Considering the uncertainty of grid connection of electric vehicle charging stations and the uncertainty of new energy and residential electricity load,a spatio-temporal decoupling strategy of dynamic reactive power o...Considering the uncertainty of grid connection of electric vehicle charging stations and the uncertainty of new energy and residential electricity load,a spatio-temporal decoupling strategy of dynamic reactive power optimization based on clustering-local relaxation-correction is proposed.Firstly,the k-medoids clustering algorithm is used to divide the reduced power scene into periods.Then,the discrete variables and continuous variables are optimized in the same period of time.Finally,the number of input groups of parallel capacitor banks(CB)in multiple periods is fixed,and then the secondary static reactive power optimization correction is carried out by using the continuous reactive power output device based on the static reactive power compensation device(SVC),the new energy grid-connected inverter,and the electric vehicle charging station.According to the characteristics of the model,a hybrid optimization algorithm with a cross-feedback mechanism is used to solve different types of variables,and an improved artificial hummingbird algorithm based on tent chaotic mapping and adaptive mutation is proposed to improve the solution efficiency.The simulation results show that the proposed decoupling strategy can obtain satisfactory optimization resultswhile strictly guaranteeing the dynamic constraints of discrete variables,and the hybrid algorithm can effectively solve the mixed integer nonlinear optimization problem.展开更多
This study proposes a method for analyzing the security distance of an Active Distribution Network(ADN)by incorporating the demand response of an Energy Hub(EH).Taking into account the impact of stochastic wind-solar ...This study proposes a method for analyzing the security distance of an Active Distribution Network(ADN)by incorporating the demand response of an Energy Hub(EH).Taking into account the impact of stochastic wind-solar power and flexible loads on the EH,an interactive power model was developed to represent the EH’s operation under these influences.Additionally,an ADN security distance model,integrating an EH with flexible loads,was constructed to evaluate the effect of flexible load variations on the ADN’s security distance.By considering scenarios such as air conditioning(AC)load reduction and base station(BS)load transfer,the security distances of phases A,B,and C increased by 17.1%,17.2%,and 17.7%,respectively.Furthermore,a multi-objective optimal power flow model was formulated and solved using the Forward-Backward Power Flow Algorithm,the NSGA-II multi-objective optimization algo-rithm,and the maximum satisfaction method.The simulation results of the IEEE33 node system example demonstrate that after opti-mization,the total energy cost for one day is reduced by 0.026%,and the total security distance limit of the ADN’s three phases is improved by 0.1 MVA.This method effectively enhances the security distance,facilitates BS load transfer and AC load reduction,and contributes to the energy-saving,economical,and safe operation of the power system.展开更多
This paper provides a systematic review on the resilience analysis of active distribution networks(ADNs)against hazardous weather events,considering the underlying cyber-physical interdependencies.As cyber-physical sy...This paper provides a systematic review on the resilience analysis of active distribution networks(ADNs)against hazardous weather events,considering the underlying cyber-physical interdependencies.As cyber-physical systems,ADNs are characterized by widespread structural and functional interdependen-cies between cyber(communication,computing,and control)and physical(electric power)subsystems and thus present complex hazardous-weather-related resilience issues.To bridge current research gaps,this paper first classifies diverse hazardous weather events for ADNs according to different time spans and degrees of hazard,with model-based and data-driven methods being utilized to characterize weather evolutions.Then,the adverse impacts of hazardous weather on all aspects of ADNs’sources,physical/cyber networks,and loads are analyzed.This paper further emphasizes the importance of situational awareness and cyber-physical collaboration throughout hazardous weather events,as these enhance the implementation of preventive dispatches,corrective actions,and coordinated restorations.In addition,a generalized quantitative resilience evaluation process is proposed regarding additional considerations about cyber subsystems and cyber-physical connections.Finally,potential hazardous-weather-related resilience challenges for both physical and cyber subsystems are discussed.展开更多
Active distribution network(ADN)planning is crucial for achieving a cost-effective transition to modern power systems,yet it poses significant challenges as the system scale increases.The advent of quantum computing o...Active distribution network(ADN)planning is crucial for achieving a cost-effective transition to modern power systems,yet it poses significant challenges as the system scale increases.The advent of quantum computing offers a transformative approach to solve ADN planning.To fully leverage the potential of quantum computing,this paper proposes a photonic quantum acceleration algorithm.First,a quantum-accelerated framework for ADN planning is proposed on the basis of coherent photonic quantum computers.The ADN planning model is then formulated and decomposed into discrete master problems and continuous subproblems to facilitate the quantum optimization process.The photonic quantum-embedded adaptive alternating direction method of multipliers(PQA-ADMM)algorithm is subsequently proposed to equivalently map the discrete master problem onto a quantum-interpretable model,enabling its deployment on a photonic quantum computer.Finally,a comparative analysis with various solvers,including Gurobi,demonstrates that the proposed PQA-ADMM algorithm achieves significant speedup on the modified IEEE 33-node and IEEE 123-node systems,highlighting its effectiveness.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
