The low efficiency and high cost of fresh agricultural product terminal distribution directly restrict the operation of the entire supply network.To reduce costs and optimize the distribution network,we construct a mi...The low efficiency and high cost of fresh agricultural product terminal distribution directly restrict the operation of the entire supply network.To reduce costs and optimize the distribution network,we construct a mixed integer programmingmodel that comprehensively considers tominimize fixed,transportation,fresh-keeping,time,carbon emissions,and performance incentive costs.We analyzed the performance of traditional rider distribution and robot distribution modes in detail.In addition,the uncertainty of the actual market demand poses a huge threat to the stability of the terminal distribution network.In order to resist uncertain interference,we further extend the model to a robust counterpart form.The results of the simulation show that the instability of random parameters will lead to an increase in the cost.Compared with the traditional rider distribution mode,the robot distribution mode can save 12.7%on logistics costs,and the distribution efficiency is higher.Our research can provide support for the design of planning schemes for transportation enterprise managers.展开更多
With the current integration of distributed energy resources into the grid,the structure of distribution networks is becoming more complex.This complexity significantly expands the solution space in the optimization p...With the current integration of distributed energy resources into the grid,the structure of distribution networks is becoming more complex.This complexity significantly expands the solution space in the optimization process for network reconstruction using intelligent algorithms.Consequently,traditional intelligent algorithms frequently encounter insufficient search accuracy and become trapped in local optima.To tackle this issue,a more advanced particle swarm optimization algorithm is proposed.To address the varying emphases at different stages of the optimization process,a dynamic strategy is implemented to regulate the social and self-learning factors.The Metropolis criterion is introduced into the simulated annealing algorithm to occasionally accept suboptimal solutions,thereby mitigating premature convergence in the population optimization process.The inertia weight is adjusted using the logistic mapping technique to maintain a balance between the algorithm’s global and local search abilities.The incorporation of the Pareto principle involves the consideration of network losses and voltage deviations as objective functions.A fuzzy membership function is employed for selecting the results.Simulation analysis is carried out on the restructuring of the distribution network,using the IEEE-33 node system and the IEEE-69 node system as examples,in conjunction with the integration of distributed energy resources.The findings demonstrate that,in comparison to other intelligent optimization algorithms,the proposed enhanced algorithm demonstrates a shorter convergence time and effectively reduces active power losses within the network.Furthermore,it enhances the amplitude of node voltages,thereby improving the stability of distribution network operations and power supply quality.Additionally,the algorithm exhibits a high level of generality and applicability.展开更多
The couple between the power network and the transportation network(TN)is deepening gradually with the increasing penetration rate of electric vehicles(EV),which also poses a great challenge to the traditional voltage...The couple between the power network and the transportation network(TN)is deepening gradually with the increasing penetration rate of electric vehicles(EV),which also poses a great challenge to the traditional voltage control scheme.In this paper,we propose a coordinated voltage control strategy for the active distribution networks considering multiple types of EV.In the first stage,the action of on-load tap changer and capacitor banks,etc.,are determined by optimal power flow calculation,and the node electricity price is also determined based on dynamic time-of-use tariff mechanism.In the second stage,multiple operating scenarios of multiple types of EVs such as cabs,private cars and buses are considered,and the scheduling results of each EV are solved by building an optimization model based on constraints such as queuing theory,Floyd-Warshall algorithm and traffic flow information.In the third stage,the output power of photovoltaic and energy storage systems is fine-tuned in the normal control mode.The charging power of EVs is also regulated in the emergency control mode to reduce the voltage deviation,and the amount of regulation is calculated based on the fair voltage control mode of EVs.Finally,we test the modified IEEE 33-bus distribution system coupled with the 24-bus Beijing TN.The simulation results show that the proposed scheme can mitigate voltage violations well.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
After suffering from a grid blackout, distributed energy resources(DERs), such as local renewable energy and controllable distributed generators and energy storage can be used to restore loads enhancing the system’s ...After suffering from a grid blackout, distributed energy resources(DERs), such as local renewable energy and controllable distributed generators and energy storage can be used to restore loads enhancing the system’s resilience. In this study, a multi-source coordinated load restoration strategy was investigated for a distribution network with soft open points(SOPs). Here, the flexible regulation ability of the SOPs is fully utilized to improve the load restoration level while mitigating voltage deviations. Owing to the uncertainty, a scenario-based stochastic optimization approach was employed,and the load restoration problem was formulated as a mixed-integer nonlinear programming model. A computationally efficient solution algorithm was developed for the model using convex relaxation and linearization methods. The algorithm is organized into a two-stage structure, in which the energy storage system is dispatched in the first stage by solving a relaxed convex problem. In the second stage, an integer programming problem is calculated to acquire the outputs of both SOPs and power resources. A numerical test was conducted on both IEEE 33-bus and IEEE 123-bus systems to validate the effectiveness of the proposed strategy.展开更多
