With the increasing integration of large-scale distributed energy resources into the grid,traditional distribution network optimization and dispatch methods struggle to address the challenges posed by both generation ...With the increasing integration of large-scale distributed energy resources into the grid,traditional distribution network optimization and dispatch methods struggle to address the challenges posed by both generation and load.Accounting for these issues,this paper proposes a multi-timescale coordinated optimization dispatch method for distribution networks.First,the probability box theory was employed to determine the uncertainty intervals of generation and load forecasts,based on which,the requirements for flexibility dispatch and capacity constraints of the grid were calculated and analyzed.Subsequently,a multi-timescale optimization framework was constructed,incorporating the generation and load forecast uncertainties.This framework included optimization models for dayahead scheduling,intra-day optimization,and real-time adjustments,aiming to meet flexibility needs across different timescales and improve the economic efficiency of the grid.Furthermore,an improved soft actor-critic algorithm was introduced to enhance the uncertainty exploration capability.Utilizing a centralized training and decentralized execution framework,a multi-agent SAC network model was developed to improve the decision-making efficiency of the agents.Finally,the effectiveness and superiority of the proposed method were validated using a modified IEEE-33 bus test system.展开更多
To better reduce the carbon emissions of a park-integrated energy system(PIES),optimize the comprehensive operating cost,and smooth the load curve,a source-load flexible response model based on the comprehensive evalu...To better reduce the carbon emissions of a park-integrated energy system(PIES),optimize the comprehensive operating cost,and smooth the load curve,a source-load flexible response model based on the comprehensive evaluation index is proposed.Firstly,a source-load flexible response model is proposed under the stepped carbon trading mechanism;the organic Rankine cycle is introduced into the source-side to construct a flexible response model with traditional combined heat and power(CHP)unit and electric boiler to realize the flexible response of CHP to load;and the load-side categorizes loads into transferable,interruptible,and substitutable loads according to the load characteristics and establishes a comprehensive demand response model.Secondly,the analytic network process(ANP)considers the linkages between indicators and allows decision-makers to consider the interactions of elements in a complex dynamic system,resulting in more realistic indicator assignment values.Considering the economy,energy efficiency,and environment,the PIES optimization operation model based on the ANP comprehensive evaluation index is constructed to optimize the system operation comprehensively.Finally,the CPLEX solver inMATLABwas employed to solve the problem.The results of the example showthat the source-load flexible response model proposed in this paper reduces the operating cost of the system by 29.90%,improves the comprehensive utilization rate by 15.00%,and reduces the carbon emission by 26.98%,which effectively enhances the system’s economy and low carbon,and the comprehensive evaluation index based on the ANP reaches 0.95,which takes into account the economy,energy efficiency,and the environment,and is more superior than the single evaluation index.展开更多
With the increasing integration of emerging source-load types such as distributed photovoltaics,electric vehicles,and energy storage into distribution networks,the operational characteristics of these networks have ev...With the increasing integration of emerging source-load types such as distributed photovoltaics,electric vehicles,and energy storage into distribution networks,the operational characteristics of these networks have evolved from traditional single-load centers to complex multi-source,multi-load systems.This transition not only increases the difficulty of effectively classifying distribution networks due to their heightened complexity but also renders traditional energy management approaches-primarily focused on economic objectives-insufficient to meet the growing demands for flexible scheduling and dynamic response.To address these challenges,this paper proposes an adaptive multi-objective energy management strategy that accounts for the distinct operational requirements of distribution networks with a high penetration of new-type source-loads.The goal is to establish a comprehensive energy management framework that optimally balances energy efficiency,carbon reduction,and economic performance in modern distribution networks.To enhance classification accuracy,the strategy constructs amulti-dimensional scenario classification model that integrates environmental and climatic factors by analyzing the operational characteristics of new-type distribution networks and incorporating expert knowledge.An improved split-coupling K-means preclustering algorithm is employed to classify distribution networks effectively.Based on the classification results,fuzzy logic control is then utilized to dynamically optimize the weighting of each objective,allowing for an adaptive adjustment of priorities to achieve a flexible and responsivemulti-objective energy management strategy.The effectiveness of the proposed approach is validated through practical case studies.Simulation results indicate that the proposed method improves classification accuracy by 18.18%compared to traditional classification methods and enhances energy savings and carbon reduction by 4.34%and 20.94%,respectively,compared to the fixed-weight strategy.展开更多