In recent years,the large-scale grid connection of various distributed power sources has made the planning and operation of distribution grids increasingly complex.Consequently,a large number of active distribution ne...In recent years,the large-scale grid connection of various distributed power sources has made the planning and operation of distribution grids increasingly complex.Consequently,a large number of active distribution network reconfiguration techniques have emerged to reduce system losses,improve system safety,and enhance power quality via switching switches to change the system topology while ensuring the radial structure of the network.While scholars have previously reviewed these methods,they all have obvious shortcomings,such as a lack of systematic integration of methods,vague classification,lack of constructive suggestions for future study,etc.Therefore,this paper attempts to provide a comprehensive and profound review of 52 methods and applications of active distribution network reconfiguration through systematic method classification and enumeration.Specifically,these methods are classified into five categories,i.e.,traditional methods,mathematical methods,meta-heuristic algorithms,machine learning methods,and hybrid methods.A thorough comparison of the various methods is also scored in terms of their practicality,complexity,number of switching actions,performance improvement,advantages,and disadvantages.Finally,four summaries and four future research prospects are presented.In summary,this paper aims to provide an up-to-date and well-rounded manual for subsequent researchers and scholars engaged in related fields.展开更多
Peer-to-peer(P2P)energy trading in active distribution networks(ADNs)plays a pivotal role in promoting the efficient consumption of renewable energy sources.However,it is challenging to effectively coordinate the powe...Peer-to-peer(P2P)energy trading in active distribution networks(ADNs)plays a pivotal role in promoting the efficient consumption of renewable energy sources.However,it is challenging to effectively coordinate the power dispatch of ADNs and P2P energy trading while preserving the privacy of different physical interests.Hence,this paper proposes a soft actor-critic algorithm incorporating distributed trading control(SAC-DTC)to tackle the optimal power dispatch of ADNs and the P2P energy trading considering privacy preservation among prosumers.First,the soft actor-critic(SAC)algorithm is used to optimize the control strategy of device in ADNs to minimize the operation cost,and the primary environmental information of the ADN at this point is published to prosumers.Then,a distributed generalized fast dual ascent method is used to iterate the trading process of prosumers and maximize their revenues.Subsequently,the results of trading are encrypted based on the differential privacy technique and returned to the ADN.Finally,the social welfare value consisting of ADN operation cost and P2P market revenue is utilized as a reward value to update network parameters and control strategies of the deep reinforcement learning.Simulation results show that the proposed SAC-DTC algorithm reduces the ADN operation cost,boosts the P2P market revenue,maximizes the social welfare,and exhibits high computational accuracy,demonstrating its practical application to the operation of power systems and power markets.展开更多
Active distribution network(ADN)is a solution for power system with interconnection of distributed energy resources(DER),which may change the network operation and power flow of traditional power distribution network....Active distribution network(ADN)is a solution for power system with interconnection of distributed energy resources(DER),which may change the network operation and power flow of traditional power distribution network.However,in some circumstances the malfunction of protection and feeder automation in distribution network occurs due to the uncertain bidirectional power flow.Therefore,a novel method of fault location,isolation,and service restoration(FLISR)for ADN based on distributed processing is proposed in this paper.The differential-activated algorithm based on synchronous sampling for feeder fault location and isolation is studied,and a framework of fault restoration is established for ADN.Finally,the effectiveness of the proposed algorithm is verified via computer simulation of a case study for active distributed power system.展开更多
With the gradual increase of distributed energy penetration,the traditional optimization model of distribution network can no longer guarantee the stable and efficient operation of the distribution network.In order to...With the gradual increase of distributed energy penetration,the traditional optimization model of distribution network can no longer guarantee the stable and efficient operation of the distribution network.In order to deal with the inevitable uncertainty of distributed energy,a new robust optimal operation method is proposed for active distribution network(ADN)based on the minimum confidence interval of distributed energy Beta distribution in this paper.First,an ADN model is established with second-order cone to include the energy storage device,capacitor bank,static var compensator,on-load tap changer,wind turbine and photovoltaic.Then,the historical data of related distributed energy are analyzed and described by the probability density function,and the minimum confidence interval is obtained by interval searching.Furthermore,via taking this minimum confidence interval as the uncertain interval,a less conservative two-stage robust optimization model is established and solved for ADN.The simulation results for the IEEE33-bus distribution network have verified that the proposed method can realize a more stable and efficient operation of the distribution network compared with the traditional robust optimization method.展开更多
This paper proposes a stochastic programming(SP)method for coordinated operation of distributed energy resources(DERs)in the unbalanced active distribution network(ADN)with diverse correlated uncertainties.First,the t...This paper proposes a stochastic programming(SP)method for coordinated operation of distributed energy resources(DERs)in the unbalanced active distribution network(ADN)with diverse correlated uncertainties.First,the threephase branch flow is modeled to characterize the unbalanced nature of the ADN,schedule DER for three phases,and derive a realistic DER allocation.Then,both active and reactive power resources are co-optimized for voltage regulation and power loss reduction.Second,the battery degradation is considered to model the aging cost for each charging or discharging event,leading to a more realistic cost estimation.Further,copulabased uncertainty modeling is applied to capture the correlations between renewable generation and power loads,and the twostage SP method is then used to get final solutions.Finally,numerical case studies are conducted on an IEEE 34-bus three-phase ADN,verifying that the proposed method can effectively reduce the system cost and co-optimize the active and reactive power.展开更多
