To ensure an uninterrupted power supply,mobile power sources(MPS)are widely deployed in power grids during emergencies.Comprising mobile emergency generators(MEGs)and mobile energy storage systems(MESS),MPS are capabl...To ensure an uninterrupted power supply,mobile power sources(MPS)are widely deployed in power grids during emergencies.Comprising mobile emergency generators(MEGs)and mobile energy storage systems(MESS),MPS are capable of supplying power to critical loads and serving as backup sources during grid contingencies,offering advantages such as flexibility and high resilience through electricity delivery via transportation networks.This paper proposes a design method for a 400 V–10 kV Dual-Winding Induction Generator(DWIG)intended for MEG applications,employing an improved particle swarmoptimization(PSO)algorithmbased on a back-propagation neural network(BPNN).A parameterized finite element(FE)model of the DWIG is established to derive constraints on its dimensional parameters,thereby simplifying the optimization space.Through sensitivity analysis between temperature rise and electromagnetic loss of the DWIG,the main factors influencing the machine’s temperature are identified,and electromagnetic loss is determined as the optimization objective.To obtain an accurate fitting function between electromagnetic loss and dimensional parameters,the BPNN is employed to predict the nonlinear relationship between the optimization objective and the parameters.The Latin hypercube sampling(LHS)method is used for random sampling in the FE model analysis for training,testing,and validation,which is then applied to compute the cost function in the PSO.Based on the relationships obtained by the BPNN,the PSO algorithm evaluates the fitness and cost functions to determine the optimal design point.The proposed optimization method is validated by comparing simulation results between the initial design and the optimized design.展开更多
To enhance power supply reliability and reduce customer outage time,Mobile Emergency Power Supply Vehicles(MEPSVs),including Mobile Diesel Generator Vehicles(MDGVs)and Mobile Energy Storage Vehicles(MESVs),have become...To enhance power supply reliability and reduce customer outage time,Mobile Emergency Power Supply Vehicles(MEPSVs),including Mobile Diesel Generator Vehicles(MDGVs)and Mobile Energy Storage Vehicles(MESVs),have become indispensable sources for grid maintenance and disaster response.However,in practice,relying solely on MESVs is constrained by battery capacity,making it difficult to meet long-duration power demands.Conversely,using only MDGVs often results in low efficiency and high fuel consumption under fluctuating load conditions,posing challenges to achieving economical and efficient power supply.To address these issues,this paper investigates the parallel power supply architecture of MDGV and MESV,and develops control models for diesel generator and energy storage converter.A fuel-minimization-oriented power distribution strategy is proposed for coordinated operation,aiming to minimize fuel consumption while maintaining the energy storage state of charge(SOC)within a reasonable range.Furthermore,a voltage–frequency control strategy is employed for the energy storage converter,while active power control is applied to the diesel generator.Through adaptive operation mode switching,the proposed strategy enables efficient and cost-effective parallel operation of MDGV and MESV,ensuring long-duration power supply across a wide load range.This approach overcomes the limitations of conventional single-source power supplymethods and provides an effective control solution for the intelligent and efficient operation of emergency power supply systems.Finally,the feasibility of the proposed strategy is verified through simulation and further demonstrated by experiments on a hardware platform.展开更多
"Generalized mobility"is used to realize the unification of tube flow and seepage in form and the unification of commonly used linear and nonlinear flow laws in form,which makes it possible to use the same f..."Generalized mobility"is used to realize the unification of tube flow and seepage in form and the unification of commonly used linear and nonlinear flow laws in form,which makes it possible to use the same form of motion equations to construct unified governing equations for reservoirs of different scales in different regions.Firstly,by defining the generalized mobility under different flow conditions,the basic equation governing fluid flow in reservoir coupling generalized tube flow and seepage is established.Secondly,two typical well test analysis models for coupling tube flow and seepage flow are given,namely,pipe-shaped composite reservoir model and partially open cylindrical reservoir model.The log-log pressure draw-down type-curve of composite pipe-shaped reservoir model can show characteristics of two sets of linear flow.The log-log pressure drawdown plot of partially opened cylindrical reservoir model can show the characteristics of spherical flow and linear flow,as well as spherical flow and radial flow.The pressure build-up derivative curves of the two models basically coincide with their respective pressure drawdown derivative curves in the early stage,pulling down features in the late stage,and the shorter the production time is,the earlier the pulling down feature appears.Finally,the practicability and reliability of the models presented in this paper are verified by three application examples.展开更多
In the event of a major power outage,critical park microgrids(PMGs)could be self-sustaining if mobile emergency generators(MEGs)are stationed to share energy.However,the need for privacy protection and the value of fl...In the event of a major power outage,critical park microgrids(PMGs)could be self-sustaining if mobile emergency generators(MEGs)are stationed to share energy.However,the need for privacy protection and the value of flexible power support on minute-time scales have not been given enough attention.To address the problem,this paper proposes a new self-sustaining strategy for critical PMGs integrating MEGs.First,to promote the cooperation between PMG and MEG,a bi-level benefit distribution mechanism is designed,where the participants'multiple roles and contributions are identified,and good behaviors are also awarded.Additionally,to increase the alliance benefits,three loss coordination modes are presented to guide the power exchange at the minute level between the MEG and PMG,considering the volatility of renewable generation and load.On this basis,a multi-time scale power-energy scheduling strategy is formulated via the alternating direction method of multipliers(ADMM)to coordinate the PMG and MEG.Finally,a dimensionality reduction technology is designed to equivalently simplify the optimization problem to facilitate the adaptive-step-based ADMM solution.Simulation studies indicate that the proposed strategy achieves the self-sustaining of PMGs integrating MEGs while increasing the economy by no less than 3.1%.展开更多
基金funded by the Science and Technology Projects of State Grid Corporation of China(Project No.J2024136).