Effective source-load prediction and reasonable dispatching are crucial to realize the economic and reliable operations of integrated energy systems(IESs).They can overcome the challenges introduced by the uncertainti...Effective source-load prediction and reasonable dispatching are crucial to realize the economic and reliable operations of integrated energy systems(IESs).They can overcome the challenges introduced by the uncertainties of new energies and various types of loads in the IES.Accordingly,a robust optimal dispatching method for the IES based on a robust economic model predictive control(REMPC)strategy considering source-load power interval prediction is proposed.First,an operation model of the IES is established,and an interval prediction model based on the bidirectional long short-term memory network optimized by beetle antenna search and bootstrap is formulated and applied to predict the photovoltaic power and the cooling,heating,and electrical loads.Then,an optimal dispatching scheme based on REMPC is devised for the IES.The source-load interval prediction results are used to improve the robustness of the REPMC and reduce the influence of source-load uncertainties on dispatching.An actual IES case is selected to conduct simulations;the results show that compared with other prediction techniques,the proposed method has higher prediction interval coverage probability and prediction interval normalized averaged width.Moreover,the operational cost of the IES is decreased by the REMPC strategy.With the devised dispatching scheme,the ability of the IES to handle the dispatching risk caused by prediction errors is enhanced.Improved dispatching robustness and operational economy are also achieved.展开更多
To optimize peaking operation when high proportion new energy accesses to power grid,evaluation indexes are proposed which simultaneously consider wind-solar complementation and source-load coupling.A typical wind-sol...To optimize peaking operation when high proportion new energy accesses to power grid,evaluation indexes are proposed which simultaneously consider wind-solar complementation and source-load coupling.A typical wind-solar power output scene model based on peaking demand is established which has anti-peaking characteristic.This model uses balancing scenes and key scenes with probability distribution based on improved Latin hypercube sampling(LHS)algorithm and scene reduction technology to illustrate the influence of wind-solar on peaking demand.Based on this,a peak shaving operation optimization model of high proportion new energy power generation is established.The various operating indexes after optimization in multi-scene peaking are calculated,and the ability of power grid peaking operation is compared whth that considering wind-solar complementation and source-load coupling.Finally,a case of high proportion new energy verifies the feasibility and validity of the proposed operation strategy.展开更多
Due to the phenomenon of abandoning wind power and photo voltage(PV)power in the“Three Northern Areas”in China,this paper presents an optimal strategy for coordinating and dispatching“source-load”in power system b...Due to the phenomenon of abandoning wind power and photo voltage(PV)power in the“Three Northern Areas”in China,this paper presents an optimal strategy for coordinating and dispatching“source-load”in power system based on multiple time scales.On the basis of the analysis of the uncertainty of wind power and PV power as well as the characteristics of load side resource dispatching,the optimal model of coordinating and dispatching“source-load”in power system based on multiple time scales is established.It can simultaneously and effectively dispatch conventional generators,wind plant,PV power station,pumped-storage power station and load side resources by optimally using three time scales:day-ahead,intra-day and real-time.According to the latest predicted information of wind power,PV power and load,the original generation schedule can be rolled and amended by using the corresponding time scale.The effectiveness of the model can be verified by a real system.The simulation results show that the proposed model can make full use of“source-load”resources to improve the ability to consume wind power and PV power of the grid-connected system.展开更多
Due to the absence of inertia, the high proportion of electronic power equipment is a great threat to the stability of the power system. Previous studies have proposed the virtual synchronous machine (VSM) control met...Due to the absence of inertia, the high proportion of electronic power equipment is a great threat to the stability of the power system. Previous studies have proposed the virtual synchronous machine (VSM) control method for the inverter-based distributed generators (DG). However, due to the capacity limitations of DG, the capability of the inverter to provide the inertia action is limited. At the same time, some controllable loads also have the ability to provide inertial support but are still not fully utilised. To get a better grid frequency response, this paper proposes a source-load coordination strategy based on the VSM and virtual asynchronous machine (VAM) concept. For that purpose, a detailed VAM model is firstly derived for the rectifier on power demand side. Not only the virtual inertia and frequency oscillation damping can be provided, but also the syn-chronisation units are not needed to obtain the unknown grid frequency. After that, a distributed consensus-based secondary control is present to regulate the frequency to converge to a reference value based on VSM and VAM. Compared with the existing frequency regulation method, the proposed scheme makes full use of the ability of the load side to participate in frequency modulation. Finally, some numerical simulations are performed to validate the feasibility of the proposed method on MATLAB/Simulink.展开更多
