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 light of the situation that the nationwide interconnection of power networks in China in the coming years will take shape, it is imperative to emphasize the importance of setting up rational power network configura...In light of the situation that the nationwide interconnection of power networks in China in the coming years will take shape, it is imperative to emphasize the importance of setting up rational power network configuration. Combined with the characteristics of regional power networks in China, problems in network planning that need to be solved are put forward in this paper, such as, the access of power plants to grid by layers and zones, the share of external power in the load of local network, the power network configuration study in-depth in planning and design stage, and enforcement of receiving-end power network trunk etc. The background of these problems and their countermeasures are also analyzed in the paper.展开更多
Grid-scale energy storage systems provide effective solutions to address challenges such as supply-load imbalances and voltage violations resulting from the non-coinciding nature of renewable energy generation and pea...Grid-scale energy storage systems provide effective solutions to address challenges such as supply-load imbalances and voltage violations resulting from the non-coinciding nature of renewable energy generation and peak demand incidents.While battery and hydrogen storage are commonly used for peak shaving,ice-based thermal energy storage systems(TESSs)offer a direct way to reduce cooling loads without electrical conversion.This paper presents a multi-objective planning framework that optimizes TESS dispatch,network topology,and photovoltaic(PV)inverter reactive power support to address operational issues in active distribution networks.The objectives of the proposed scheme include minimizing peak demand,voltage deviations,and PV inverter VAr dependency.The mixed-integer nonlinear programming problem is solved using a Pareto-based multi-objective particle swarm optimization(MOPSO)method.The MATLAB-OpenDSS simulations for a modified IEEE-123 bus system show a 7.1%reduction in peak demand,a 13%reduction in voltage deviation,and a 52%drop in PV inverter VAr usage.The obtained solutions confirm minimal operational stress on control devices such as switches and PV inverters.Thus,unlike earlier studies,this work combines all three strategies to offer an effective solution for the operational planning of the active distribution network.展开更多
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
Rural power network planning is a complicated nonlinear optimized combination problem which based on load forecasting results, and its actual load is affected by many uncertain factors, which influenced optimization r...Rural power network planning is a complicated nonlinear optimized combination problem which based on load forecasting results, and its actual load is affected by many uncertain factors, which influenced optimization results of rural power network planning. To solve the problems, the interval algorithm was used to modify the initial search method of uncertainty load mathematics model in rural network planning. Meanwhile, the genetic/tabu search combination algorithm was adopted to optimize the initialized network. The sample analysis results showed that compared with the certainty planning, the improved method was suitable for urban medium-voltage distribution network planning with consideration of uncertainty load and the planning results conformed to the reality.展开更多
A distribution network plays an extremely important role in the safe and efficient operation of a power grid.As the core part of a power grid’s operation,a distribution network will have a significant impact on the s...A distribution network plays an extremely important role in the safe and efficient operation of a power grid.As the core part of a power grid’s operation,a distribution network will have a significant impact on the safety and reliability of residential electricity consumption.it is necessary to actively plan and modify the distribution network’s structure in the power grid,improve the quality of the distribution network,and optimize the planning of the distribution network,so that the network can be fully utilized to meet the needs of electricity consumption.In this paper,a distribution network grid planning algorithm based on the reliability of electricity consumption was completed using ant colony algorithm.For the distribution network structure planning of dual power sources,the parallel ant colony algorithm was used to prove that the premise of parallelism is the interactive process of ant colonies,and the dual power distribution network structure model is established based on the principle of the lowest cost.The artificial ants in the algorithm were compared with real ants in nature,and the basic steps and working principle of the ant colony optimization algorithm was studied with the help of the travelling salesman problem(TSP).Then,the limitations of the ant colony algorithm were analyzed,and an improvement strategy was proposed by using python for digital simulation.The results demonstrated the reliability of model-building and algorithm improvement.展开更多