文摘To ensure an uninterrupted power supply,mobile power sources(MPS)are widely deployed in power grids during emergencies.Comprising mobile emergency generators(MEGs)and mobile energy storage systems(MESS),MPS are capable of supplying power to critical loads and serving as backup sources during grid contingencies,offering advantages such as flexibility and high resilience through electricity delivery via transportation networks.This paper proposes a design method for a 400 V–10 kV Dual-Winding Induction Generator(DWIG)intended for MEG applications,employing an improved particle swarmoptimization(PSO)algorithmbased on a back-propagation neural network(BPNN).A parameterized finite element(FE)model of the DWIG is established to derive constraints on its dimensional parameters,thereby simplifying the optimization space.Through sensitivity analysis between temperature rise and electromagnetic loss of the DWIG,the main factors influencing the machine’s temperature are identified,and electromagnetic loss is determined as the optimization objective.To obtain an accurate fitting function between electromagnetic loss and dimensional parameters,the BPNN is employed to predict the nonlinear relationship between the optimization objective and the parameters.The Latin hypercube sampling(LHS)method is used for random sampling in the FE model analysis for training,testing,and validation,which is then applied to compute the cost function in the PSO.Based on the relationships obtained by the BPNN,the PSO algorithm evaluates the fitness and cost functions to determine the optimal design point.The proposed optimization method is validated by comparing simulation results between the initial design and the optimized design.
基金funded by the Science and Technology Project of State Grid Jiangsu Electric Power Co.,Ltd.(Project No.J2024136).
文摘To enhance power supply reliability and reduce customer outage time,Mobile Emergency Power Supply Vehicles(MEPSVs),including Mobile Diesel Generator Vehicles(MDGVs)and Mobile Energy Storage Vehicles(MESVs),have become indispensable sources for grid maintenance and disaster response.However,in practice,relying solely on MESVs is constrained by battery capacity,making it difficult to meet long-duration power demands.Conversely,using only MDGVs often results in low efficiency and high fuel consumption under fluctuating load conditions,posing challenges to achieving economical and efficient power supply.To address these issues,this paper investigates the parallel power supply architecture of MDGV and MESV,and develops control models for diesel generator and energy storage converter.A fuel-minimization-oriented power distribution strategy is proposed for coordinated operation,aiming to minimize fuel consumption while maintaining the energy storage state of charge(SOC)within a reasonable range.Furthermore,a voltage–frequency control strategy is employed for the energy storage converter,while active power control is applied to the diesel generator.Through adaptive operation mode switching,the proposed strategy enables efficient and cost-effective parallel operation of MDGV and MESV,ensuring long-duration power supply across a wide load range.This approach overcomes the limitations of conventional single-source power supplymethods and provides an effective control solution for the intelligent and efficient operation of emergency power supply systems.Finally,the feasibility of the proposed strategy is verified through simulation and further demonstrated by experiments on a hardware platform.
基金Supported by the Scientific Research Project of Key Laboratory of Shaanxi Provincial Department of Education(13JS090)。
文摘"Generalized mobility"is used to realize the unification of tube flow and seepage in form and the unification of commonly used linear and nonlinear flow laws in form,which makes it possible to use the same form of motion equations to construct unified governing equations for reservoirs of different scales in different regions.Firstly,by defining the generalized mobility under different flow conditions,the basic equation governing fluid flow in reservoir coupling generalized tube flow and seepage is established.Secondly,two typical well test analysis models for coupling tube flow and seepage flow are given,namely,pipe-shaped composite reservoir model and partially open cylindrical reservoir model.The log-log pressure draw-down type-curve of composite pipe-shaped reservoir model can show characteristics of two sets of linear flow.The log-log pressure drawdown plot of partially opened cylindrical reservoir model can show the characteristics of spherical flow and linear flow,as well as spherical flow and radial flow.The pressure build-up derivative curves of the two models basically coincide with their respective pressure drawdown derivative curves in the early stage,pulling down features in the late stage,and the shorter the production time is,the earlier the pulling down feature appears.Finally,the practicability and reliability of the models presented in this paper are verified by three application examples.
基金supported by the National Natural Science Foundation of China(52307149,52007103)China Postdoctoral Fund(BX20230326)the State Grid of China(520601230003)。
文摘In the event of a major power outage,critical park microgrids(PMGs)could be self-sustaining if mobile emergency generators(MEGs)are stationed to share energy.However,the need for privacy protection and the value of flexible power support on minute-time scales have not been given enough attention.To address the problem,this paper proposes a new self-sustaining strategy for critical PMGs integrating MEGs.First,to promote the cooperation between PMG and MEG,a bi-level benefit distribution mechanism is designed,where the participants'multiple roles and contributions are identified,and good behaviors are also awarded.Additionally,to increase the alliance benefits,three loss coordination modes are presented to guide the power exchange at the minute level between the MEG and PMG,considering the volatility of renewable generation and load.On this basis,a multi-time scale power-energy scheduling strategy is formulated via the alternating direction method of multipliers(ADMM)to coordinate the PMG and MEG.Finally,a dimensionality reduction technology is designed to equivalently simplify the optimization problem to facilitate the adaptive-step-based ADMM solution.Simulation studies indicate that the proposed strategy achieves the self-sustaining of PMGs integrating MEGs while increasing the economy by no less than 3.1%.