Traditional distribution network planning relies on the professional knowledge of planners,especially when analyzing the correlations between the problems existing in the network and the crucial influencing factors.Th...Traditional distribution network planning relies on the professional knowledge of planners,especially when analyzing the correlations between the problems existing in the network and the crucial influencing factors.The inherent laws reflected by the historical data of the distribution network are ignored,which affects the objectivity of the planning scheme.In this study,to improve the efficiency and accuracy of distribution network planning,the characteristics of distribution network data were extracted using a data-mining technique,and correlation knowledge of existing problems in the network was obtained.A data-mining model based on correlation rules was established.The inputs of the model were the electrical characteristic indices screened using the gray correlation method.The Apriori algorithm was used to extract correlation knowledge from the operational data of the distribution network and obtain strong correlation rules.Degree of promotion and chi-square tests were used to verify the rationality of the strong correlation rules of the model output.In this study,the correlation relationship between heavy load or overload problems of distribution network feeders in different regions and related characteristic indices was determined,and the confidence of the correlation rules was obtained.These results can provide an effective basis for the formulation of a distribution network planning scheme.展开更多
A novel operation control method for relay protection in flexible DC distribution networks with distributed power supply is proposed to address the issue of inaccurate fault location during relay protection,leading to...A novel operation control method for relay protection in flexible DC distribution networks with distributed power supply is proposed to address the issue of inaccurate fault location during relay protection,leading to poor performance.The method combines a fault-tolerant fault location method based on long-term and short-term memory networks to accurately locate the fault section.Then,an operation control method for relay protection based on adaptive weight and whale optimization algorithm(WOA)is used to construct an objective function considering the shortest relay protection action time and the smallest impulse current.The adaptive weight and WOA are employed to obtain the optimal strategy for relay protection operation control,reducing the action time and impulse current.Experimental results demonstrate the effectiveness of the proposed method in accurately locating faults and improving relay protection performance.The longest operation time is reduced by 4.7023 s,and the maximum impulse current is limited to 0.3 A,effectively controlling the impact of large impulse currents and enhancing control efficiency.展开更多
The N-1 criterion is a critical factor for ensuring the reliable and resilient operation of electric power distribution networks.However,the increasing complexity of distribution networks and the associated growth in ...The N-1 criterion is a critical factor for ensuring the reliable and resilient operation of electric power distribution networks.However,the increasing complexity of distribution networks and the associated growth in data size have created a significant challenge for distribution network planners.To address this issue,we propose a fast N-1 verification procedure for urban distribution networks that combines CIM file data analysis with MILP-based mathematical modeling.Our proposed method leverages the principles of CIM file analysis for distribution network N-1 analysis.We develop a mathematical model of distribution networks based on CIM data and transfer it into MILP.We also take into account the characteristics of medium voltage distribution networks after a line failure and select the feeder section at the exit of each substation with a high load rate to improve the efficiency of N-1 analysis.We validate our approach through a series of case studies and demonstrate its scalability and superiority over traditional N-1 analysis and heuristic optimization algorithms.By enabling online N-1 analysis,our approach significantly improves the work efficiency of distribution network planners.In summary,our proposed method provides a valuable tool for distribution network planners to enhance the accuracy and efficiency of their N-1 analyses.By leveraging the advantages of CIM file data analysis and MILP-based mathematical modeling,our approach contributes to the development of more resilient and reliable electric power distribution networks.展开更多
The uncertainty of distributed generation energy has dramatically challenged the coordinated development of distribution networks at all levels.This paper focuses on the multi-time-scale regulation model of distribute...The uncertainty of distributed generation energy has dramatically challenged the coordinated development of distribution networks at all levels.This paper focuses on the multi-time-scale regulation model of distributed generation energy under normal conditions.The simulation results of the example verify the self-optimization characteristics and the effectiveness of real-time dispatching of the distribution network control technology at all levels under multiple time scales.展开更多
