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
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
In order to form an algorithm for distribution network routing,an automatic routing method of distribution network planning was proposed based on the shortest path.The problem of automatic routing was divided into two...In order to form an algorithm for distribution network routing,an automatic routing method of distribution network planning was proposed based on the shortest path.The problem of automatic routing was divided into two steps in the method:the first step was that the shortest paths along streets between substation and load points were found by the basic ant colony algorithm to form a preliminary radial distribution network,and the second step was that the result of the shortest path was used to initialize pheromone concentration and pheromone updating rules to generate globally optimal distribution network.Cases studies show that the proposed method is effective and can meet the planning requirements.It is verified that the proposed method has better solution and utility than planning method based on the ant colony algorithm.展开更多
The models, methods and their application experiences of a practical GIS(geographic information system)-based computer decision-making support system of urban power distribution network planning with seven subsystems,...The models, methods and their application experiences of a practical GIS(geographic information system)-based computer decision-making support system of urban power distribution network planning with seven subsystems,termed CNP,are described.In each subsystem there is at least one or one set of practical mathematical methobs.Some new models and mathematical methods have been introduced.In the development of CNP the idea of cognitive system engineering has been insisted on,which claims that human and computer intelligence should be combined together to solve the complex engineering problems cooperatively.Practical applications have shown that not only the optimal plan can be automatically reached with many complicated factors considered, but also the computation,analysis and graphic drawing burden can be released considerably.展开更多
At the present stage, the distribution network has been in a relatively low voltage position, has become the main medium between power supply companies, customers and distribution system users, the working conditions ...At the present stage, the distribution network has been in a relatively low voltage position, has become the main medium between power supply companies, customers and distribution system users, the working conditions of distribution network system and the distribution equipment quality has high requirements, so by improving the grid requirements to improve the security of the distribution network, become Chinas current power development transition stage must attach great importance to the development goals, is also the key measures to ensure user safety. With the continuous growth of the national economy, Chinas domestic power industry development has been improved accordingly, its level is gradually to developed countries and local governments, this is mainly due to the distribution network construction, construction, management operation accumulated valuable experience, learned a lot of lessons and made significant progress, but over time, Chinas domestic distribution network operation calculation specification also need to be modified with the process of time, it is an important measure to improve the level of distribution network management, but also to reduce the negative impact and play a good role.展开更多
Theauthor proposes a dual layer source grid load storage collaborative planning model based on Benders decomposition to optimize the low-carbon and economic performance of the distribution network.The model plans the ...Theauthor proposes a dual layer source grid load storage collaborative planning model based on Benders decomposition to optimize the low-carbon and economic performance of the distribution network.The model plans the configuration of photovoltaic(3.8 MW),wind power(2.5 MW),energy storage(2.2 MWh),and SVC(1.2 Mvar)through interaction between upper and lower layers,and modifies lines 2–3,8–9,etc.to improve transmission capacity and voltage stability.The author uses normal distribution and Monte Carlo method to model load uncertainty,and combines Weibull distribution to describe wind speed characteristics.Compared to the traditional three-layer model(TLM),Benders decomposition-based two-layer model(BLBD)has a 58.1%reduction in convergence time(5.36 vs.12.78 h),a 51.1%reduction in iteration times(23 vs.47 times),a 8.07%reduction in total cost(12.436 vs.13.528 million yuan),and a 9.62%reduction in carbon emissions(12,456 vs.13,782 t).After optimization,the peak valley difference decreased from4.1 to 2.9MW,the renewable energy consumption rate reached 93.4%,and the energy storage efficiency was 87.6%.Themodel has been validated in the IEEE 33 node system,demonstrating its superiority in terms of economy,low-carbon,and reliability.展开更多