In order to resolve the coordination and optimization of the power network planning effectively, on the basis of introducing the concept of power intelligence center (PIC), the key factor power flow, line investment a...In order to resolve the coordination and optimization of the power network planning effectively, on the basis of introducing the concept of power intelligence center (PIC), the key factor power flow, line investment and load that impact generation sector, transmission sector and dispatching center in PIC were analyzed and a multi-objective coordination optimal model for new power intelligence center (NPIC) was established. To ensure the reliability and coordination of power grid and reduce investment cost, two aspects were optimized. The evolutionary algorithm was introduced to solve optimal power flow problem and the fitness function was improved to ensure the minimum cost of power generation. The gray particle swarm optimization (GPSO) algorithm was used to forecast load accurately, which can ensure the network with high reliability. On this basis, the multi-objective coordination optimal model which was more practical and in line with the need of the electricity market was proposed, then the coordination model was effectively solved through the improved particle swarm optimization algorithm, and the corresponding algorithm was obtained. The optimization of IEEE30 node system shows that the evolutionary algorithm can effectively solve the problem of optimal power flow. The average load forecasting of GPSO is 26.97 MW, which has an error of 0.34 MW compared with the actual load. The algorithm has higher forecasting accuracy. The multi-objective coordination optimal model for NPIC can effectively process the coordination and optimization problem of power network.展开更多
The paper mainly focuses on the network planning and optimization problem in the 5G telecommunication system based on the numerical investigation.There have been two portions of this work,such as network planning for ...The paper mainly focuses on the network planning and optimization problem in the 5G telecommunication system based on the numerical investigation.There have been two portions of this work,such as network planning for efficient network models and optimization of power allocation in the 5G network.The radio network planning process has been completed based on a specific area.The data rate requirement can be solved by allowing the densification of the system by deploying small cells.The radio network planning scheme is the indispensable platform in arranging a wireless network that encounters convinced coverage method,capacity,and Quality of Service necessities.In this study,the eighty micro base stations and two-hundred mobile stations are deployed in the-15km×15km wide selected area in the Yangon downtown area.The optimization processes were also analyzed based on the source and destination nodes in the 5G network.The base stations’location is minimized and optimized in a selected geographical area with the linear programming technique and analyzed in this study.展开更多
This paper proposes to use the power system simulation software CYME to plan, model and simulate for an actual distribution network for improving the reliability and efficiency, enhancing the efficiency and capacity, ...This paper proposes to use the power system simulation software CYME to plan, model and simulate for an actual distribution network for improving the reliability and efficiency, enhancing the efficiency and capacity, simulating the abnormal condition of distribution network, and presenting operation program of safe, reliable and having simulation record statements. The modeling simulation results show that the software module has lots of advantages including high accuracy, ideal reliability, powerful practicality in simulation and analysis of distribution network, it only need to create once model, the model can sufficiently satisfy multifarious types of simulation analysis required for the distribution network planning.展开更多
The capacitive reactive power reversal in the urban distribution grid is increasingly prominent at the period of light load in the last years.In severe cases,it will endanger the security and stability of power grid.T...The capacitive reactive power reversal in the urban distribution grid is increasingly prominent at the period of light load in the last years.In severe cases,it will endanger the security and stability of power grid.This paper presents an optimal reactive power compensation method of distribution network to prevent reactive power reverse.Firstly,an integrated reactive power planning(RPP)model with power factor constraints is established.Capacitors and reactors are considered to be installed in the distribution system at the same time.The objective function is the cost minimization of compensation and real power loss with transformers and lines during the planning period.Nodal power factor limits and reactor capacity constraints are new constraints.Then,power factor sensitivity with respect to reactive power is derived.An improved genetic algorithm by power factor sensitivity is used to solve the model.The optimal locations and sizes of reactors and capacitors can avoid reactive power reversal and power factor exceeding the limit.Finally,the effectiveness of the model and algorithm is proven by a typical high-voltage distribution network.展开更多
This paper introduces the selection and scheme demonstration of higher voltage class in Northwest ChinaPower Network, and conclusions made by main research institutes and experts’ comments.[