In the framework of vigorous promotion of low-carbon power system growth as well as economic globalization,multi-resource penetration in active distribution networks has been advancing fiercely.In particular,distribut...In the framework of vigorous promotion of low-carbon power system growth as well as economic globalization,multi-resource penetration in active distribution networks has been advancing fiercely.In particular,distributed generation(DG)based on renewable energy is critical for active distribution network operation enhancement.To comprehensively analyze the accessing impact of DG in distribution networks from various parts,this paper establishes an optimal DG location and sizing planning model based on active power losses,voltage profile,pollution emissions,and the economics of DG costs as well as meteorological conditions.Subsequently,multiobjective particle swarm optimization(MOPSO)is applied to obtain the optimal Pareto front.Besides,for the sake of avoiding the influence of the subjective setting of the weight coefficient,the decisionmethod based on amodified ideal point is applied to execute a Pareto front decision.Finally,simulation tests based on IEEE33 and IEEE69 nodes are designed.The experimental results show thatMOPSO can achieve wider and more uniformPareto front distribution.In the IEEE33 node test system,power loss,and voltage deviation decreased by 52.23%,and 38.89%,respectively,while taking the economy into account.In the IEEE69 test system,the three indexes decreased by 19.67%,and 58.96%,respectively.展开更多
A blockchain-based power transaction method is proposed for Active Distribution Network(ADN),considering the poor security and high cost of a centralized power trading system.Firstly,the decentralized blockchain struc...A blockchain-based power transaction method is proposed for Active Distribution Network(ADN),considering the poor security and high cost of a centralized power trading system.Firstly,the decentralized blockchain structure of the ADN power transaction is built and the transaction information is kept in blocks.Secondly,considering the transaction needs between users and power suppliers in ADN,an energy request mechanism is proposed,and the optimization objective function is designed by integrating cost aware requests and storage aware requests.Finally,the particle swarm optimization algorithm is used for multi-objective optimal search to find the power trading scheme with the minimum power purchase cost of users and the maximum power sold by power suppliers.The experimental demonstration of the proposed method based on the experimental platform shows that when the number of participants is no more than 10,the transaction delay time is 0.2 s,and the transaction cost fluctuates at 200,000 yuan,which is better than other comparison methods.展开更多
Distribution networks denote important public infrastructure necessary for people’s livelihoods.However,extreme natural disasters,such as earthquakes,typhoons,and mudslides,severely threaten the safe and stable opera...Distribution networks denote important public infrastructure necessary for people’s livelihoods.However,extreme natural disasters,such as earthquakes,typhoons,and mudslides,severely threaten the safe and stable operation of distribution networks and power supplies needed for daily life.Therefore,considering the requirements for distribution network disaster prevention and mitigation,there is an urgent need for in-depth research on risk assessment methods of distribution networks under extreme natural disaster conditions.This paper accessesmultisource data,presents the data quality improvement methods of distribution networks,and conducts data-driven active fault diagnosis and disaster damage analysis and evaluation using data-driven theory.Furthermore,the paper realizes real-time,accurate access to distribution network disaster information.The proposed approach performs an accurate and rapid assessment of cross-sectional risk through case study.The minimal average annual outage time can be reduced to 3 h/a in the ring network through case study.The approach proposed in this paper can provide technical support to the further improvement of the ability of distribution networks to cope with extreme natural disasters.展开更多
ADC distribution network is an effective solution for increasing renewable energy utilization with distinct benefits,such as high efficiency and easy control.However,a sudden increase in the current after the occurren...ADC distribution network is an effective solution for increasing renewable energy utilization with distinct benefits,such as high efficiency and easy control.However,a sudden increase in the current after the occurrence of faults in the network may adversely affect network stability.This study proposes an artificial neural network(ANN)-based fault detection and protection method for DC distribution networks.The ANN is applied to a classifier for different faults ontheDC line.The backpropagationneuralnetwork is used to predict the line current,and the fault detection threshold is obtained on the basis of the difference between the predicted current and the actual current.The proposed method only uses local signals,with no requirement of a strict communication link.Simulation experiments are conducted for the proposed algorithm on a two-terminal DC distribution network modeled in the PSCAD/EMTDC and developed on the MATLAB platform.The results confirm that the proposed method can accurately detect and classify line faults within a few milliseconds and is not affected by fault locations,fault resistance,noise,and communication delay.展开更多
A distribution network plays an extremely important role in the safe and efficient operation of a power grid.As the core part of a power grid’s operation,a distribution network will have a significant impact on the s...A distribution network plays an extremely important role in the safe and efficient operation of a power grid.As the core part of a power grid’s operation,a distribution network will have a significant impact on the safety and reliability of residential electricity consumption.it is necessary to actively plan and modify the distribution network’s structure in the power grid,improve the quality of the distribution network,and optimize the planning of the distribution network,so that the network can be fully utilized to meet the needs of electricity consumption.In this paper,a distribution network grid planning algorithm based on the reliability of electricity consumption was completed using ant colony algorithm.For the distribution network structure planning of dual power sources,the parallel ant colony algorithm was used to prove that the premise of parallelism is the interactive process of ant colonies,and the dual power distribution network structure model is established based on the principle of the lowest cost.The artificial ants in the algorithm were compared with real ants in nature,and the basic steps and working principle of the ant colony optimization algorithm was studied with the help of the travelling salesman problem(TSP).Then,the limitations of the ant colony algorithm were analyzed,and an improvement strategy was proposed by using python for digital simulation.The results demonstrated the reliability of model-building and algorithm improvement.展开更多