The region-based method has been applied in transmission systems and traditional passive distribution systems without power sources. This paper proposes the model of total quadrant security region(TQSR) for active dis...The region-based method has been applied in transmission systems and traditional passive distribution systems without power sources. This paper proposes the model of total quadrant security region(TQSR) for active distribution networks(ADN) with high penetration of distributed generation(DG). Firstly, TQSR is defined as a closed set of all the N-1 secure operation points in the state space of ADN. Then, the TQSR is modeled considering the constraints of state space,normal operation and N-1 security criterion. Then, the characteristics of TQSR are observed and analyzed on the test systems with different DG penetrations. TQSR can be located in any quadrant of the state space. For different DG penetrations,the shape and security features of TQSR are also different. Finally, the region map is discovered, which summarizes the features of different types of distribution networks.展开更多
The distributed generation (DG) plays an important role in the context of the environmental problems and sustain- able development throughout the world. This paper proposes a DG siting and sizing model in an active di...The distributed generation (DG) plays an important role in the context of the environmental problems and sustain- able development throughout the world. This paper proposes a DG siting and sizing model in an active distribution network (ADN). The objective is to minimize the total cost, including investment, operation and maintenance costs. The proposed model is transferred to a Mixed Integer Second-Order Cone Programming (MISOCP) model based on a distribution network forward backward-sweep power flow and constraint relaxation. The CVX platform and GUROBI solver are used for the solution. The scenario analysis is used for the uncertainties of load and DG. Different numbers of operational scenarios are considered in order to analyze the effect of a non-network solution to the final planning result and total investment. The planning results with and without consideration of active managements, and the planning results with and without taking environmental profits into consideration, are compared and analyzed. The proposed methodology is verified with a modified IEEE 33 example.展开更多
This paper proposes a new multi-area framework for unbalanced active distribution network(ADN) state estimation. Firstly, an innovative three-phase distributed generator(DG) model is presented to take the asymmetric c...This paper proposes a new multi-area framework for unbalanced active distribution network(ADN) state estimation. Firstly, an innovative three-phase distributed generator(DG) model is presented to take the asymmetric characteristics of DG three-phase outputs into consideration. Then a feasible method to set pseudo-measurements for unmonitored DGs is introduced. The states of DGs,together with the states of alternating current(AC) buses in ADNs, were estimated by using the weighted least squares(WLS) method. After that, the ADN was divided into several independent subareas. Based on the augmented Lagrangian method, this work proposes a fully distributed three-phase state estimator for the multi-area ADN.Finally, from the simulation results on the modified IEEE123-bus system, the effectiveness and applicability of the proposed methodology have been investigated and discussed.展开更多
The escalating installation of distributed generation (DG) within active distribution networks (ADNs) diminishes the reliance on fossil fuels, yet it intensifies the disparity between demand and generation across vari...The escalating installation of distributed generation (DG) within active distribution networks (ADNs) diminishes the reliance on fossil fuels, yet it intensifies the disparity between demand and generation across various regions. Moreover, due to the intermittent and stochastic characteristics, DG also introduces uncertain forecasting errors, which further increase difficulties for power dispatch. To overcome these challenges, an emerging flexible interconnection device, soft open point (SOP), is introduced. A distributionally robust chance-constrained optimization (DRCCO) model is also proposed to effectively exploit the benefits of SOPs in ADNs under uncertainties. Compared with conventional robust, stochastic and chance-constrained models, the DRCCO model can better balance reliability and economic profits without the exact distribution of uncertainties. More-over, unlike most published works that employ two individual chance constraints to approximate the upper and lower bound constraints (e.g, bus voltage and branch current limitations), joint two-sided chance constraints are introduced and exactly reformulated into conic forms to avoid redundant conservativeness. Based on numerical experiments, we validate that SOPs' employment can significantly enhance the energy efficiency of ADNs by alleviating DG curtailment and load shedding problems. Simulation results also confirm that the proposed joint two-sided DRCCO method can achieve good balance between economic efficiency and reliability while reducing the conservativeness of conventional DRCCO methods.展开更多
This study investigates a hybrid hierarchical multi-agent system for distributed cooperative voltage control in active distribution networks. The hybrid hierarchical multi-agent system adopts on-load tap-changing(OLTC...This study investigates a hybrid hierarchical multi-agent system for distributed cooperative voltage control in active distribution networks. The hybrid hierarchical multi-agent system adopts on-load tap-changing(OLTC) agents for the distribution transformers and feeder control section(FCS) agents for the distributed generators(DGs). The objective is to minimize the voltage deviations over the network. The FCS agents also have the objective of minimizing reductions in DG power output. A least squares method is used for curve fitting to achieve the two objectives. The OLTC agent receives voltage information from the FCS agents to evaluate the state of the voltage in each feeder and the distribution network and cooperates with the FCS agents to control the voltage of the network.The FCS agents exchange the fitted curve parameters and basic information on the DGs with other agents to achieve the objectives. The effectiveness of the proposed distributed cooperative voltage control scheme is verified through simulations. Depending on the network voltages obtained by the OLTC agent, different operations are executed to prevent voltage limit violations and to minimize the voltage deviations and reductions in the DG power outputs.展开更多