A problem of upgrading to the Next Generation Wireless Network (NGWN) is backward compatibility with pre-existing networks, the cost and operational benefit of gradually enhancing networks, by replacing, upgrading and...A problem of upgrading to the Next Generation Wireless Network (NGWN) is backward compatibility with pre-existing networks, the cost and operational benefit of gradually enhancing networks, by replacing, upgrading and installing new wireless network infrastructure elements that can accommodate both voice and data demand. In this paper, we propose a new genetic algorithm has double population to solve Multi-Objectives Optimal of Upgrading Infrastructure (MOOUI) problem in NGWN. We modeling network topology for MOOUI problem has two levels in which mobile users are sources and both base stations and base station controllers are concentrators. Our objective function is the sources to concentrators connectivity cost as well as the cost of the installation, connection, replacement, and capacity upgrade of infrastructure equipment. We generate two populations satisfy constraints and combine them to build solutions and evaluate the performance of my algorithm with data randomly generated. Numerical results show that our algorithm is a promising approach to solve this problem.展开更多
According to the population, area and economy development of Shanghai City, this paper introduces the load forecast of the city and points out that the development of urban power network should adapt the development o...According to the population, area and economy development of Shanghai City, this paper introduces the load forecast of the city and points out that the development of urban power network should adapt the development of its economy. In this paper, the developing targets of Shanghai power network are also presented.展开更多
This paper uses a novel scenario generation method for tackling the uncertainties of wind power in the transmission network expansion planning(TNEP)problem.A heuristic moment matching(HMM)method is first applied to ge...This paper uses a novel scenario generation method for tackling the uncertainties of wind power in the transmission network expansion planning(TNEP)problem.A heuristic moment matching(HMM)method is first applied to generate the typical scenarios for capturing the stochastic features of wind power,including expectation,standard deviation,skewness,kurtosis,and correlation of multiple wind farms.Then,based on the typical scenarios,a robust TNEP problem is presented and formulated.The solution of the problem is robust against all the scenarios that represent the stochastic features of wind power.Three test systems are used to verify the HMM method and is compared against Taguchi’s Orthogonal Array(OA)method.The simulation results show that the HMM method has better performance than the OA method in terms of the trade-off between robustness and economy.Additionally,the main factors influencing the planning scheme are studied,including the number of scenarios,wind farm capacity,and penalty factors,which provide a reference for system operators choosing parameters.展开更多
With the advancement of clean heating projects and the integration of large-scale distributed heat pumps into rural distribution networks in northern China,power grid companies face tremendous pressure to invest in po...With the advancement of clean heating projects and the integration of large-scale distributed heat pumps into rural distribution networks in northern China,power grid companies face tremendous pressure to invest in power grid upgrades,which bring opportunities for renewable power generation integration.The combination of heating by distributed renewable energy with the flexible operation of heat pumps is a feasible alternative for dealing with grid reinforcement challenges resulting from heating electrification.In this paper,a mathematical model of the collaborative planning of distributed wind power generation(DWPG)and distribution network with large-scale heat pumps is developed.In this model,the operational flexibility of the heat pump load is fully considered and the requirements of a comfortable indoor temperature are met.By applying this model,the goals of not only increasing the profit of DWPG but also reducing the cost of the power grid upgrade can be achieved.展开更多
In this paper,we jointly design the power control and position dispatch for Multi-Unmanned Aerial Vehicle(UAV)-enabled communication in Device-to-Device(D2D)networks.Our objective is to maximize the total transmission...In this paper,we jointly design the power control and position dispatch for Multi-Unmanned Aerial Vehicle(UAV)-enabled communication in Device-to-Device(D2D)networks.Our objective is to maximize the total transmission rate of Downlink Users(DUs).Meanwhile,the Quality of Service(QoS)of all D2D users must be satisfied.We comprehensively considered the interference among D2D communications and downlink transmissions.The original problem is strongly non-convex,which requires high computational complexity for traditional optimization methods.And to make matters worse,the results are not necessarily globally optimal.In this paper,we propose a novel Graph Neural Networks(GNN)based approach that can map the considered system into a specific graph structure and achieve the optimal solution in a low complexity manner.Particularly,we first construct a GNN-based model for the proposed network,in which the transmission links and interference links are formulated as vertexes and edges,respectively.Then,by taking the channel state information and the coordinates of ground users as the inputs,as well as the location of UAVs and the transmission power of all transmitters as outputs,we obtain the mapping from inputs to outputs through training the parameters of GNN.Simulation results verified that the way to maximize the total transmission rate of DUs can be extracted effectively via the training on samples.Moreover,it also shows that the performance of proposed GNN-based method is better than that of traditional means.展开更多