Taking an industrial park as an example,this study aims to analyze the characteristics of a distribution network that incorporates distributed energy resources(DERs).The study begins by summarizing the key features of...Taking an industrial park as an example,this study aims to analyze the characteristics of a distribution network that incorporates distributed energy resources(DERs).The study begins by summarizing the key features of a distribution network with DERs based on recent power usage data.To predict and analyze the load growth of the industrial park,an improved back-propagation algorithm is employed.Furthermore,the study classifies users within the industrial park according to their specific power consumption and supply requirements.This user segmentation allows for the introduction of three constraints:node voltage,wire current,and capacity of DERs.By incorporating these constraints,the study constructs an optimization model for the distribution network in the industrial park,with the objective of minimizing the total operation and maintenance cost.The primary goal of these optimizations is to address the needs of DERs connected to the distribution network,while simultaneously mitigating their potential adverse impact on the network.Additionally,the study aims to enhance the overall energy efficiency of the industrial park through more efficient utilization of resources.展开更多
Based on the background of achieving carbon peaking and carbon neutrality, the development and application of new high-power compressors, electric grid drilling RIGS and electric fracturing pump system provide new equ...Based on the background of achieving carbon peaking and carbon neutrality, the development and application of new high-power compressors, electric grid drilling RIGS and electric fracturing pump system provide new equipment support for the electric, green and intelligent development of shale gas fields in China. However, the harmonic pollution of shale gas grid becomes more serious due to the converter and frequency conversion device in the system, which easily causes harmonic resonance problem. Therefore, the harmonic resonance of shale gas grid is comprehensively analyzed and treated. Firstly, the working mechanism of compressor, electric drilling RIGS of the harmonic impedance model of electric fracturing pump system is established. Secondly, the main research methods of harmonic resonance analysis are introduced, and the basic principle of modal analysis is explained. Modal analysis method was used to analyze. Finally, harmonic resonance is suppressed. The results show that there may be multiple resonant frequency points in the distribution network changes, but these changes are relatively clear;if the original resonant frequency point of the resonant loop does not exist, the resonant frequency point disappears. The optimal configuration strategy of passive filter can effectively suppress harmonic resonance of distribution network in shale gas field.展开更多
At present,the large-scale access to electric vehicles(EVs)is exerting considerable pressure on the distribution network.Hence,it is particularly important to analyze the capacity of the distribution network to accomm...At present,the large-scale access to electric vehicles(EVs)is exerting considerable pressure on the distribution network.Hence,it is particularly important to analyze the capacity of the distribution network to accommodate EVs.To this end,we propose a method for analyzing the EV capacity of the distribution network by considering the composition of the conventional load.First,the analysis and pretreatment methods for the distribution network architecture and conventional load are proposed.Second,the charging behavior of an EVis simulated by combining the Monte Carlo method and the trip chain theory.After obtaining the temporal and spatial distribution of the EV charging load,themethod of distribution according to the proportion of the same type of conventional load among the nodes is adopted to integrate the EV charging load with the conventional load of the distribution network.By adjusting the EV ownership,the EV capacity in the distribution network is analyzed and solved on the basis of the following indices:node voltage,branch current,and transformer capacity.Finally,by considering the 10-kV distribution network in some areas of an actual city as an example,we show that the proposed analysis method can obtain a more reasonable number of EVs to be accommodated in the distribution network.展开更多
In this paper,a model free volt/var control(VVC)algorithm is developed by using deep reinforcement learning(DRL).We transform the VVC problem of distribution networks into the network framework of PPO algorithm,in ord...In this paper,a model free volt/var control(VVC)algorithm is developed by using deep reinforcement learning(DRL).We transform the VVC problem of distribution networks into the network framework of PPO algorithm,in order to avoid directly solving a large-scale nonlinear optimization problem.We select photovoltaic inverters as agents to adjust system voltage in a distribution network,taking the reactive power output of inverters as action variables.An appropriate reward function is designed to guide the interaction between photovoltaic inverters and the distribution network environment.OPENDSS is used to output system node voltage and network loss.This method realizes the goal of optimal VVC in distribution network.The IEEE 13-bus three phase unbalanced distribution system is used to verify the effectiveness of the proposed algorithm.Simulation results demonstrate that the proposed method has excellent performance in voltage and reactive power regulation of a distribution network.展开更多