With increasing electricity demand and large-scale stochastic charging of electric vehicles(EVs),distribution networks face inevitable shortage of transfer capability,bringing new challenges to distribution network pl...With increasing electricity demand and large-scale stochastic charging of electric vehicles(EVs),distribution networks face inevitable shortage of transfer capability,bringing new challenges to distribution network planning(DNP).Dynamic thermal rating(DTR),which evaluates the equipment rating based on actual meteorological conditions and equipment thermal state,can enhance the equipment transfer capability to meet the increasing load demand.In this paper,we propose a model considering the active response of EVs,and a bi-level DNP model incorporating the DTR of cables and transformers,in the upper level,the Prim algorithm is embedded into the particle swarm optimisation(PSO)algorithm to obtain an initial grid topology;in the lower level,types of cables and transformers as well as the installation of DTR equipment are determined,second-order cone(SOC)relaxation and linearisation of the variables product are then carried out to meet the non-linear constraints of cables and transformers,and the upper and lower models are solved in an iterative manner.Case studies demonstrate that the implementation of DTR effectively enhances the transfer capability of cables and transformers,saving 4.8%investment cost while ensuring 96%uplift of power supply.Besides,with 90%active response rate of EVs,total cost can be further reduced.展开更多
Rational distribution network planning optimizes power flow distribution,reduces grid stress,enhances voltage quality,promotes renewable energy utilization,and reduces costs.This study establishes a distribution netwo...Rational distribution network planning optimizes power flow distribution,reduces grid stress,enhances voltage quality,promotes renewable energy utilization,and reduces costs.This study establishes a distribution network planning model incorporating distributed wind turbines(DWT),distributed photovoltaics(DPV),and energy storage systems(ESS).K-means++is employed to partition the distribution network based on electrical distance.Considering the spatiotemporal correlation of distributed generation(DG)outputs in the same region,a joint output model of DWT and DPV is developed using the Frank-Copula.Due to the model’s high dimensionality,multiple constraints,and mixed-integer characteristics,bilevel programming theory is utilized to structure the model.The model is solved using a mixed-integer particle swarmoptimization algorithm(MIPSO)to determine the optimal location and capacity of DG and ESS integrated into the distribution network to achieve the best economic benefits and operation quality.The proposed bilevel planning method for distribution networks is validated through simulations on the modified IEEE 33-bus system.The results demonstrate significant improvements,with the proposedmethod reducing the annual comprehensive cost by 41.65%and 13.98%,respectively,compared to scenarios without DG and ESS or with only DG integration.Furthermore,it reduces the daily average voltage deviation by 24.35%and 10.24%and daily network losses by 55.72%and 35.71%.展开更多
For facing the challenges brought by large-scale renewable energy having access to the system and considering the key technologies of energy Internet,it is very necessary to put forward the location method of distribu...For facing the challenges brought by large-scale renewable energy having access to the system and considering the key technologies of energy Internet,it is very necessary to put forward the location method of distribution network equipment and capacity from the perspective of life cycle cost.Compared with the traditional energy network,the equipment capacity problem of energy interconnected distribution network which involves in electricity network,thermal energy network and natural gas network is comprehensively considered in this paper.On this basis,firstly,the operation architecture of energy interconnected distribution network is designed.Secondly,taking the grid connection location and configuration capacity of key equipment in the system as the control variables and the operation cost of system comprehensive planning in the whole life cycle as the goal,the equipment location and capacity optimization model of energy interconnected distribution network is established.Finally,an IEEE 33 bus energy mutual distribution grid system is taken for example analysis,and the improved chaotic particle swarmoptimization algorithm is used to solve it.The simulation results show that the method proposed in this paper is suitable for the equipment location and capacity planning of energy interconnected distribution network,and it can effectively improve the social and economic benefits of system operation.展开更多
This paper presents a novel approach for electrical distribution network expansion planning using multi-objective particle swarm optimization (PSO). The optimization objectives are: investment and operation cost, ener...This paper presents a novel approach for electrical distribution network expansion planning using multi-objective particle swarm optimization (PSO). The optimization objectives are: investment and operation cost, energy losses cost, and power congestion cost. A two-phase multi-objective PSO algorithm is employed to solve this optimization problem, which can accelerate the convergence and guarantee the diversity of Pareto-optimal front set as well. The feasibility and effectiveness of both the proposed multi-objective planning approach and the improved multi-objective PSO have been verified by the 18-node typical system.展开更多