Because of the randomness of wind power and photovoltaic(PV)output of new energy bases,the problem of peak regulation capability and voltage stability of ultra-high voltage direct current(UHVDC)transmission lines,we p...Because of the randomness of wind power and photovoltaic(PV)output of new energy bases,the problem of peak regulation capability and voltage stability of ultra-high voltage direct current(UHVDC)transmission lines,we proposed an optimum allocation method of installed capacity of the solar-thermal power station based on chance constrained programming in this work.Firstly,we established the uncertainty model of wind power and PV based on the chance constrained planning theory.Then we used the K-medoids clusteringmethod to cluster the scenarios considering the actual operation scenarios throughout the year.Secondly,we established the optimal configuration model based on the objective function of the strongest transient voltage stability and the lowest overall cost of operation.Finally,by quantitative analysis of actual wind power and photovoltaic new energy base,this work verified the feasibility of the proposed method.As a result of the simulations,we found that using the optimal configuration method of solar-thermal power stations could ensure an accurate allocation of installed capacity.When the installed capacity of the solar-thermal power station is 1×106 kW,the transient voltage recovery index(TVRI)is 0.359,which has a strong voltage support capacity for the system.Based on the results of this work,the optimal configuration of the installed capacity of the solar-thermal power plant can improve peak shaving performance,transient voltage support capability,and new energy consumption while satisfying the Direct Current(DC)outgoing transmission premise.展开更多
This paper describes the study analysis performed to evaluate the available and potential solutions to control the highly increasing short circuit （SC） levels in Kuwait power system. The real Kuwait High Voltage （H...This paper describes the study analysis performed to evaluate the available and potential solutions to control the highly increasing short circuit （SC） levels in Kuwait power system. The real Kuwait High Voltage （HV） network was simulated to examine different measures at both 275 kV and 132 kV stations. The simulation results show that the short circuit currents exceed the permissible levels （40 kA in the 132 kV network and 63 kA in the 275 kV network） in some specific points. The examined measures include the a study on changing the neutral point policy, changing some lines from alternating current （AC） to direct current （DC）, dividing specific bus bars in some generating stations and applying current limiters. The paper also presents a new plan for the transmission network in order to manage the expected increase in short circuit levels in the future.展开更多
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.
文摘In light of the situation that the nationwide interconnection of power networks in China in the coming years will take shape, it is imperative to emphasize the importance of setting up rational power network configuration. Combined with the characteristics of regional power networks in China, problems in network planning that need to be solved are put forward in this paper, such as, the access of power plants to grid by layers and zones, the share of external power in the load of local network, the power network configuration study in-depth in planning and design stage, and enforcement of receiving-end power network trunk etc. The background of these problems and their countermeasures are also analyzed in the paper.
基金supported by the US Appalachian Regional Commission(ARC)under Grant MU-21579-23。
文摘Grid-scale energy storage systems provide effective solutions to address challenges such as supply-load imbalances and voltage violations resulting from the non-coinciding nature of renewable energy generation and peak demand incidents.While battery and hydrogen storage are commonly used for peak shaving,ice-based thermal energy storage systems(TESSs)offer a direct way to reduce cooling loads without electrical conversion.This paper presents a multi-objective planning framework that optimizes TESS dispatch,network topology,and photovoltaic(PV)inverter reactive power support to address operational issues in active distribution networks.The objectives of the proposed scheme include minimizing peak demand,voltage deviations,and PV inverter VAr dependency.The mixed-integer nonlinear programming problem is solved using a Pareto-based multi-objective particle swarm optimization(MOPSO)method.The MATLAB-OpenDSS simulations for a modified IEEE-123 bus system show a 7.1%reduction in peak demand,a 13%reduction in voltage deviation,and a 52%drop in PV inverter VAr usage.The obtained solutions confirm minimal operational stress on control devices such as switches and PV inverters.Thus,unlike earlier studies,this work combines all three strategies to offer an effective solution for the operational planning of the active distribution network.