This paper concentrates on compensating the power quality issues which have been increased in day-to-day life due to the enormous usage of loads with power electronic control.One such solution is compensating devices ...This paper concentrates on compensating the power quality issues which have been increased in day-to-day life due to the enormous usage of loads with power electronic control.One such solution is compensating devices like Pension Protection Fund(PPF),Active power filter(APF),hybrid power filter(HPF),etc.,which are used to overcome Power Quality(PQ)issues.The proposed method used here is an active compensator called unified power quality condi-tioner(UPQC)which is a combination of shunt and series type active filter con-nected via a common DC link.The primary objective is to investigate the behavior of the compensators in the distribution networks.The performance of two configurations of UPQC,Right Shunt UPQC(RS-UPQC)and Left Shunt UPQC(LS-UPQC)are tested in the distribution networks under various load con-ditions by connecting them at the source side of harmonic generation using a spe-cially constructed transformer called inductively filtered converter transformer which adopts special wiring scheme at the secondary side.PSCAD(Power Sys-tems Computer Aided Design)/EMTDC(Electromagnetic Transients with DC Analysis)software is used to model the compensators connected to the nonlinear load.Both RS-UPQC and LS-UPQC are tested at the distribution side of the sup-ply system with Hysteresis current controller for shunt and Sinusoidal pulse with modulation controller for series at various locations of power system network and their results are compared.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
文摘The low efficiency and high cost of fresh agricultural product terminal distribution directly restrict the operation of the entire supply network.To reduce costs and optimize the distribution network,we construct a mixed integer programmingmodel that comprehensively considers tominimize fixed,transportation,fresh-keeping,time,carbon emissions,and performance incentive costs.We analyzed the performance of traditional rider distribution and robot distribution modes in detail.In addition,the uncertainty of the actual market demand poses a huge threat to the stability of the terminal distribution network.In order to resist uncertain interference,we further extend the model to a robust counterpart form.The results of the simulation show that the instability of random parameters will lead to an increase in the cost.Compared with the traditional rider distribution mode,the robot distribution mode can save 12.7%on logistics costs,and the distribution efficiency is higher.Our research can provide support for the design of planning schemes for transportation enterprise managers.
基金This research is supported by the Science and Technology Program of Gansu Province(No.23JRRA880).
文摘With the current integration of distributed energy resources into the grid,the structure of distribution networks is becoming more complex.This complexity significantly expands the solution space in the optimization process for network reconstruction using intelligent algorithms.Consequently,traditional intelligent algorithms frequently encounter insufficient search accuracy and become trapped in local optima.To tackle this issue,a more advanced particle swarm optimization algorithm is proposed.To address the varying emphases at different stages of the optimization process,a dynamic strategy is implemented to regulate the social and self-learning factors.The Metropolis criterion is introduced into the simulated annealing algorithm to occasionally accept suboptimal solutions,thereby mitigating premature convergence in the population optimization process.The inertia weight is adjusted using the logistic mapping technique to maintain a balance between the algorithm’s global and local search abilities.The incorporation of the Pareto principle involves the consideration of network losses and voltage deviations as objective functions.A fuzzy membership function is employed for selecting the results.Simulation analysis is carried out on the restructuring of the distribution network,using the IEEE-33 node system and the IEEE-69 node system as examples,in conjunction with the integration of distributed energy resources.The findings demonstrate that,in comparison to other intelligent optimization algorithms,the proposed enhanced algorithm demonstrates a shorter convergence time and effectively reduces active power losses within the network.Furthermore,it enhances the amplitude of node voltages,thereby improving the stability of distribution network operations and power supply quality.Additionally,the algorithm exhibits a high level of generality and applicability.
基金supported by the Science and Technology Project of North China Electric Power Research Institute,which is“Research on Key Technologies for Power Quality Evaluation and Improvement of New Distribution Network Based on Collaborative Interaction of Source-Network-Load-Storage”(KJZ2022016).
文摘The couple between the power network and the transportation network(TN)is deepening gradually with the increasing penetration rate of electric vehicles(EV),which also poses a great challenge to the traditional voltage control scheme.In this paper,we propose a coordinated voltage control strategy for the active distribution networks considering multiple types of EV.In the first stage,the action of on-load tap changer and capacitor banks,etc.,are determined by optimal power flow calculation,and the node electricity price is also determined based on dynamic time-of-use tariff mechanism.In the second stage,multiple operating scenarios of multiple types of EVs such as cabs,private cars and buses are considered,and the scheduling results of each EV are solved by building an optimization model based on constraints such as queuing theory,Floyd-Warshall algorithm and traffic flow information.In the third stage,the output power of photovoltaic and energy storage systems is fine-tuned in the normal control mode.The charging power of EVs is also regulated in the emergency control mode to reduce the voltage deviation,and the amount of regulation is calculated based on the fair voltage control mode of EVs.Finally,we test the modified IEEE 33-bus distribution system coupled with the 24-bus Beijing TN.The simulation results show that the proposed scheme can mitigate voltage violations well.