In order to cope with the global environmental crisis caused by energy generation and achieve carbon neutrality,it is imperative to promote a new power system dominated by renewable energy sources(RESs).This paper foc...In order to cope with the global environmental crisis caused by energy generation and achieve carbon neutrality,it is imperative to promote a new power system dominated by renewable energy sources(RESs).This paper focuses on the uncertainty of RESs and the distribution characteristics of carbon emission flows(CEFs),and studies the low-carbon operation and power system planning problem.Firstly,this paper extends the uncertainty of RES to the meteorological field and establishes meteorological robust constraints of photovoltaic(PV)generation.Based on the CEF theory,the carbon transmission trajectory is accurately delineated to improve the operation of power system.Considering further constraints from the power flow,CEF,and component operation characteristics of the active distribution network(ADN),this paper formulates a low-carbon joint planning model of ADN with PV,battery energy storage system(BESS),and distributed gas generator(DGG),taking into account economy and carbon reduction.In the case study,the low-carbon planning and operation scheme are analyzed in detail across multiple dimensions including time and space.The solution results show that the planning model can effectively leverage the low-carbon performance of PV and BESS,and improve the distribution of CEF.Through case comparison,the model can also efficiently reduce the total cost of the system and enhance carbon emission reduction benefits by 35.10 to 41.04%.展开更多
More electricity utilities will participate in the investment and operation of private distributed generations(DGs)while the local power company is responsible for the reinforcement of lines and DGs,as well.How to ach...More electricity utilities will participate in the investment and operation of private distributed generations(DGs)while the local power company is responsible for the reinforcement of lines and DGs,as well.How to achieve the maximum benefits among various utilities,including the power company,is a task in the expansion planning of distribution networks.To solve the market-oriented planning problem,virtual peer to peer(P2P)trading is integrated and modeled in the new expansion planning of distribution networks.First,virtual market transaction optimization among prosumers is formulated.Second,the distributed regional marginal price(DLMP)is calculated by the optimal operation model,which contributed to the network usage charge(NUC)and then integrated in the expansion planning model.Case studies are performed and indicate the integrated P2P transaction strategy could improve local load consumption,while reducing the load rate of lines,as well as the electricity cost of users.Besides,the total planning cost paid by the power company could be saved via prosumers’investment and P2P transactions and the factors affecting power company’s profit are also classified in multi-investor planning of distribution networks.展开更多
The health status of distribution equipment and networks is not considered directly in existing distribution network planning methods.In order to effectively consider the health status and deal with the risk associate...The health status of distribution equipment and networks is not considered directly in existing distribution network planning methods.In order to effectively consider the health status and deal with the risk associated with load and renewable generation uncertainties,this paper presents a new optimal expansion planning approach for distribution network(EPADN)incorporating equipment’s health index(HI)and non-network solutions(NNSs).HI and relevant risk are used to help develop the optimal equipment replacement strategy and temporary NNSs are considered as promising options for handling the uncertainties of load growth,reliability requirements of power supply and output of distributed energy resources(DERs)at a lower cost than network alternatives.An EPADN model using network solutions(NSs)and NNSs is proposed.The planning objectives of the proposed model are safety,reliability,economy,and‘greenness’that are also the meaning of distribution network HI.A method integrating an improved niche genetic algorithm(INGA)and a spanning tree algorithm(STA)is fitted to solve the model presented here for real sized networks with a manageable computational cost.Simulation results of an actual 22-node distribution network in China,illustrate the effectiveness of the proposed approach.展开更多
The concept of DG clusters is introduced with highly penetrated integration of distributed generation(DG)into active distribution networks(ADNs).DG clusters are referred to as parts of an ADN,including DGs,distributio...The concept of DG clusters is introduced with highly penetrated integration of distributed generation(DG)into active distribution networks(ADNs).DG clusters are referred to as parts of an ADN,including DGs,distribution lines and loads.The formation of DG clusters helps to optimally dispatch DG outputs within ADNs.In this regard,an integrated planning strategy of ADNs and DGs in cluster(IPNDGC)is proposed.In order to guarantee that the planning strategy meets the reliability requirements,a reliability assessment is considered in the proposed model.However,reliability assessment is generally accomplished according to a fixed network topology and known DG allocation,which makes it difficult to integrate reliability into planning models.To deal with this difficulty,a novel formulation method for reliability assessment is proposed considering the network topology uncertainties and isolated operating probabilities of DG clusters.The reliability index(RI)represented by expected customer interruption cost(ECOST)is employed in the proposed planning model.The planning model is formulated as a mixed integer second order conic programming planning model.An actual distribution system is employed to illustrate the accuracy and efficiency of the proposed planning model.展开更多
