers are divided into chunks and are allocated chunk by chunk.The simulation results show that the proposed algorithm achieves more superior performance than uniform power allocation scheme and Lagrange relaxation method,and then the proposed algorithm can strike a balance between the complexity and performance of the multi-carrier Ultra-Dense Networks.展开更多
This paper proposes a data-driven topology identification method for distribution systems with distributed energy resources(DERs).First,a neural network is trained to depict the relationship between nodal power inject...This paper proposes a data-driven topology identification method for distribution systems with distributed energy resources(DERs).First,a neural network is trained to depict the relationship between nodal power injections and voltage magnitude measurements,and then it is used to generate synthetic measurements under independent nodal power injections,thus eliminating the influence of correlated nodal power injections on topology identification.Second,a maximal information coefficient-based maximum spanning tree algorithm is developed to obtain the network topology by evaluating the dependence among the synthetic measurements.The proposed method is tested on different distribution networks and the simulation results are compared with those of other methods to validate the effectiveness of the proposed method.展开更多
基金supported by the Scientific and Technological Research Council of Turkey(TUBITAK)under Grant No.124E002(1001-Project).
文摘This study addresses the critical challenge of reconfiguration in unbalanced power distribution networks(UPDNs),focusing on the complex 123-Bus test system.Three scenarios are investigated:(1)simultaneous power loss reduction and voltage profile improvement,(2)minimization of voltage and current unbalance indices under various operational cases,and(3)multi-objective optimization using Pareto front analysis to concurrently optimize voltage unbalance index,active power loss,and current unbalance index.Unlike previous research that oftensimplified system components,this work maintains all equipment,including capacitor banks,transformers,and voltage regulators,to ensure realistic results.The study evaluates twelve metaheuristic algorithms to solve the reconfiguration problem(RecPrb)in UPDNs.A comprehensive statistical analysis is conducted to identify the most efficient algorithm for solving the RecPrb in the 123-Bus UPDN,employing multiple performance metrics and comparative techniques.The Artificial Hummingbird Algorithm emerges as the top-performing algorithm and is subsequently applied to address a multi-objective optimization challenge in the 123-Bus UPDN.This research contributes valuable insights for network operators and researchers in selecting suitable algorithms for specific reconfiguration scenarios,advancing the field of UPDN optimization and management.
基金This work is supported by the project of Hebei power technology of state grid from 2018 to 2019:Research and application of real-time situation assessment and visualization(SZKJXM20170445).
文摘In order to quickly and accurately locate the fault location of the distribution network and increase the stability of the distribution network,a fault recovery method based on multi-objective optimization algorithm is proposed.The optimization of the power distribution network fault system based on multiagent technology realizes fast recovery of multi-objective fault,solve the problem of network learning and parameter adjustment in the later stage of particle swarm optimization algorithm falling into the local extreme value dilemma,and realize the multi-dimensional nonlinear optimization of the main grid and the auxiliary grid.The system proposed in this study takes power distribution network as the goal,applies fuzzy probability algorithm,simplifies the calculation process,avoids local extreme value,and finally realizes the energy balance between each power grid.Simulation results show that the Multi-Agent Technology enjoys priority in restoring important load,shortening the recovery time of power grid balance,and reducing the overall line loss rate of power grid.Therefore,the power grid fault self-healing system can improve the safety and stability of the important power grid,and reduce the economic loss rate of the whole power grid.
文摘The models, methods and their application experiences of a practical GIS(geographic information system)-based computer decision-making support system of urban power distribution network planning with seven subsystems,termed CNP,are described.In each subsystem there is at least one or one set of practical mathematical methobs.Some new models and mathematical methods have been introduced.In the development of CNP the idea of cognitive system engineering has been insisted on,which claims that human and computer intelligence should be combined together to solve the complex engineering problems cooperatively.Practical applications have shown that not only the optimal plan can be automatically reached with many complicated factors considered, but also the computation,analysis and graphic drawing burden can be released considerably.
文摘A new combined model is proposed to obtain predictive data value applied in state estimation for radial power distribution networks. The time delay part of the model is calculated by a recursive least squares algorithm of system identification, which can gradually forget past information. The grey series part of the model uses an equal dimension new information model (EDNIM) and it applies 3 points smoothing method to preprocess the original data and modify remnant difference by GM(1,1). Through the optimization of the coefficient of the model, we are able to minimize the error variance of predictive data. A case study shows that the proposed method achieved high calculation precision and speed and it can be used to obtain the predictive value in real time state estimation of power distribution networks.