As numerous distributed energy resources(DERs)are integrated into the distribution networks,the optimal dispatch of DERs is more and more imperative to achieve transition to active distribution networks(ADNs).Since ac...As numerous distributed energy resources(DERs)are integrated into the distribution networks,the optimal dispatch of DERs is more and more imperative to achieve transition to active distribution networks(ADNs).Since accurate models are usually unavailable in ADNs,an increasing number of reinforcement learning(RL)based methods have been proposed for the optimal dispatch problem.However,these RL based methods are typically formulated without safety guarantees,which hinders their application in real world.In this paper,we propose an RL based method called supervisor-projector-enhanced safe soft actor-critic(S3AC)for the optimal dispatch of DERs in ADNs,which not only minimizes the operational cost but also satisfies safety constraints during online execution.In the proposed S3AC,the data-driven supervisor and projector are pre-trained based on the historical data from supervisory control and data acquisition(SCADA)system,effectively providing enhanced safety for executed actions.Numerical studies on several IEEE test systems demonstrate the effectiveness and safety of the proposed S3AC.展开更多
Aiming at the shortcomings of a traditional centralized control in an active distribution network(AND),this paper proposes a leader-follower distributed group cooperative control strategy to realize multiple operation...Aiming at the shortcomings of a traditional centralized control in an active distribution network(AND),this paper proposes a leader-follower distributed group cooperative control strategy to realize multiple operation and control tasks for an ADN.The distributed information exchange protocols of the distributed generation(DG)group devoted to node voltage regulation or exchange power control are developed using a DG power utilization ratio as the consensus variable.On these bases,this study further investigates the leader optimal selection method for a DG group to improve the response speed of the distributed control system.Furthermore,a single or multiple leader selection model is established to minimize the constraints of the one-step convergence factor and the number of leaders to improve the response speed of the distributed control system.The simulation results of the IEEE 33 bus standard test system show the effectiveness of the proposed distributed control strategy.In addition,the response speed of a DG control group can be improved effectively when the single or multiple leaders are selected optimally.展开更多
This paper proposes an AI-based approach for islanding detection in active distribution networks.A review of existing AI-based studies reveals several gaps,including model complexity and stability concerns,limited acc...This paper proposes an AI-based approach for islanding detection in active distribution networks.A review of existing AI-based studies reveals several gaps,including model complexity and stability concerns,limited accuracy in noisy conditions,and limited applicability to systems with different types of resources.To address these challenges,this paper proposes a novel approach that adapts the WaveNet generator into a classifier,enhanced with a denoising UNet model,to improve performance in varying signal-to-noise ratio(SNR)conditions.In designing this model,we deviate from state-of-the-art approaches that primarily rely on long short-term memory(LSTM)architectures by employing 1D convolutional layers.This enables the model to focus on spatial analysis of the input signal,making it particularly well-suited for processing long input sequences.Additionally,residual connections are incorporated to mitigate overfitting and significantly enhance the model’s generalizability.To verify the effectiveness of the proposed scheme,over 14000 islanding/non-islanding cases are tested,considering different load active/reactive power values,load switching transients,capacitor bank switching,fault conditions in the main grid,different load quality factors,SNR levels,changes in network topology,and both types of conventional and inverter-based sources.展开更多
With the development of distributed photovoltaic energy in mining areas,the increasing proportion of new energy integration will gradually drive the structural transformation of coal mine parks into industrial active ...With the development of distributed photovoltaic energy in mining areas,the increasing proportion of new energy integration will gradually drive the structural transformation of coal mine parks into industrial active distribution networks.This paper takes a coal mine in Shaanxi Province as an empirical research subject,employing a multi-spatial hierarchical analysis method to systematically analyze the electricity usage characteristics across different spatial levels.It innovatively proposes a power line loss correction method for multi-level electrical equipment,effectively balancing the metering deviations of line losses between levels.Based on two types of carbon emission factors,it achieves precise evaluation of indirect carbon emissions from electricity usage in different levels of equipment or energy units.When calculating indirect carbon emissions from electricity using static carbon emission factors,the measured values show a positive correlation with peak electricity load.As the proportion of renewable photovoltaic power integration in industrial active distribution networks increases,the system’s indirect carbon emission factors exhibit a periodic decreasing trend.After adopting dynamic indirect carbon emission factors for accounting,the indirect carbon emissions from electricity in the first consumption level can be reduced by 31%-55%,while the overall plant-wide indirect carbon emissions decrease by 29068.94 kgCO_(2)/d,a reduction of approximately 40%.For the second consumption level in industrial production areas,indirect carbon emissions from electricity can be reduced by 5%-83%,with overall industrial park-wide indirect carbon emissions decreasing by 7376.48 kgCO_(2)/d,a reduction of about 31%.It is recommended to use advanced equipment and energy-saving technologies to suppress technical line losses in coal mine power supply systems and improve energy efficiency.Promoting the coordinated application of renewable energy and energy storage technologies can expand the scale of stable and reliable renewable energy supply,effectively reducing indirect carbon emissions from electricity.展开更多
基金funded by the“Research and Application Project of Collaborative Optimization Control Technology for Distribution Station Area for High Proportion Distributed PV Consumption(4000-202318079A-1-1-ZN)”of the Headquarters of the State Grid Corporation.