Large integration of electric vehicles(EVs)brings uncertainties and challenges for distribution networks.Reliability and allocation of charging systems(charging stations and piles)need strong support from the distribu...Large integration of electric vehicles(EVs)brings uncertainties and challenges for distribution networks.Reliability and allocation of charging systems(charging stations and piles)need strong support from the distribution network,whose expansion planning would be also greatly impacted by the incremental load from the charging system.To address this issue,a collaborative planning scheme of the EV charging system and distribution networks that combines economic and reliability benefits is proposed,which is formulated as a two-stage distributionally robust optimization model considering source-load uncertainties.First,a candidate EVCS planning scheme is obtained using queuing theory.Then,system reliability is quantified by adopting the average energy not supplied index and correlated integrated into the two-stage mixed-integer linear programming model.Finally,it is solved to perform distributionally robust expansion planning by the column and constraint generation algorithm.Effectiveness and scalability of the proposed planning method are illustrated by numerical case studies.Results indicate the planning scheme that considers economic and reliability benefit can perform better than traditional optimization methods.展开更多
With the increased integration of photovoltaic(PV)power generation into active distribution networks,the operational challenges and their complexities are increased.Such networks need detailed characterization PV syst...With the increased integration of photovoltaic(PV)power generation into active distribution networks,the operational challenges and their complexities are increased.Such networks need detailed characterization PV systems under multiple operating conditions to understand true impacts.This paper presents a new mathematical model for a PV system to capture detailed effects of PV systems.The proposed model incorporates state transitions of components in a PV system and captures effects of insolation variations.The paper performs a reliability assessment incorporating PV systems at resource locations.The results suggest that the reliability performance of an active distribution network at stressed operating conditions might be influenced by the high penetration of PV system.Reliability performance of distribution networks that are high penetrated with PV systems can be affected by cloudy effects resulting from insolation variations.The proposed model can be used to quantify the level of reduction in reliability,resulting with cloudy effects.展开更多
Feeder routing and reliability assessment are essential for effective distribution network planning.However,excessively long feeders can lead to increased costs and decreased reliability.To enhance economic and reliab...Feeder routing and reliability assessment are essential for effective distribution network planning.However,excessively long feeders can lead to increased costs and decreased reliability.To enhance economic and reliability performance,this paper proposes a reliability-centered planning method for feeder routing and conductor sizing.Specifically,a graph-based fictitious power flow model is constructed within the geographic graph.Overlapping feeder routes powered by fictitious power flows from multiple sources are designated as line connection.These feeder routes,constrained by the geographic graph,are interconnected via line connection to form a mesh network structure.To meet the requirements of reliability-centered optimization,the affiliation variables are introduced.Based on the affiliation variables,the algebraic formula is embedded into the fictitious power flow model to enable the calculation of reliability during the optimization process.By incorporating customized reliability-related constraints in the model,the specific reliability objectives can be achieved.In addition,the non-convex terms in the fictitious power flow model are relaxed into convex forms,and certain variable products are replaced with auxiliary variables,allowing the problem to be solved by an off-the-shelf solver.Finally,the proposed method is tested on two case studies,demonstrating its effectiveness.展开更多
为充分提高配电系统调度和控制的灵活性,建设和落实以智能化和主动化为导向,以信息通信技术为支撑的信息物理主动配电系统(cyber-physical active distribution system,CPADS)显得至关重要。基于此,提出计及混合通信组网的CPADS协调规...为充分提高配电系统调度和控制的灵活性,建设和落实以智能化和主动化为导向,以信息通信技术为支撑的信息物理主动配电系统(cyber-physical active distribution system,CPADS)显得至关重要。基于此,提出计及混合通信组网的CPADS协调规划方法。首先,将信息域混合通信组网策略和物理域主动配电系统时空运行策略有机统一,建立旨在最小化投资–运行总成本的CPADS协调规划模型。具体而言,综合考虑主动控制设备投资成本、有线/无线组网投资成本、网损成本、弃光成本、失负荷成本、电压偏差优化成本等建立多维度投资运行目标函数。然后,综合考虑物理域主动控制设备的选址或选型、信息域有线组网和无线组网的差异性构建投资约束;充分考虑设备主动控制策略、电压偏差等构建CPADS时空运行约束。最后,综合考虑场景概率分布不确定性置信度集合的1-范数和∞-范数约束,将所提规划模型重构为一个数据驱动下的分布鲁棒协调规划框架,并利用列与约束生成(columnandconstraintgeneration,CCG)算法迭代求解。展开更多
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.