基金supported by the US Appalachian Regional Commission(ARC)under Grant MU-21579-23。
文摘Grid-scale energy storage systems provide effective solutions to address challenges such as supply-load imbalances and voltage violations resulting from the non-coinciding nature of renewable energy generation and peak demand incidents.While battery and hydrogen storage are commonly used for peak shaving,ice-based thermal energy storage systems(TESSs)offer a direct way to reduce cooling loads without electrical conversion.This paper presents a multi-objective planning framework that optimizes TESS dispatch,network topology,and photovoltaic(PV)inverter reactive power support to address operational issues in active distribution networks.The objectives of the proposed scheme include minimizing peak demand,voltage deviations,and PV inverter VAr dependency.The mixed-integer nonlinear programming problem is solved using a Pareto-based multi-objective particle swarm optimization(MOPSO)method.The MATLAB-OpenDSS simulations for a modified IEEE-123 bus system show a 7.1%reduction in peak demand,a 13%reduction in voltage deviation,and a 52%drop in PV inverter VAr usage.The obtained solutions confirm minimal operational stress on control devices such as switches and PV inverters.Thus,unlike earlier studies,this work combines all three strategies to offer an effective solution for the operational planning of the active distribution network.
基金supported by the Scientific and Technological Research Council of Turkey(TUBITAK)under Grant No.124E002(1001-Project).
文摘This study examines various issues arising in three-phase unbalanced power distribution networks(PDNs)using a comprehensive optimization approach.With the integration of renewable energy sources,increasing energy demands,and the adoption of smart grid technologies,power systems are undergoing a rapid transformation,making the need for efficient,reliable,and sustainable distribution networks increasingly critical.In this paper,the reconfiguration problem in a 37-bus unbalanced PDN test system is solved using five different popular metaheuristic algorithms.Among these advanced search algorithms,the Bonobo Optimizer(BO)has demonstrated superior performance in handling the complexities of unbalanced power distribution network optimization.The study is structured around four distinct scenarios:(Ⅰ)improving mean voltage profile and minimizing active power loss,(Ⅱ)minimizing Voltage Unbalance Index(VUI)and Current Unbalance Index(CUI),(Ⅲ)optimizing key reliability indices using both Line Oriented Reliability Index(LORI)and Customer Oriented Reliability Index(CORI)approaches,and(Ⅳ)employing multi-objective optimization using the Pareto front technique to simultaneously minimize active power loss,average CUI,and System Average Interruption Duration Index(SAIDI).The study aims to contribute to the development of more efficient,reliable,and sustainable energy systems by addressing voltage profiles,power losses,reduction of imbalance,and the enhancement of reliability together.
基金financially supported by the Fundamental Research Funds for the Central Universities(No.2021QN1066)。
文摘Owing to potential regulation capacities from flexible resources in energy coupling,storage,and consumption links,central energy stations(CESs)can provide additional support to power distribution network(PDN)in case of power disruption.However,existing research has not explicitly revealed the emergency response of PDN with leveraging multiple CESs.This paper proposes a decentralized self-healing strategy of PDN to minimize the entire load loss,in which multi-area CESs’potentials including thermal storage and building thermal inertia,as well as the flexible topology of PDN,are reasonably exploited for service recovery.For sake of privacy preservation,the co-optimization of PDN and CESs is realized in a decentralized manner using adaptive alternating direction method of multipliers(ADMM).Furtherly,bilateral risk management with conditional value-at-risk(CVaR)for PDN and risk constraints for CESs is integrated to deal with uncertainties from outage duration.Case studies are conducted on a modified IEEE 33-bus PDN with multiple CESs.Numerical results illustrate that the proposed strategy can fully utilize the potentials of multi-area CESs for coordinated load restoration.The effectiveness of the performance and behaviors’adaptation against random risks is also validated.
基金The National Key Research and Development Program of China(Basic Research Class 2017YFB0903000)Basic Theories and Methods of Analysis and Control of the Cyber Physical Systems for Power Grid,and the Natural Science Foundation of Zhejiang Province(LZ15E070001).