文摘Considering the uncertainty of grid connection of electric vehicle charging stations and the uncertainty of new energy and residential electricity load,a spatio-temporal decoupling strategy of dynamic reactive power optimization based on clustering-local relaxation-correction is proposed.Firstly,the k-medoids clustering algorithm is used to divide the reduced power scene into periods.Then,the discrete variables and continuous variables are optimized in the same period of time.Finally,the number of input groups of parallel capacitor banks(CB)in multiple periods is fixed,and then the secondary static reactive power optimization correction is carried out by using the continuous reactive power output device based on the static reactive power compensation device(SVC),the new energy grid-connected inverter,and the electric vehicle charging station.According to the characteristics of the model,a hybrid optimization algorithm with a cross-feedback mechanism is used to solve different types of variables,and an improved artificial hummingbird algorithm based on tent chaotic mapping and adaptive mutation is proposed to improve the solution efficiency.The simulation results show that the proposed decoupling strategy can obtain satisfactory optimization resultswhile strictly guaranteeing the dynamic constraints of discrete variables,and the hybrid algorithm can effectively solve the mixed integer nonlinear optimization problem.
基金supported in part by the National Nat-ural Science Foundation of China(No.51977012,No.52307080).
文摘This study proposes a method for analyzing the security distance of an Active Distribution Network(ADN)by incorporating the demand response of an Energy Hub(EH).Taking into account the impact of stochastic wind-solar power and flexible loads on the EH,an interactive power model was developed to represent the EH’s operation under these influences.Additionally,an ADN security distance model,integrating an EH with flexible loads,was constructed to evaluate the effect of flexible load variations on the ADN’s security distance.By considering scenarios such as air conditioning(AC)load reduction and base station(BS)load transfer,the security distances of phases A,B,and C increased by 17.1%,17.2%,and 17.7%,respectively.Furthermore,a multi-objective optimal power flow model was formulated and solved using the Forward-Backward Power Flow Algorithm,the NSGA-II multi-objective optimization algo-rithm,and the maximum satisfaction method.The simulation results of the IEEE33 node system example demonstrate that after opti-mization,the total energy cost for one day is reduced by 0.026%,and the total security distance limit of the ADN’s three phases is improved by 0.1 MVA.This method effectively enhances the security distance,facilitates BS load transfer and AC load reduction,and contributes to the energy-saving,economical,and safe operation of the power system.
基金supported by the National Natural Science Foundation of China(52477132 and U2066601).
文摘This paper provides a systematic review on the resilience analysis of active distribution networks(ADNs)against hazardous weather events,considering the underlying cyber-physical interdependencies.As cyber-physical systems,ADNs are characterized by widespread structural and functional interdependen-cies between cyber(communication,computing,and control)and physical(electric power)subsystems and thus present complex hazardous-weather-related resilience issues.To bridge current research gaps,this paper first classifies diverse hazardous weather events for ADNs according to different time spans and degrees of hazard,with model-based and data-driven methods being utilized to characterize weather evolutions.Then,the adverse impacts of hazardous weather on all aspects of ADNs’sources,physical/cyber networks,and loads are analyzed.This paper further emphasizes the importance of situational awareness and cyber-physical collaboration throughout hazardous weather events,as these enhance the implementation of preventive dispatches,corrective actions,and coordinated restorations.In addition,a generalized quantitative resilience evaluation process is proposed regarding additional considerations about cyber subsystems and cyber-physical connections.Finally,potential hazardous-weather-related resilience challenges for both physical and cyber subsystems are discussed.
基金supported in part by the National Natural Science Foundation of China under Grant 52307134the Fundamental Research Funds for the Central Universities(xzy012025022)。
文摘Active distribution network(ADN)planning is crucial for achieving a cost-effective transition to modern power systems,yet it poses significant challenges as the system scale increases.The advent of quantum computing offers a transformative approach to solve ADN planning.To fully leverage the potential of quantum computing,this paper proposes a photonic quantum acceleration algorithm.First,a quantum-accelerated framework for ADN planning is proposed on the basis of coherent photonic quantum computers.The ADN planning model is then formulated and decomposed into discrete master problems and continuous subproblems to facilitate the quantum optimization process.The photonic quantum-embedded adaptive alternating direction method of multipliers(PQA-ADMM)algorithm is subsequently proposed to equivalently map the discrete master problem onto a quantum-interpretable model,enabling its deployment on a photonic quantum computer.Finally,a comparative analysis with various solvers,including Gurobi,demonstrates that the proposed PQA-ADMM algorithm achieves significant speedup on the modified IEEE 33-node and IEEE 123-node systems,highlighting its effectiveness.
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.