基金Project(2009CB219703) supported by the National Basic Research Program of ChinaProject(2011AA05A117) supported by the National High Technology Research and Development Program of China
文摘In order to form an algorithm for distribution network routing,an automatic routing method of distribution network planning was proposed based on the shortest path.The problem of automatic routing was divided into two steps in the method:the first step was that the shortest paths along streets between substation and load points were found by the basic ant colony algorithm to form a preliminary radial distribution network,and the second step was that the result of the shortest path was used to initialize pheromone concentration and pheromone updating rules to generate globally optimal distribution network.Cases studies show that the proposed method is effective and can meet the planning requirements.It is verified that the proposed method has better solution and utility than planning method based on the ant colony algorithm.
文摘The models, methods and their application experiences of a practical GIS(geographic information system)-based computer decision-making support system of urban power distribution network planning with seven subsystems,termed CNP,are described.In each subsystem there is at least one or one set of practical mathematical methobs.Some new models and mathematical methods have been introduced.In the development of CNP the idea of cognitive system engineering has been insisted on,which claims that human and computer intelligence should be combined together to solve the complex engineering problems cooperatively.Practical applications have shown that not only the optimal plan can be automatically reached with many complicated factors considered, but also the computation,analysis and graphic drawing burden can be released considerably.
文摘At the present stage, the distribution network has been in a relatively low voltage position, has become the main medium between power supply companies, customers and distribution system users, the working conditions of distribution network system and the distribution equipment quality has high requirements, so by improving the grid requirements to improve the security of the distribution network, become Chinas current power development transition stage must attach great importance to the development goals, is also the key measures to ensure user safety. With the continuous growth of the national economy, Chinas domestic power industry development has been improved accordingly, its level is gradually to developed countries and local governments, this is mainly due to the distribution network construction, construction, management operation accumulated valuable experience, learned a lot of lessons and made significant progress, but over time, Chinas domestic distribution network operation calculation specification also need to be modified with the process of time, it is an important measure to improve the level of distribution network management, but also to reduce the negative impact and play a good role.
文摘Theauthor proposes a dual layer source grid load storage collaborative planning model based on Benders decomposition to optimize the low-carbon and economic performance of the distribution network.The model plans the configuration of photovoltaic(3.8 MW),wind power(2.5 MW),energy storage(2.2 MWh),and SVC(1.2 Mvar)through interaction between upper and lower layers,and modifies lines 2–3,8–9,etc.to improve transmission capacity and voltage stability.The author uses normal distribution and Monte Carlo method to model load uncertainty,and combines Weibull distribution to describe wind speed characteristics.Compared to the traditional three-layer model(TLM),Benders decomposition-based two-layer model(BLBD)has a 58.1%reduction in convergence time(5.36 vs.12.78 h),a 51.1%reduction in iteration times(23 vs.47 times),a 8.07%reduction in total cost(12.436 vs.13.528 million yuan),and a 9.62%reduction in carbon emissions(12,456 vs.13,782 t).After optimization,the peak valley difference decreased from4.1 to 2.9MW,the renewable energy consumption rate reached 93.4%,and the energy storage efficiency was 87.6%.Themodel has been validated in the IEEE 33 node system,demonstrating its superiority in terms of economy,low-carbon,and reliability.