To ensure the safety and reliability of the distribution network and adapt to the uncertain development of renewable energy sources and loads,a two-stage distributionally robust optimization model is proposed for the ...To ensure the safety and reliability of the distribution network and adapt to the uncertain development of renewable energy sources and loads,a two-stage distributionally robust optimization model is proposed for the active distribution network(ADN)optimization problem considering the uncertainties of the source and load in this paper.By establishing an ambiguity set to capture the uncertainties of the photovoltaic(PV)power,wind power and load,the piecewise-linear function and auxiliary parameters are introduced to help characterize the probability distribution of uncertain variables.The optimization goal of the model is to minimize the total expected cost under the worst-case distribution in the ambiguity set.The first-stage expected cost is obtained based on the predicted value of the uncertainty variable.The second-stage expected cost is based on the actual value of the uncertainty variable to solve the first-stage decision.The generalized linear decision rule approximates the two-stage optimization model,and the affine function is introduced to provide a closer approximation to the second-stage optimization model.Finally,the improved IEEE 33-node and IEEE 118-node systems are simulated and analyzed with deterministic methods,stochastic programming,and robust optimization methods to verify the feasibility and superiority of the proposed model and algorithm.展开更多
An equivalent source-load MTDC system including DC voltage control units,power control units and interconnected DC lines is considered in this paper,which can be regarded as a generic structure of low-voltage DC micro...An equivalent source-load MTDC system including DC voltage control units,power control units and interconnected DC lines is considered in this paper,which can be regarded as a generic structure of low-voltage DC microgrids,mediumvoltage DC distribution systems or HVDC transmission systems with a common DC bus.A reduced-order model is proposed with a circuit structure of a resistor,inductor and capacitor in parallel for dynamic stability analysis of the system in DC voltage control timescale.The relationship between control parameters and physical parameters of the equivalent circuit can be found,which provides an intuitive insight into the physical meaning of control parameters.Employing this model,a second-order characteristic equation is further derived to investigate system dynamic stability mechanisms in an analytical approach.As a result,the system oscillation frequency and damping are characterized in a straight forward manner,and the role of electrical and control parameters and different system-level control strategies in system dynamic stability in DC voltage control timescale is defined.The effectiveness of the proposed reduced-order model and the correctness of the theoretical analysis are verified by simulation based on PSCAD/EMTDC and an experiment based on a hardware low-voltage MTDC system platform.展开更多
基金funded by Jilin Province Science and Technology Development Plan Project,grant number 20220203163SF.
文摘With the increasing integration of large-scale distributed energy resources into the grid,traditional distribution network optimization and dispatch methods struggle to address the challenges posed by both generation and load.Accounting for these issues,this paper proposes a multi-timescale coordinated optimization dispatch method for distribution networks.First,the probability box theory was employed to determine the uncertainty intervals of generation and load forecasts,based on which,the requirements for flexibility dispatch and capacity constraints of the grid were calculated and analyzed.Subsequently,a multi-timescale optimization framework was constructed,incorporating the generation and load forecast uncertainties.This framework included optimization models for dayahead scheduling,intra-day optimization,and real-time adjustments,aiming to meet flexibility needs across different timescales and improve the economic efficiency of the grid.Furthermore,an improved soft actor-critic algorithm was introduced to enhance the uncertainty exploration capability.Utilizing a centralized training and decentralized execution framework,a multi-agent SAC network model was developed to improve the decision-making efficiency of the agents.Finally,the effectiveness and superiority of the proposed method were validated using a modified IEEE-33 bus test system.
文摘To better reduce the carbon emissions of a park-integrated energy system(PIES),optimize the comprehensive operating cost,and smooth the load curve,a source-load flexible response model based on the comprehensive evaluation index is proposed.Firstly,a source-load flexible response model is proposed under the stepped carbon trading mechanism;the organic Rankine cycle is introduced into the source-side to construct a flexible response model with traditional combined heat and power(CHP)unit and electric boiler to realize the flexible response of CHP to load;and the load-side categorizes loads into transferable,interruptible,and substitutable loads according to the load characteristics and establishes a comprehensive demand response model.Secondly,the analytic network process(ANP)considers the linkages between indicators and allows decision-makers to consider the interactions of elements in a complex dynamic system,resulting in more realistic indicator assignment values.Considering the economy,energy efficiency,and environment,the PIES optimization operation model based on the ANP comprehensive evaluation index is constructed to optimize the system operation comprehensively.Finally,the CPLEX solver inMATLABwas employed to solve the problem.The results of the example showthat the source-load flexible response model proposed in this paper reduces the operating cost of the system by 29.90%,improves the comprehensive utilization rate by 15.00%,and reduces the carbon emission by 26.98%,which effectively enhances the system’s economy and low carbon,and the comprehensive evaluation index based on the ANP reaches 0.95,which takes into account the economy,energy efficiency,and the environment,and is more superior than the single evaluation index.