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Rural power network planning is a complicated nonlinear optimized combination problem which based on load forecasting results, and its actual load is affected by many uncertain factors, which influenced optimization results of rural power network planning. To solve the problems, the interval algorithm was used to modify the initial search method of uncertainty load mathematics model in rural network planning. Meanwhile, the genetic/tabu search combination algorithm was adopted to optimize the initialized network. The sample analysis results showed that compared with the certainty planning, the improved method was suitable for urban medium-voltage distribution network planning with consideration of uncertainty load and the planning results conformed to the reality.
文摘A distribution network plays an extremely important role in the safe and efficient operation of a power grid.As the core part of a power grid’s operation,a distribution network will have a significant impact on the safety and reliability of residential electricity consumption.it is necessary to actively plan and modify the distribution network’s structure in the power grid,improve the quality of the distribution network,and optimize the planning of the distribution network,so that the network can be fully utilized to meet the needs of electricity consumption.In this paper,a distribution network grid planning algorithm based on the reliability of electricity consumption was completed using ant colony algorithm.For the distribution network structure planning of dual power sources,the parallel ant colony algorithm was used to prove that the premise of parallelism is the interactive process of ant colonies,and the dual power distribution network structure model is established based on the principle of the lowest cost.The artificial ants in the algorithm were compared with real ants in nature,and the basic steps and working principle of the ant colony optimization algorithm was studied with the help of the travelling salesman problem(TSP).Then,the limitations of the ant colony algorithm were analyzed,and an improvement strategy was proposed by using python for digital simulation.The results demonstrated the reliability of model-building and algorithm improvement.
基金Project (70671039) supported by the National Natural Science Foundation of China
文摘In order to resolve the coordination and optimization of the power network planning effectively, on the basis of introducing the concept of power intelligence center (PIC), the key factor power flow, line investment and load that impact generation sector, transmission sector and dispatching center in PIC were analyzed and a multi-objective coordination optimal model for new power intelligence center (NPIC) was established. To ensure the reliability and coordination of power grid and reduce investment cost, two aspects were optimized. The evolutionary algorithm was introduced to solve optimal power flow problem and the fitness function was improved to ensure the minimum cost of power generation. The gray particle swarm optimization (GPSO) algorithm was used to forecast load accurately, which can ensure the network with high reliability. On this basis, the multi-objective coordination optimal model which was more practical and in line with the need of the electricity market was proposed, then the coordination model was effectively solved through the improved particle swarm optimization algorithm, and the corresponding algorithm was obtained. The optimization of IEEE30 node system shows that the evolutionary algorithm can effectively solve the problem of optimal power flow. The average load forecasting of GPSO is 26.97 MW, which has an error of 0.34 MW compared with the actual load. The algorithm has higher forecasting accuracy. The multi-objective coordination optimal model for NPIC can effectively process the coordination and optimization problem of power network.
基金This work was fully supported by U Nyi Hla Nge Foundation at Yangon Technological University,Gyogone,Insein PO,11011,Yangon,Myanmar。
文摘The paper mainly focuses on the network planning and optimization problem in the 5G telecommunication system based on the numerical investigation.There have been two portions of this work,such as network planning for efficient network models and optimization of power allocation in the 5G network.The radio network planning process has been completed based on a specific area.The data rate requirement can be solved by allowing the densification of the system by deploying small cells.The radio network planning scheme is the indispensable platform in arranging a wireless network that encounters convinced coverage method,capacity,and Quality of Service necessities.In this study,the eighty micro base stations and two-hundred mobile stations are deployed in the-15km×15km wide selected area in the Yangon downtown area.The optimization processes were also analyzed based on the source and destination nodes in the 5G network.The base stations’location is minimized and optimized in a selected geographical area with the linear programming technique and analyzed in this study.