基金The State Grid under Project,Grant/Award Number:5700-202118195A-0-0-00。
文摘With increasing electricity demand and large-scale stochastic charging of electric vehicles(EVs),distribution networks face inevitable shortage of transfer capability,bringing new challenges to distribution network planning(DNP).Dynamic thermal rating(DTR),which evaluates the equipment rating based on actual meteorological conditions and equipment thermal state,can enhance the equipment transfer capability to meet the increasing load demand.In this paper,we propose a model considering the active response of EVs,and a bi-level DNP model incorporating the DTR of cables and transformers,in the upper level,the Prim algorithm is embedded into the particle swarm optimisation(PSO)algorithm to obtain an initial grid topology;in the lower level,types of cables and transformers as well as the installation of DTR equipment are determined,second-order cone(SOC)relaxation and linearisation of the variables product are then carried out to meet the non-linear constraints of cables and transformers,and the upper and lower models are solved in an iterative manner.Case studies demonstrate that the implementation of DTR effectively enhances the transfer capability of cables and transformers,saving 4.8%investment cost while ensuring 96%uplift of power supply.Besides,with 90%active response rate of EVs,total cost can be further reduced.
基金This research was funded by“Chunhui Program”Collaborative Scientific Research Project of the Ministry of Education of the People’s Republic of China(Project No.HZKY20220242)the S&T Program of Hebei(Project No.225676163GH).
文摘Rational distribution network planning optimizes power flow distribution,reduces grid stress,enhances voltage quality,promotes renewable energy utilization,and reduces costs.This study establishes a distribution network planning model incorporating distributed wind turbines(DWT),distributed photovoltaics(DPV),and energy storage systems(ESS).K-means++is employed to partition the distribution network based on electrical distance.Considering the spatiotemporal correlation of distributed generation(DG)outputs in the same region,a joint output model of DWT and DPV is developed using the Frank-Copula.Due to the model’s high dimensionality,multiple constraints,and mixed-integer characteristics,bilevel programming theory is utilized to structure the model.The model is solved using a mixed-integer particle swarmoptimization algorithm(MIPSO)to determine the optimal location and capacity of DG and ESS integrated into the distribution network to achieve the best economic benefits and operation quality.The proposed bilevel planning method for distribution networks is validated through simulations on the modified IEEE 33-bus system.The results demonstrate significant improvements,with the proposedmethod reducing the annual comprehensive cost by 41.65%and 13.98%,respectively,compared to scenarios without DG and ESS or with only DG integration.Furthermore,it reduces the daily average voltage deviation by 24.35%and 10.24%and daily network losses by 55.72%and 35.71%.
基金The authors received specific funding for State Grid Corporation Headquarters Project Support,Key Technologies and Applications of Planning and Decision-Making Based on the Full Cost Chain of the Power Grid,Grant No.5205331800001.
文摘For facing the challenges brought by large-scale renewable energy having access to the system and considering the key technologies of energy Internet,it is very necessary to put forward the location method of distribution network equipment and capacity from the perspective of life cycle cost.Compared with the traditional energy network,the equipment capacity problem of energy interconnected distribution network which involves in electricity network,thermal energy network and natural gas network is comprehensively considered in this paper.On this basis,firstly,the operation architecture of energy interconnected distribution network is designed.Secondly,taking the grid connection location and configuration capacity of key equipment in the system as the control variables and the operation cost of system comprehensive planning in the whole life cycle as the goal,the equipment location and capacity optimization model of energy interconnected distribution network is established.Finally,an IEEE 33 bus energy mutual distribution grid system is taken for example analysis,and the improved chaotic particle swarmoptimization algorithm is used to solve it.The simulation results show that the method proposed in this paper is suitable for the equipment location and capacity planning of energy interconnected distribution network,and it can effectively improve the social and economic benefits of system operation.
基金financial supports and the strategic platform for innovation&research provided by Danish national project iPower.
文摘This paper presents a novel approach for electrical distribution network expansion planning using multi-objective particle swarm optimization (PSO). The optimization objectives are: investment and operation cost, energy losses cost, and power congestion cost. A two-phase multi-objective PSO algorithm is employed to solve this optimization problem, which can accelerate the convergence and guarantee the diversity of Pareto-optimal front set as well. The feasibility and effectiveness of both the proposed multi-objective planning approach and the improved multi-objective PSO have been verified by the 18-node typical system.
基金supported by the Key Program of National Natural Science Foundation of China under Grant 52130702.