基金funding from the National Natural Science Foundation of China(62263014)Yunnan Provincial Basic Research Project(202401AT070344,202301AT070443)Science and Technology Commission of Shanghai Municipality(STCSM)Sailing Program(22YF1414400).
文摘In recent years,the large-scale grid connection of various distributed power sources has made the planning and operation of distribution grids increasingly complex.Consequently,a large number of active distribution network reconfiguration techniques have emerged to reduce system losses,improve system safety,and enhance power quality via switching switches to change the system topology while ensuring the radial structure of the network.While scholars have previously reviewed these methods,they all have obvious shortcomings,such as a lack of systematic integration of methods,vague classification,lack of constructive suggestions for future study,etc.Therefore,this paper attempts to provide a comprehensive and profound review of 52 methods and applications of active distribution network reconfiguration through systematic method classification and enumeration.Specifically,these methods are classified into five categories,i.e.,traditional methods,mathematical methods,meta-heuristic algorithms,machine learning methods,and hybrid methods.A thorough comparison of the various methods is also scored in terms of their practicality,complexity,number of switching actions,performance improvement,advantages,and disadvantages.Finally,four summaries and four future research prospects are presented.In summary,this paper aims to provide an up-to-date and well-rounded manual for subsequent researchers and scholars engaged in related fields.
基金supported by the National Natural Science Foundation of China(No.52177085).
文摘Peer-to-peer(P2P)energy trading in active distribution networks(ADNs)plays a pivotal role in promoting the efficient consumption of renewable energy sources.However,it is challenging to effectively coordinate the power dispatch of ADNs and P2P energy trading while preserving the privacy of different physical interests.Hence,this paper proposes a soft actor-critic algorithm incorporating distributed trading control(SAC-DTC)to tackle the optimal power dispatch of ADNs and the P2P energy trading considering privacy preservation among prosumers.First,the soft actor-critic(SAC)algorithm is used to optimize the control strategy of device in ADNs to minimize the operation cost,and the primary environmental information of the ADN at this point is published to prosumers.Then,a distributed generalized fast dual ascent method is used to iterate the trading process of prosumers and maximize their revenues.Subsequently,the results of trading are encrypted based on the differential privacy technique and returned to the ADN.Finally,the social welfare value consisting of ADN operation cost and P2P market revenue is utilized as a reward value to update network parameters and control strategies of the deep reinforcement learning.Simulation results show that the proposed SAC-DTC algorithm reduces the ADN operation cost,boosts the P2P market revenue,maximizes the social welfare,and exhibits high computational accuracy,demonstrating its practical application to the operation of power systems and power markets.
基金This paper was supported by the National High Technology Research and Development Program of China(863 Program)(No.2014AA051902).
文摘Active distribution network(ADN)is a solution for power system with interconnection of distributed energy resources(DER),which may change the network operation and power flow of traditional power distribution network.However,in some circumstances the malfunction of protection and feeder automation in distribution network occurs due to the uncertain bidirectional power flow.Therefore,a novel method of fault location,isolation,and service restoration(FLISR)for ADN based on distributed processing is proposed in this paper.The differential-activated algorithm based on synchronous sampling for feeder fault location and isolation is studied,and a framework of fault restoration is established for ADN.Finally,the effectiveness of the proposed algorithm is verified via computer simulation of a case study for active distributed power system.
基金supported in part by the National Natural Science Foundation of China(No.61703081)the Liaoning Joint Fund of National Natural Science Foundation of China(No.U1908217)+1 种基金the Natural Science Foundation of Liaoning Province(No.20170520113)the Fundamental Research Funds for the Central Universities(No.N2004016)。
文摘With the gradual increase of distributed energy penetration,the traditional optimization model of distribution network can no longer guarantee the stable and efficient operation of the distribution network.In order to deal with the inevitable uncertainty of distributed energy,a new robust optimal operation method is proposed for active distribution network(ADN)based on the minimum confidence interval of distributed energy Beta distribution in this paper.First,an ADN model is established with second-order cone to include the energy storage device,capacitor bank,static var compensator,on-load tap changer,wind turbine and photovoltaic.Then,the historical data of related distributed energy are analyzed and described by the probability density function,and the minimum confidence interval is obtained by interval searching.Furthermore,via taking this minimum confidence interval as the uncertain interval,a less conservative two-stage robust optimization model is established and solved for ADN.The simulation results for the IEEE33-bus distribution network have verified that the proposed method can realize a more stable and efficient operation of the distribution network compared with the traditional robust optimization method.
文摘This paper proposes a stochastic programming(SP)method for coordinated operation of distributed energy resources(DERs)in the unbalanced active distribution network(ADN)with diverse correlated uncertainties.First,the threephase branch flow is modeled to characterize the unbalanced nature of the ADN,schedule DER for three phases,and derive a realistic DER allocation.Then,both active and reactive power resources are co-optimized for voltage regulation and power loss reduction.Second,the battery degradation is considered to model the aging cost for each charging or discharging event,leading to a more realistic cost estimation.Further,copulabased uncertainty modeling is applied to capture the correlations between renewable generation and power loads,and the twostage SP method is then used to get final solutions.Finally,numerical case studies are conducted on an IEEE 34-bus three-phase ADN,verifying that the proposed method can effectively reduce the system cost and co-optimize the active and reactive power.