文摘This paper proposes to use the power system simulation software CYME to plan, model and simulate for an actual distribution network for improving the reliability and efficiency, enhancing the efficiency and capacity, simulating the abnormal condition of distribution network, and presenting operation program of safe, reliable and having simulation record statements. The modeling simulation results show that the software module has lots of advantages including high accuracy, ideal reliability, powerful practicality in simulation and analysis of distribution network, it only need to create once model, the model can sufficiently satisfy multifarious types of simulation analysis required for the distribution network planning.
文摘The capacitive reactive power reversal in the urban distribution grid is increasingly prominent at the period of light load in the last years.In severe cases,it will endanger the security and stability of power grid.This paper presents an optimal reactive power compensation method of distribution network to prevent reactive power reverse.Firstly,an integrated reactive power planning(RPP)model with power factor constraints is established.Capacitors and reactors are considered to be installed in the distribution system at the same time.The objective function is the cost minimization of compensation and real power loss with transformers and lines during the planning period.Nodal power factor limits and reactor capacity constraints are new constraints.Then,power factor sensitivity with respect to reactive power is derived.An improved genetic algorithm by power factor sensitivity is used to solve the model.The optimal locations and sizes of reactors and capacitors can avoid reactive power reversal and power factor exceeding the limit.Finally,the effectiveness of the model and algorithm is proven by a typical high-voltage distribution network.
文摘This paper introduces the selection and scheme demonstration of higher voltage class in Northwest ChinaPower Network, and conclusions made by main research institutes and experts’ comments.[
文摘A problem of upgrading to the Next Generation Wireless Network (NGWN) is backward compatibility with pre-existing networks, the cost and operational benefit of gradually enhancing networks, by replacing, upgrading and installing new wireless network infrastructure elements that can accommodate both voice and data demand. In this paper, we propose a new genetic algorithm has double population to solve Multi-Objectives Optimal of Upgrading Infrastructure (MOOUI) problem in NGWN. We modeling network topology for MOOUI problem has two levels in which mobile users are sources and both base stations and base station controllers are concentrators. Our objective function is the sources to concentrators connectivity cost as well as the cost of the installation, connection, replacement, and capacity upgrade of infrastructure equipment. We generate two populations satisfy constraints and combine them to build solutions and evaluate the performance of my algorithm with data randomly generated. Numerical results show that our algorithm is a promising approach to solve this problem.
文摘According to the population, area and economy development of Shanghai City, this paper introduces the load forecast of the city and points out that the development of urban power network should adapt the development of its economy. In this paper, the developing targets of Shanghai power network are also presented.
基金supported in part by the National Natural Science Foundation of China under Grant No.51377027The National Basic Research Program of China under Grant No.2013CB228205by Innovation Project of Guangxi Graduate Education under Grant No.YCSZ2015053.
文摘This paper uses a novel scenario generation method for tackling the uncertainties of wind power in the transmission network expansion planning(TNEP)problem.A heuristic moment matching(HMM)method is first applied to generate the typical scenarios for capturing the stochastic features of wind power,including expectation,standard deviation,skewness,kurtosis,and correlation of multiple wind farms.Then,based on the typical scenarios,a robust TNEP problem is presented and formulated.The solution of the problem is robust against all the scenarios that represent the stochastic features of wind power.Three test systems are used to verify the HMM method and is compared against Taguchi’s Orthogonal Array(OA)method.The simulation results show that the HMM method has better performance than the OA method in terms of the trade-off between robustness and economy.Additionally,the main factors influencing the planning scheme are studied,including the number of scenarios,wind farm capacity,and penalty factors,which provide a reference for system operators choosing parameters.