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 the State Grid Tianjin Electric Power Company Science and Technology Project (Grant No. KJ22-1-45)。
文摘After suffering from a grid blackout, distributed energy resources(DERs), such as local renewable energy and controllable distributed generators and energy storage can be used to restore loads enhancing the system’s resilience. In this study, a multi-source coordinated load restoration strategy was investigated for a distribution network with soft open points(SOPs). Here, the flexible regulation ability of the SOPs is fully utilized to improve the load restoration level while mitigating voltage deviations. Owing to the uncertainty, a scenario-based stochastic optimization approach was employed,and the load restoration problem was formulated as a mixed-integer nonlinear programming model. A computationally efficient solution algorithm was developed for the model using convex relaxation and linearization methods. The algorithm is organized into a two-stage structure, in which the energy storage system is dispatched in the first stage by solving a relaxed convex problem. In the second stage, an integer programming problem is calculated to acquire the outputs of both SOPs and power resources. A numerical test was conducted on both IEEE 33-bus and IEEE 123-bus systems to validate the effectiveness of the proposed strategy.
基金supported by the Science and Technology Project of China Southern Power Grid(GZHKJXM20210043-080041KK52210002).
文摘Traditional distribution network planning relies on the professional knowledge of planners,especially when analyzing the correlations between the problems existing in the network and the crucial influencing factors.The inherent laws reflected by the historical data of the distribution network are ignored,which affects the objectivity of the planning scheme.In this study,to improve the efficiency and accuracy of distribution network planning,the characteristics of distribution network data were extracted using a data-mining technique,and correlation knowledge of existing problems in the network was obtained.A data-mining model based on correlation rules was established.The inputs of the model were the electrical characteristic indices screened using the gray correlation method.The Apriori algorithm was used to extract correlation knowledge from the operational data of the distribution network and obtain strong correlation rules.Degree of promotion and chi-square tests were used to verify the rationality of the strong correlation rules of the model output.In this study,the correlation relationship between heavy load or overload problems of distribution network feeders in different regions and related characteristic indices was determined,and the confidence of the correlation rules was obtained.These results can provide an effective basis for the formulation of a distribution network planning scheme.
文摘A novel operation control method for relay protection in flexible DC distribution networks with distributed power supply is proposed to address the issue of inaccurate fault location during relay protection,leading to poor performance.The method combines a fault-tolerant fault location method based on long-term and short-term memory networks to accurately locate the fault section.Then,an operation control method for relay protection based on adaptive weight and whale optimization algorithm(WOA)is used to construct an objective function considering the shortest relay protection action time and the smallest impulse current.The adaptive weight and WOA are employed to obtain the optimal strategy for relay protection operation control,reducing the action time and impulse current.Experimental results demonstrate the effectiveness of the proposed method in accurately locating faults and improving relay protection performance.The longest operation time is reduced by 4.7023 s,and the maximum impulse current is limited to 0.3 A,effectively controlling the impact of large impulse currents and enhancing control efficiency.
基金supported by the National Natural Science Foundation of China(52207105)。
文摘The N-1 criterion is a critical factor for ensuring the reliable and resilient operation of electric power distribution networks.However,the increasing complexity of distribution networks and the associated growth in data size have created a significant challenge for distribution network planners.To address this issue,we propose a fast N-1 verification procedure for urban distribution networks that combines CIM file data analysis with MILP-based mathematical modeling.Our proposed method leverages the principles of CIM file analysis for distribution network N-1 analysis.We develop a mathematical model of distribution networks based on CIM data and transfer it into MILP.We also take into account the characteristics of medium voltage distribution networks after a line failure and select the feeder section at the exit of each substation with a high load rate to improve the efficiency of N-1 analysis.We validate our approach through a series of case studies and demonstrate its scalability and superiority over traditional N-1 analysis and heuristic optimization algorithms.By enabling online N-1 analysis,our approach significantly improves the work efficiency of distribution network planners.In summary,our proposed method provides a valuable tool for distribution network planners to enhance the accuracy and efficiency of their N-1 analyses.By leveraging the advantages of CIM file data analysis and MILP-based mathematical modeling,our approach contributes to the development of more resilient and reliable electric power distribution networks.
文摘The uncertainty of distributed generation energy has dramatically challenged the coordinated development of distribution networks at all levels.This paper focuses on the multi-time-scale regulation model of distributed generation energy under normal conditions.The simulation results of the example verify the self-optimization characteristics and the effectiveness of real-time dispatching of the distribution network control technology at all levels under multiple time scales.
基金The authors gratefully acknowledge the support of the Enhancement Strategy of Multi-Type Energy Integration of Active Distribution Network(YNKJXM20220113).