基金supported in part by National Key Research and Development Program of China (No. 2016YFB0900100)National Natural Science Foundation of China (No. 51877144)China Postdoctoral Science Foundation (No.2020M670668)。
文摘The region-based method has been applied in transmission systems and traditional passive distribution systems without power sources. This paper proposes the model of total quadrant security region(TQSR) for active distribution networks(ADN) with high penetration of distributed generation(DG). Firstly, TQSR is defined as a closed set of all the N-1 secure operation points in the state space of ADN. Then, the TQSR is modeled considering the constraints of state space,normal operation and N-1 security criterion. Then, the characteristics of TQSR are observed and analyzed on the test systems with different DG penetrations. TQSR can be located in any quadrant of the state space. For different DG penetrations,the shape and security features of TQSR are also different. Finally, the region map is discovered, which summarizes the features of different types of distribution networks.
基金This work was supported in part by the Shanghai Engineering Re-search Center of Green Energy Grid-Connected Technology under Grant 13DZ2251900the Key Laboratory of Control of Power Transmission and Conversion(SJTU),Ministry of Education(2016AA01,2016AA03).
文摘The distributed generation (DG) plays an important role in the context of the environmental problems and sustain- able development throughout the world. This paper proposes a DG siting and sizing model in an active distribution network (ADN). The objective is to minimize the total cost, including investment, operation and maintenance costs. The proposed model is transferred to a Mixed Integer Second-Order Cone Programming (MISOCP) model based on a distribution network forward backward-sweep power flow and constraint relaxation. The CVX platform and GUROBI solver are used for the solution. The scenario analysis is used for the uncertainties of load and DG. Different numbers of operational scenarios are considered in order to analyze the effect of a non-network solution to the final planning result and total investment. The planning results with and without consideration of active managements, and the planning results with and without taking environmental profits into consideration, are compared and analyzed. The proposed methodology is verified with a modified IEEE 33 example.
基金supported by National Natural Science Foundation of China(No.51277052)
文摘This paper proposes a new multi-area framework for unbalanced active distribution network(ADN) state estimation. Firstly, an innovative three-phase distributed generator(DG) model is presented to take the asymmetric characteristics of DG three-phase outputs into consideration. Then a feasible method to set pseudo-measurements for unmonitored DGs is introduced. The states of DGs,together with the states of alternating current(AC) buses in ADNs, were estimated by using the weighted least squares(WLS) method. After that, the ADN was divided into several independent subareas. Based on the augmented Lagrangian method, this work proposes a fully distributed three-phase state estimator for the multi-area ADN.Finally, from the simulation results on the modified IEEE123-bus system, the effectiveness and applicability of the proposed methodology have been investigated and discussed.
基金supported in part by the Science and Technology Development Fund,Macao,China(File no.SKL-IOTSC2021-2023(UM)&0076/2019/AMJ&003/2020/AKP)the Science and Technology Department of Sichuan Province(File no.2020YFH0191).
文摘The escalating installation of distributed generation (DG) within active distribution networks (ADNs) diminishes the reliance on fossil fuels, yet it intensifies the disparity between demand and generation across various regions. Moreover, due to the intermittent and stochastic characteristics, DG also introduces uncertain forecasting errors, which further increase difficulties for power dispatch. To overcome these challenges, an emerging flexible interconnection device, soft open point (SOP), is introduced. A distributionally robust chance-constrained optimization (DRCCO) model is also proposed to effectively exploit the benefits of SOPs in ADNs under uncertainties. Compared with conventional robust, stochastic and chance-constrained models, the DRCCO model can better balance reliability and economic profits without the exact distribution of uncertainties. More-over, unlike most published works that employ two individual chance constraints to approximate the upper and lower bound constraints (e.g, bus voltage and branch current limitations), joint two-sided chance constraints are introduced and exactly reformulated into conic forms to avoid redundant conservativeness. Based on numerical experiments, we validate that SOPs' employment can significantly enhance the energy efficiency of ADNs by alleviating DG curtailment and load shedding problems. Simulation results also confirm that the proposed joint two-sided DRCCO method can achieve good balance between economic efficiency and reliability while reducing the conservativeness of conventional DRCCO methods.
基金supported by the National High Technology Research and Development Program(863 Program)of China under Grant 2015AA050104the Science and Technology Project of the State Grid Corporation of China(5211DS150015)
文摘This study investigates a hybrid hierarchical multi-agent system for distributed cooperative voltage control in active distribution networks. The hybrid hierarchical multi-agent system adopts on-load tap-changing(OLTC) agents for the distribution transformers and feeder control section(FCS) agents for the distributed generators(DGs). The objective is to minimize the voltage deviations over the network. The FCS agents also have the objective of minimizing reductions in DG power output. A least squares method is used for curve fitting to achieve the two objectives. The OLTC agent receives voltage information from the FCS agents to evaluate the state of the voltage in each feeder and the distribution network and cooperates with the FCS agents to control the voltage of the network.The FCS agents exchange the fitted curve parameters and basic information on the DGs with other agents to achieve the objectives. The effectiveness of the proposed distributed cooperative voltage control scheme is verified through simulations. Depending on the network voltages obtained by the OLTC agent, different operations are executed to prevent voltage limit violations and to minimize the voltage deviations and reductions in the DG power outputs.