文摘Background:The increasing penetration of a massive number of plug-in electric vehicles(PEVs)and distributed generators(DGs)into current power distribution networks imposes obvious challenges on power distribution network operation.Methods:This paper presents an optimal temporal-spatial scheduling strategy of PEV charging demand in the presence of DGs.The solution is designed to ensure the reliable and secure operation of the active power distribution networks,the randomness introduced by PEVs and DGs can be managed through the appropriate scheduling of the PEV charging demand,as the PEVs can be considered as mobile energy storage units.Results:As a result,the charging demands of PEVs are optimally scheduled temporally and spatially,which can improve the DG utilization efficiency as well as reduce the charging cost under real-time pricing(RTP).Conclusions:The proposed scheduling strategy is evaluated through a series of simulations and the numerical results demonstrate the effectiveness and the benefits of the proposed solution.
基金This work was supported by the Research Program DGRES(MIS 380360)within the Research Activity ARCHIMEDES III,funded by the NSRF 2007-2013,Greece.
文摘In this work,a novel performance analysis method for evaluating the robustness of emerging power distribution networks(PDNs),which involve deployable renewable energy sources,is proposed.This is realized with the aid of the outage probability(OP)criterion in the context of cooperative communications,which is widely considered in modern wireless communication systems.The main usefulness of this method is that it allows the involved components to communicate to each-other by means of a robust and flexible wireless sensor network architecture.In this context,any conventional medium voltage(MV)bus of the PDN is represented as a wireless relay node where data signals gathered from each MV bus can be forwarded reliably to a control station for the subsequent processing.The received signals at wireless nodes are decoded and then forwarded to ensure minimal errors and maximal robustness at the receiving site.The considered OP analysis denotes the probability that the power of a received information signal drops below a pre-defined threshold which satisfies the acceptable Quality of Service requirements of a reliable signal reception.To this end,simple closed-form expressions are proposed for the OP of a regenerative cooperative-based PDN in the presence of various multipath fading effects,which degrade information signals during wireless transmission.The offered results are rather simple and provide meaningful insights for the design and deployment of smart grid systems.
文摘Like others countries of the world, in Niger also, we are witnessing an increasing use of non-linear electric loads in the domestic, hospital and industrial sectors. However, these loads degrade the shape of the electrical signal and cause disastrous effects to the equipment of the distribution system and the devices which are connected to the network. This article highlights the presence of electric harmonics in the distribution network in Niamey city. In order to do this, measurements were taken at the secondary level of the substations using an energy quality analyze r (FLUKE 1735). By using this measuring instrument, we quantified the voltage and current Total Harmonic Distortion (THD) in the three substations. The results obtained show that, although the statutable rates set by the standards are not exceeded for phase conductors, the neutral contains a very critical percentage of distortion on the residential and hospital substations. Moreover, this assessment made it possible to observe the variation of harmonics in the presence of voltage drops.
文摘This paper introduces the problems emerged in the developing process of Nanning Medium-voltage distribution network to adapt the progress of HV network. These problems are: (1) unreasonable structure (large amount of radical type 10 kV lines); (2) one 10 kV line for each customer (causing difficulties for line corridors); (3) circuit breaker are widely used for MV customers (result in complicated substation structure); (4) lots of overhead 10 kV lines in urban area. Ring circuit, insulated cables, load break switches, and fast acting fuses etc. advanced technologies are proposed for the retrofit of urban distribution network.
基金funded in part by the Grant No.RG-15-135-43 from the Deanship of Scientific Research(DSR)at King Abdulaziz University in Saudi Arabia.
文摘The proliferation of distributed energy resources(DERs)and the large-scale electrification of transportation are driving forces behind the ongoing evolution for transforming traditionally passive consumers into prosumers(both consumers and producers)in coordinated power distribution network(PDN)and urban transportation network(UTN).In this new paradigm,peer-to-peer(P2P)energy trading is a promising energy management strategy for dynamically balancing the supply and demand in elec-tricity markets.In this paper,we propose the application of Blockchain(BC)to electric vehicle charging station(EVCS)op-erations to optimally transact energy in a hierarchical P2P framework.In the proposed framework,a decentralised privacy-preserving clearing mechanism is implemented in the transactive energy market(TEM)in which BC's smart contracts are applied in a coordinated PDN and UTN operation.The effectiveness of the proposed TEM and its solution approach are validated via numerical simulations which are performed on a modified IEEE 123-bus PDN and a modified Sioux Falls UTN.