文摘In the framework of vigorous promotion of low-carbon power system growth as well as economic globalization,multi-resource penetration in active distribution networks has been advancing fiercely.In particular,distributed generation(DG)based on renewable energy is critical for active distribution network operation enhancement.To comprehensively analyze the accessing impact of DG in distribution networks from various parts,this paper establishes an optimal DG location and sizing planning model based on active power losses,voltage profile,pollution emissions,and the economics of DG costs as well as meteorological conditions.Subsequently,multiobjective particle swarm optimization(MOPSO)is applied to obtain the optimal Pareto front.Besides,for the sake of avoiding the influence of the subjective setting of the weight coefficient,the decisionmethod based on amodified ideal point is applied to execute a Pareto front decision.Finally,simulation tests based on IEEE33 and IEEE69 nodes are designed.The experimental results show thatMOPSO can achieve wider and more uniformPareto front distribution.In the IEEE33 node test system,power loss,and voltage deviation decreased by 52.23%,and 38.89%,respectively,while taking the economy into account.In the IEEE69 test system,the three indexes decreased by 19.67%,and 58.96%,respectively.
基金supported by the Postdoctoral Research Funding Program of Jiangsu Province under Grant 2021K622C.
文摘A blockchain-based power transaction method is proposed for Active Distribution Network(ADN),considering the poor security and high cost of a centralized power trading system.Firstly,the decentralized blockchain structure of the ADN power transaction is built and the transaction information is kept in blocks.Secondly,considering the transaction needs between users and power suppliers in ADN,an energy request mechanism is proposed,and the optimization objective function is designed by integrating cost aware requests and storage aware requests.Finally,the particle swarm optimization algorithm is used for multi-objective optimal search to find the power trading scheme with the minimum power purchase cost of users and the maximum power sold by power suppliers.The experimental demonstration of the proposed method based on the experimental platform shows that when the number of participants is no more than 10,the transaction delay time is 0.2 s,and the transaction cost fluctuates at 200,000 yuan,which is better than other comparison methods.
文摘Distribution networks denote important public infrastructure necessary for people’s livelihoods.However,extreme natural disasters,such as earthquakes,typhoons,and mudslides,severely threaten the safe and stable operation of distribution networks and power supplies needed for daily life.Therefore,considering the requirements for distribution network disaster prevention and mitigation,there is an urgent need for in-depth research on risk assessment methods of distribution networks under extreme natural disaster conditions.This paper accessesmultisource data,presents the data quality improvement methods of distribution networks,and conducts data-driven active fault diagnosis and disaster damage analysis and evaluation using data-driven theory.Furthermore,the paper realizes real-time,accurate access to distribution network disaster information.The proposed approach performs an accurate and rapid assessment of cross-sectional risk through case study.The minimal average annual outage time can be reduced to 3 h/a in the ring network through case study.The approach proposed in this paper can provide technical support to the further improvement of the ability of distribution networks to cope with extreme natural disasters.
基金supported by Key Natural Science Research Projects of Colleges and Universities in Anhui Province(No.2022AH051831).
文摘ADC distribution network is an effective solution for increasing renewable energy utilization with distinct benefits,such as high efficiency and easy control.However,a sudden increase in the current after the occurrence of faults in the network may adversely affect network stability.This study proposes an artificial neural network(ANN)-based fault detection and protection method for DC distribution networks.The ANN is applied to a classifier for different faults ontheDC line.The backpropagationneuralnetwork is used to predict the line current,and the fault detection threshold is obtained on the basis of the difference between the predicted current and the actual current.The proposed method only uses local signals,with no requirement of a strict communication link.Simulation experiments are conducted for the proposed algorithm on a two-terminal DC distribution network modeled in the PSCAD/EMTDC and developed on the MATLAB platform.The results confirm that the proposed method can accurately detect and classify line faults within a few milliseconds and is not affected by fault locations,fault resistance,noise,and communication delay.
文摘A distribution network plays an extremely important role in the safe and efficient operation of a power grid.As the core part of a power grid’s operation,a distribution network will have a significant impact on the safety and reliability of residential electricity consumption.it is necessary to actively plan and modify the distribution network’s structure in the power grid,improve the quality of the distribution network,and optimize the planning of the distribution network,so that the network can be fully utilized to meet the needs of electricity consumption.In this paper,a distribution network grid planning algorithm based on the reliability of electricity consumption was completed using ant colony algorithm.For the distribution network structure planning of dual power sources,the parallel ant colony algorithm was used to prove that the premise of parallelism is the interactive process of ant colonies,and the dual power distribution network structure model is established based on the principle of the lowest cost.The artificial ants in the algorithm were compared with real ants in nature,and the basic steps and working principle of the ant colony optimization algorithm was studied with the help of the travelling salesman problem(TSP).Then,the limitations of the ant colony algorithm were analyzed,and an improvement strategy was proposed by using python for digital simulation.The results demonstrated the reliability of model-building and algorithm improvement.
基金supported by the Shanghai Municipal Social Science Foundation(No.2020BGL032).