文摘In order to cope with the global environmental crisis caused by energy generation and achieve carbon neutrality,it is imperative to promote a new power system dominated by renewable energy sources(RESs).This paper focuses on the uncertainty of RESs and the distribution characteristics of carbon emission flows(CEFs),and studies the low-carbon operation and power system planning problem.Firstly,this paper extends the uncertainty of RES to the meteorological field and establishes meteorological robust constraints of photovoltaic(PV)generation.Based on the CEF theory,the carbon transmission trajectory is accurately delineated to improve the operation of power system.Considering further constraints from the power flow,CEF,and component operation characteristics of the active distribution network(ADN),this paper formulates a low-carbon joint planning model of ADN with PV,battery energy storage system(BESS),and distributed gas generator(DGG),taking into account economy and carbon reduction.In the case study,the low-carbon planning and operation scheme are analyzed in detail across multiple dimensions including time and space.The solution results show that the planning model can effectively leverage the low-carbon performance of PV and BESS,and improve the distribution of CEF.Through case comparison,the model can also efficiently reduce the total cost of the system and enhance carbon emission reduction benefits by 35.10 to 41.04%.
基金supported by the National Natural Science Foundation of China(52177103).
文摘More electricity utilities will participate in the investment and operation of private distributed generations(DGs)while the local power company is responsible for the reinforcement of lines and DGs,as well.How to achieve the maximum benefits among various utilities,including the power company,is a task in the expansion planning of distribution networks.To solve the market-oriented planning problem,virtual peer to peer(P2P)trading is integrated and modeled in the new expansion planning of distribution networks.First,virtual market transaction optimization among prosumers is formulated.Second,the distributed regional marginal price(DLMP)is calculated by the optimal operation model,which contributed to the network usage charge(NUC)and then integrated in the expansion planning model.Case studies are performed and indicate the integrated P2P transaction strategy could improve local load consumption,while reducing the load rate of lines,as well as the electricity cost of users.Besides,the total planning cost paid by the power company could be saved via prosumers’investment and P2P transactions and the factors affecting power company’s profit are also classified in multi-investor planning of distribution networks.
基金This work was supported in part by the Science and Technology Project of SGCC under Grant No.PD71-18-023.
文摘The health status of distribution equipment and networks is not considered directly in existing distribution network planning methods.In order to effectively consider the health status and deal with the risk associated with load and renewable generation uncertainties,this paper presents a new optimal expansion planning approach for distribution network(EPADN)incorporating equipment’s health index(HI)and non-network solutions(NNSs).HI and relevant risk are used to help develop the optimal equipment replacement strategy and temporary NNSs are considered as promising options for handling the uncertainties of load growth,reliability requirements of power supply and output of distributed energy resources(DERs)at a lower cost than network alternatives.An EPADN model using network solutions(NSs)and NNSs is proposed.The planning objectives of the proposed model are safety,reliability,economy,and‘greenness’that are also the meaning of distribution network HI.A method integrating an improved niche genetic algorithm(INGA)and a spanning tree algorithm(STA)is fitted to solve the model presented here for real sized networks with a manageable computational cost.Simulation results of an actual 22-node distribution network in China,illustrate the effectiveness of the proposed approach.
基金supported in part by the National Key R&D Program of China (No.2016YFB0900400)in part by National Natural Science Foundation of China (51907043)in part by the Fundamental Research Funds for the Central Universities (JZ2020HGTB0040,PA2019GDPK0085).
文摘The concept of DG clusters is introduced with highly penetrated integration of distributed generation(DG)into active distribution networks(ADNs).DG clusters are referred to as parts of an ADN,including DGs,distribution lines and loads.The formation of DG clusters helps to optimally dispatch DG outputs within ADNs.In this regard,an integrated planning strategy of ADNs and DGs in cluster(IPNDGC)is proposed.In order to guarantee that the planning strategy meets the reliability requirements,a reliability assessment is considered in the proposed model.However,reliability assessment is generally accomplished according to a fixed network topology and known DG allocation,which makes it difficult to integrate reliability into planning models.To deal with this difficulty,a novel formulation method for reliability assessment is proposed considering the network topology uncertainties and isolated operating probabilities of DG clusters.The reliability index(RI)represented by expected customer interruption cost(ECOST)is employed in the proposed planning model.The planning model is formulated as a mixed integer second order conic programming planning model.An actual distribution system is employed to illustrate the accuracy and efficiency of the proposed planning model.