基金supported by the National Natural Science Foundation of China(No.52377086)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.SJCX23_0063)。
文摘With the proliferation of advanced communication technologies and the deepening interdependence between cyber and physical components,power distribution networks are subject to miscellaneous security risks induced by malicious attackers.To address the issue,this paper proposes a security risk assessment method and a risk-oriented defense resource allocation strategy for cyber-physical distribution networks(CPDNs)against coordinated cyber attacks.First,an attack graph-based CPDN architecture is constructed,and representative cyber-attack paths are drawn considering the CPDN topology and the risk propagation process.The probability of a successful coordinated cyber attack and incurred security risks are quantitatively assessed based on the absorbing Markov chain model and National Institute of Standards and Technology(NIST)standard.Next,a risk-oriented defense resource allocation strategy is proposed for CPDNs in different attack scenarios.The tradeoff between security risk and limited resource budget is formulated as a multi-objective optimization(MOO)problem,which is solved by an efficient optimal Pareto solution generation approach.By employing a generational distance metric,the optimal solution is prioritized from the optimal Pareto set of the MOO and leveraged for subsequent atomic allocation of defense resources.Several case studies on a modified IEEE 123-node test feeder substantiate the efficacy of the proposed security risk assessment method and risk-oriented defense resource allocation strategy.
文摘为了应对海量分布式资源分层分布接入柔性配电网给无功优化引入的不确定性,提出了基于概率场景驱动的柔性配电网分布式无功优化方法。首先,以最小化系统损耗为目标建立了柔性配电网无功优化模型,其次,综合考虑1-范数和∞-范数的置信约束,构建基于概率场景模糊集的柔性配电网分布鲁棒无功优化模型。在此基础上,以分布式优化模型为外部框架,采用一致性加速梯度交替方向乘子法(alternating direction method of multipliers,ADMM)进行全局协调与更新迭代求解,以各子区域分布鲁棒优化模型为内部框架,采用列与约束生成(column and constraint generation,CCG)算法求解。基于改进的IEEE-33节点系统的算例仿真结果表明,所提出的柔性配电网分布式无功优化方法具有较好的收敛性,兼顾了经济性和鲁棒性的平衡。
文摘为应对分布式光伏(photovoltaic,PV)出力和负荷需求的随机性给电力系统的经济运行造成的影响,文中提出了一种考虑多主体互动的虚拟电厂(virtual power plant,VPP)合作博弈鲁棒优化策略。文中在电能交易和无功辅助服务市场下,分别建立基于价格配额曲线的配电网优化运行模型和基于点对点(peer to peer,P2P)能量交换的VPP优化运行模型,基于KL(kullback-leibler)散度的分布鲁棒优化下,以配电网制定的电价和VPP确定的上网功率为交互变量,通过配电网和VPP间的互动实现不同市场主体间的利润分配平衡,在此基础上,根据配电网和VPP互动得到的决策信息,基于纳什议价模型对各VPP进行利益分配,并采用一致性交替方向乘子法(alternating direction method of multipliers,ADMM)进行分布式求解,实现多VPP间的合作博弈,在某城区配电系统上进行的算例仿真验证了文中所提策略的有效性。
基金supported in part by Beijing Natural Science Foundation(4152047)the 863 project No.2014AA01A701+1 种基金111 Project of China under Grant B14010China Mobile Research Institute under grant[2014]451
文摘In this paper,a distributed chunkbased optimization algorithm is proposed for the resource allocation in broadband ultra-dense small cell networks.Based on the proposed algorithm,the power and subcarrier allocation problems are jointly optimized.In order to make the resource allocation suitable for large scale networks,the optimization problem is decomposed first based on an effective decomposition algorithm named optimal condition decomposition(OCD) algorithm.Furthermore,aiming at reducing implementation complexity,the subcarriers are divided into chunks and are allocated chunk by chunk.The simulation results show that the proposed algorithm achieves more superior performance than uniform power allocation scheme and Lagrange relaxation method,and then the proposed algorithm can strike a balance between the complexity and performance of the multi-carrier Ultra-Dense Networks.
基金supported by the National Key R&D Program of China(No.2017YFB0902800)the National Natural Science Foundation of China(Grant No.52077136).
文摘This paper proposes a data-driven topology identification method for distribution systems with distributed energy resources(DERs).First,a neural network is trained to depict the relationship between nodal power injections and voltage magnitude measurements,and then it is used to generate synthetic measurements under independent nodal power injections,thus eliminating the influence of correlated nodal power injections on topology identification.Second,a maximal information coefficient-based maximum spanning tree algorithm is developed to obtain the network topology by evaluating the dependence among the synthetic measurements.The proposed method is tested on different distribution networks and the simulation results are compared with those of other methods to validate the effectiveness of the proposed method.