文摘Taking an industrial park as an example,this study aims to analyze the characteristics of a distribution network that incorporates distributed energy resources(DERs).The study begins by summarizing the key features of a distribution network with DERs based on recent power usage data.To predict and analyze the load growth of the industrial park,an improved back-propagation algorithm is employed.Furthermore,the study classifies users within the industrial park according to their specific power consumption and supply requirements.This user segmentation allows for the introduction of three constraints:node voltage,wire current,and capacity of DERs.By incorporating these constraints,the study constructs an optimization model for the distribution network in the industrial park,with the objective of minimizing the total operation and maintenance cost.The primary goal of these optimizations is to address the needs of DERs connected to the distribution network,while simultaneously mitigating their potential adverse impact on the network.Additionally,the study aims to enhance the overall energy efficiency of the industrial park through more efficient utilization of resources.
文摘Based on the background of achieving carbon peaking and carbon neutrality, the development and application of new high-power compressors, electric grid drilling RIGS and electric fracturing pump system provide new equipment support for the electric, green and intelligent development of shale gas fields in China. However, the harmonic pollution of shale gas grid becomes more serious due to the converter and frequency conversion device in the system, which easily causes harmonic resonance problem. Therefore, the harmonic resonance of shale gas grid is comprehensively analyzed and treated. Firstly, the working mechanism of compressor, electric drilling RIGS of the harmonic impedance model of electric fracturing pump system is established. Secondly, the main research methods of harmonic resonance analysis are introduced, and the basic principle of modal analysis is explained. Modal analysis method was used to analyze. Finally, harmonic resonance is suppressed. The results show that there may be multiple resonant frequency points in the distribution network changes, but these changes are relatively clear;if the original resonant frequency point of the resonant loop does not exist, the resonant frequency point disappears. The optimal configuration strategy of passive filter can effectively suppress harmonic resonance of distribution network in shale gas field.
基金supported by the Science and Technology Project of Zhangjiakou Power Supply Company of State Grid Jibei Co.,Ltd.(SGJBZJ00YJJS2001096).
文摘At present,the large-scale access to electric vehicles(EVs)is exerting considerable pressure on the distribution network.Hence,it is particularly important to analyze the capacity of the distribution network to accommodate EVs.To this end,we propose a method for analyzing the EV capacity of the distribution network by considering the composition of the conventional load.First,the analysis and pretreatment methods for the distribution network architecture and conventional load are proposed.Second,the charging behavior of an EVis simulated by combining the Monte Carlo method and the trip chain theory.After obtaining the temporal and spatial distribution of the EV charging load,themethod of distribution according to the proportion of the same type of conventional load among the nodes is adopted to integrate the EV charging load with the conventional load of the distribution network.By adjusting the EV ownership,the EV capacity in the distribution network is analyzed and solved on the basis of the following indices:node voltage,branch current,and transformer capacity.Finally,by considering the 10-kV distribution network in some areas of an actual city as an example,we show that the proposed analysis method can obtain a more reasonable number of EVs to be accommodated in the distribution network.
基金supported by the Science and Technology Project of State Grid Zhejiang Electric Power Co.,Ltd.under Grant B311JY21000A。
文摘In this paper,a model free volt/var control(VVC)algorithm is developed by using deep reinforcement learning(DRL).We transform the VVC problem of distribution networks into the network framework of PPO algorithm,in order to avoid directly solving a large-scale nonlinear optimization problem.We select photovoltaic inverters as agents to adjust system voltage in a distribution network,taking the reactive power output of inverters as action variables.An appropriate reward function is designed to guide the interaction between photovoltaic inverters and the distribution network environment.OPENDSS is used to output system node voltage and network loss.This method realizes the goal of optimal VVC in distribution network.The IEEE 13-bus three phase unbalanced distribution system is used to verify the effectiveness of the proposed algorithm.Simulation results demonstrate that the proposed method has excellent performance in voltage and reactive power regulation of a distribution network.
文摘This paper concentrates on compensating the power quality issues which have been increased in day-to-day life due to the enormous usage of loads with power electronic control.One such solution is compensating devices like Pension Protection Fund(PPF),Active power filter(APF),hybrid power filter(HPF),etc.,which are used to overcome Power Quality(PQ)issues.The proposed method used here is an active compensator called unified power quality condi-tioner(UPQC)which is a combination of shunt and series type active filter con-nected via a common DC link.The primary objective is to investigate the behavior of the compensators in the distribution networks.The performance of two configurations of UPQC,Right Shunt UPQC(RS-UPQC)and Left Shunt UPQC(LS-UPQC)are tested in the distribution networks under various load con-ditions by connecting them at the source side of harmonic generation using a spe-cially constructed transformer called inductively filtered converter transformer which adopts special wiring scheme at the secondary side.PSCAD(Power Sys-tems Computer Aided Design)/EMTDC(Electromagnetic Transients with DC Analysis)software is used to model the compensators connected to the nonlinear load.Both RS-UPQC and LS-UPQC are tested at the distribution side of the sup-ply system with Hysteresis current controller for shunt and Sinusoidal pulse with modulation controller for series at various locations of power system network and their results are compared.
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.