基金supported by the National Natural Science Foundation of China(52111530067)the Academy of Finland project“Robust Distribution Network Planning to Facilitate Electric Vehicle Integration”(341473).
文摘Large integration of electric vehicles(EVs)brings uncertainties and challenges for distribution networks.Reliability and allocation of charging systems(charging stations and piles)need strong support from the distribution network,whose expansion planning would be also greatly impacted by the incremental load from the charging system.To address this issue,a collaborative planning scheme of the EV charging system and distribution networks that combines economic and reliability benefits is proposed,which is formulated as a two-stage distributionally robust optimization model considering source-load uncertainties.First,a candidate EVCS planning scheme is obtained using queuing theory.Then,system reliability is quantified by adopting the average energy not supplied index and correlated integrated into the two-stage mixed-integer linear programming model.Finally,it is solved to perform distributionally robust expansion planning by the column and constraint generation algorithm.Effectiveness and scalability of the proposed planning method are illustrated by numerical case studies.Results indicate the planning scheme that considers economic and reliability benefit can perform better than traditional optimization methods.
文摘With the increased integration of photovoltaic(PV)power generation into active distribution networks,the operational challenges and their complexities are increased.Such networks need detailed characterization PV systems under multiple operating conditions to understand true impacts.This paper presents a new mathematical model for a PV system to capture detailed effects of PV systems.The proposed model incorporates state transitions of components in a PV system and captures effects of insolation variations.The paper performs a reliability assessment incorporating PV systems at resource locations.The results suggest that the reliability performance of an active distribution network at stressed operating conditions might be influenced by the high penetration of PV system.Reliability performance of distribution networks that are high penetrated with PV systems can be affected by cloudy effects resulting from insolation variations.The proposed model can be used to quantify the level of reduction in reliability,resulting with cloudy effects.
基金supported by the National Natural Science Foundation of China (No. 51977133)
文摘Feeder routing and reliability assessment are essential for effective distribution network planning.However,excessively long feeders can lead to increased costs and decreased reliability.To enhance economic and reliability performance,this paper proposes a reliability-centered planning method for feeder routing and conductor sizing.Specifically,a graph-based fictitious power flow model is constructed within the geographic graph.Overlapping feeder routes powered by fictitious power flows from multiple sources are designated as line connection.These feeder routes,constrained by the geographic graph,are interconnected via line connection to form a mesh network structure.To meet the requirements of reliability-centered optimization,the affiliation variables are introduced.Based on the affiliation variables,the algebraic formula is embedded into the fictitious power flow model to enable the calculation of reliability during the optimization process.By incorporating customized reliability-related constraints in the model,the specific reliability objectives can be achieved.In addition,the non-convex terms in the fictitious power flow model are relaxed into convex forms,and certain variable products are replaced with auxiliary variables,allowing the problem to be solved by an off-the-shelf solver.Finally,the proposed method is tested on two case studies,demonstrating its effectiveness.
文摘为充分提高配电系统调度和控制的灵活性,建设和落实以智能化和主动化为导向,以信息通信技术为支撑的信息物理主动配电系统(cyber-physical active distribution system,CPADS)显得至关重要。基于此,提出计及混合通信组网的CPADS协调规划方法。首先,将信息域混合通信组网策略和物理域主动配电系统时空运行策略有机统一,建立旨在最小化投资–运行总成本的CPADS协调规划模型。具体而言,综合考虑主动控制设备投资成本、有线/无线组网投资成本、网损成本、弃光成本、失负荷成本、电压偏差优化成本等建立多维度投资运行目标函数。然后,综合考虑物理域主动控制设备的选址或选型、信息域有线组网和无线组网的差异性构建投资约束;充分考虑设备主动控制策略、电压偏差等构建CPADS时空运行约束。最后,综合考虑场景概率分布不确定性置信度集合的1-范数和∞-范数约束,将所提规划模型重构为一个数据驱动下的分布鲁棒协调规划框架,并利用列与约束生成(columnandconstraintgeneration,CCG)算法迭代求解。