基金supported in part by the National Key Research and Development Plan of China(No.2022YFB2402900)in part by the Science and Technology Project of State Grid Corporation of China“Key Techniques of Adaptive Grid Integration and Active Synchronization for Extremely High Penetration Distributed Photovoltaic Power Generation”(No.52060023001T)。
文摘As numerous distributed energy resources(DERs)are integrated into the distribution networks,the optimal dispatch of DERs is more and more imperative to achieve transition to active distribution networks(ADNs).Since accurate models are usually unavailable in ADNs,an increasing number of reinforcement learning(RL)based methods have been proposed for the optimal dispatch problem.However,these RL based methods are typically formulated without safety guarantees,which hinders their application in real world.In this paper,we propose an RL based method called supervisor-projector-enhanced safe soft actor-critic(S3AC)for the optimal dispatch of DERs in ADNs,which not only minimizes the operational cost but also satisfies safety constraints during online execution.In the proposed S3AC,the data-driven supervisor and projector are pre-trained based on the historical data from supervisory control and data acquisition(SCADA)system,effectively providing enhanced safety for executed actions.Numerical studies on several IEEE test systems demonstrate the effectiveness and safety of the proposed S3AC.
文摘Aiming at the shortcomings of a traditional centralized control in an active distribution network(AND),this paper proposes a leader-follower distributed group cooperative control strategy to realize multiple operation and control tasks for an ADN.The distributed information exchange protocols of the distributed generation(DG)group devoted to node voltage regulation or exchange power control are developed using a DG power utilization ratio as the consensus variable.On these bases,this study further investigates the leader optimal selection method for a DG group to improve the response speed of the distributed control system.Furthermore,a single or multiple leader selection model is established to minimize the constraints of the one-step convergence factor and the number of leaders to improve the response speed of the distributed control system.The simulation results of the IEEE 33 bus standard test system show the effectiveness of the proposed distributed control strategy.In addition,the response speed of a DG control group can be improved effectively when the single or multiple leaders are selected optimally.
文摘This paper proposes an AI-based approach for islanding detection in active distribution networks.A review of existing AI-based studies reveals several gaps,including model complexity and stability concerns,limited accuracy in noisy conditions,and limited applicability to systems with different types of resources.To address these challenges,this paper proposes a novel approach that adapts the WaveNet generator into a classifier,enhanced with a denoising UNet model,to improve performance in varying signal-to-noise ratio(SNR)conditions.In designing this model,we deviate from state-of-the-art approaches that primarily rely on long short-term memory(LSTM)architectures by employing 1D convolutional layers.This enables the model to focus on spatial analysis of the input signal,making it particularly well-suited for processing long input sequences.Additionally,residual connections are incorporated to mitigate overfitting and significantly enhance the model’s generalizability.To verify the effectiveness of the proposed scheme,over 14000 islanding/non-islanding cases are tested,considering different load active/reactive power values,load switching transients,capacitor bank switching,fault conditions in the main grid,different load quality factors,SNR levels,changes in network topology,and both types of conventional and inverter-based sources.
基金supported by CHN Energy Investment Group(GJNY-23-138)。
文摘With the development of distributed photovoltaic energy in mining areas,the increasing proportion of new energy integration will gradually drive the structural transformation of coal mine parks into industrial active distribution networks.This paper takes a coal mine in Shaanxi Province as an empirical research subject,employing a multi-spatial hierarchical analysis method to systematically analyze the electricity usage characteristics across different spatial levels.It innovatively proposes a power line loss correction method for multi-level electrical equipment,effectively balancing the metering deviations of line losses between levels.Based on two types of carbon emission factors,it achieves precise evaluation of indirect carbon emissions from electricity usage in different levels of equipment or energy units.When calculating indirect carbon emissions from electricity using static carbon emission factors,the measured values show a positive correlation with peak electricity load.As the proportion of renewable photovoltaic power integration in industrial active distribution networks increases,the system’s indirect carbon emission factors exhibit a periodic decreasing trend.After adopting dynamic indirect carbon emission factors for accounting,the indirect carbon emissions from electricity in the first consumption level can be reduced by 31%-55%,while the overall plant-wide indirect carbon emissions decrease by 29068.94 kgCO_(2)/d,a reduction of approximately 40%.For the second consumption level in industrial production areas,indirect carbon emissions from electricity can be reduced by 5%-83%,with overall industrial park-wide indirect carbon emissions decreasing by 7376.48 kgCO_(2)/d,a reduction of about 31%.It is recommended to use advanced equipment and energy-saving technologies to suppress technical line losses in coal mine power supply systems and improve energy efficiency.Promoting the coordinated application of renewable energy and energy storage technologies can expand the scale of stable and reliable renewable energy supply,effectively reducing indirect carbon emissions from electricity.