文摘With the advancement of clean heating projects and the integration of large-scale distributed heat pumps into rural distribution networks in northern China,power grid companies face tremendous pressure to invest in power grid upgrades,which bring opportunities for renewable power generation integration.The combination of heating by distributed renewable energy with the flexible operation of heat pumps is a feasible alternative for dealing with grid reinforcement challenges resulting from heating electrification.In this paper,a mathematical model of the collaborative planning of distributed wind power generation(DWPG)and distribution network with large-scale heat pumps is developed.In this model,the operational flexibility of the heat pump load is fully considered and the requirements of a comfortable indoor temperature are met.By applying this model,the goals of not only increasing the profit of DWPG but also reducing the cost of the power grid upgrade can be achieved.
基金supported in part by the National Natural Science Foundation of China(61901231)in part by the National Natural Science Foundation of China(61971238)+3 种基金in part by the Natural Science Foundation of Jiangsu Province of China(BK20180757)in part by the open project of the Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space,Ministry of Industry and Information Technology(KF20202102)in part by the China Postdoctoral Science Foundation under Grant(2020M671480)in part by the Jiangsu Planned Projects for Postdoctoral Research Funds(2020z295).
文摘In this paper,we jointly design the power control and position dispatch for Multi-Unmanned Aerial Vehicle(UAV)-enabled communication in Device-to-Device(D2D)networks.Our objective is to maximize the total transmission rate of Downlink Users(DUs).Meanwhile,the Quality of Service(QoS)of all D2D users must be satisfied.We comprehensively considered the interference among D2D communications and downlink transmissions.The original problem is strongly non-convex,which requires high computational complexity for traditional optimization methods.And to make matters worse,the results are not necessarily globally optimal.In this paper,we propose a novel Graph Neural Networks(GNN)based approach that can map the considered system into a specific graph structure and achieve the optimal solution in a low complexity manner.Particularly,we first construct a GNN-based model for the proposed network,in which the transmission links and interference links are formulated as vertexes and edges,respectively.Then,by taking the channel state information and the coordinates of ground users as the inputs,as well as the location of UAVs and the transmission power of all transmitters as outputs,we obtain the mapping from inputs to outputs through training the parameters of GNN.Simulation results verified that the way to maximize the total transmission rate of DUs can be extracted effectively via the training on samples.Moreover,it also shows that the performance of proposed GNN-based method is better than that of traditional means.
基金funded by Major Science and Technology Projects in Gansu Province(19ZD2GA003).
文摘Because of the randomness of wind power and photovoltaic(PV)output of new energy bases,the problem of peak regulation capability and voltage stability of ultra-high voltage direct current(UHVDC)transmission lines,we proposed an optimum allocation method of installed capacity of the solar-thermal power station based on chance constrained programming in this work.Firstly,we established the uncertainty model of wind power and PV based on the chance constrained planning theory.Then we used the K-medoids clusteringmethod to cluster the scenarios considering the actual operation scenarios throughout the year.Secondly,we established the optimal configuration model based on the objective function of the strongest transient voltage stability and the lowest overall cost of operation.Finally,by quantitative analysis of actual wind power and photovoltaic new energy base,this work verified the feasibility of the proposed method.As a result of the simulations,we found that using the optimal configuration method of solar-thermal power stations could ensure an accurate allocation of installed capacity.When the installed capacity of the solar-thermal power station is 1×106 kW,the transient voltage recovery index(TVRI)is 0.359,which has a strong voltage support capacity for the system.Based on the results of this work,the optimal configuration of the installed capacity of the solar-thermal power plant can improve peak shaving performance,transient voltage support capability,and new energy consumption while satisfying the Direct Current(DC)outgoing transmission premise.
文摘This paper describes the study analysis performed to evaluate the available and potential solutions to control the highly increasing short circuit （SC） levels in Kuwait power system. The real Kuwait High Voltage （HV） network was simulated to examine different measures at both 275 kV and 132 kV stations. The simulation results show that the short circuit currents exceed the permissible levels （40 kA in the 132 kV network and 63 kA in the 275 kV network） in some specific points. The examined measures include the a study on changing the neutral point policy, changing some lines from alternating current （AC） to direct current （DC）, dividing specific bus bars in some generating stations and applying current limiters. The paper also presents a new plan for the transmission network in order to manage the expected increase in short circuit levels in the future.