基金supported by the Science and Technology Project of the Headquarters of the State Grid Corporation(project code:5400-202323233A-1-1-ZN).
文摘With the increasing integration of emerging source-load types such as distributed photovoltaics,electric vehicles,and energy storage into distribution networks,the operational characteristics of these networks have evolved from traditional single-load centers to complex multi-source,multi-load systems.This transition not only increases the difficulty of effectively classifying distribution networks due to their heightened complexity but also renders traditional energy management approaches-primarily focused on economic objectives-insufficient to meet the growing demands for flexible scheduling and dynamic response.To address these challenges,this paper proposes an adaptive multi-objective energy management strategy that accounts for the distinct operational requirements of distribution networks with a high penetration of new-type source-loads.The goal is to establish a comprehensive energy management framework that optimally balances energy efficiency,carbon reduction,and economic performance in modern distribution networks.To enhance classification accuracy,the strategy constructs amulti-dimensional scenario classification model that integrates environmental and climatic factors by analyzing the operational characteristics of new-type distribution networks and incorporating expert knowledge.An improved split-coupling K-means preclustering algorithm is employed to classify distribution networks effectively.Based on the classification results,fuzzy logic control is then utilized to dynamically optimize the weighting of each objective,allowing for an adaptive adjustment of priorities to achieve a flexible and responsivemulti-objective energy management strategy.The effectiveness of the proposed approach is validated through practical case studies.Simulation results indicate that the proposed method improves classification accuracy by 18.18%compared to traditional classification methods and enhances energy savings and carbon reduction by 4.34%and 20.94%,respectively,compared to the fixed-weight strategy.
基金supported by the National Key Research and Development Project of China(2018YFE0122200).
文摘Effective source-load prediction and reasonable dispatching are crucial to realize the economic and reliable operations of integrated energy systems(IESs).They can overcome the challenges introduced by the uncertainties of new energies and various types of loads in the IES.Accordingly,a robust optimal dispatching method for the IES based on a robust economic model predictive control(REMPC)strategy considering source-load power interval prediction is proposed.First,an operation model of the IES is established,and an interval prediction model based on the bidirectional long short-term memory network optimized by beetle antenna search and bootstrap is formulated and applied to predict the photovoltaic power and the cooling,heating,and electrical loads.Then,an optimal dispatching scheme based on REMPC is devised for the IES.The source-load interval prediction results are used to improve the robustness of the REPMC and reduce the influence of source-load uncertainties on dispatching.An actual IES case is selected to conduct simulations;the results show that compared with other prediction techniques,the proposed method has higher prediction interval coverage probability and prediction interval normalized averaged width.Moreover,the operational cost of the IES is decreased by the REMPC strategy.With the devised dispatching scheme,the ability of the IES to handle the dispatching risk caused by prediction errors is enhanced.Improved dispatching robustness and operational economy are also achieved.
基金Youth Science and Technology Fund Project of Gansu Province(No.18JR3RA011)Major Projects in Gansu Province(No.17ZD2GA010)+1 种基金Science and Technology Projects Funding of State Grid Corporation(No.522727160001)Science and Technology Projects of State Grid Gansu Electric Power Company(No.52272716000K)
文摘To optimize peaking operation when high proportion new energy accesses to power grid,evaluation indexes are proposed which simultaneously consider wind-solar complementation and source-load coupling.A typical wind-solar power output scene model based on peaking demand is established which has anti-peaking characteristic.This model uses balancing scenes and key scenes with probability distribution based on improved Latin hypercube sampling(LHS)algorithm and scene reduction technology to illustrate the influence of wind-solar on peaking demand.Based on this,a peak shaving operation optimization model of high proportion new energy power generation is established.The various operating indexes after optimization in multi-scene peaking are calculated,and the ability of power grid peaking operation is compared whth that considering wind-solar complementation and source-load coupling.Finally,a case of high proportion new energy verifies the feasibility and validity of the proposed operation strategy.
基金Major Projects of Gansu Province(No.17ZD2GA010)Power Company Technology Projects of State Grid Corporation in Gansu Province(No.52272716000K)
文摘Due to the phenomenon of abandoning wind power and photo voltage(PV)power in the“Three Northern Areas”in China,this paper presents an optimal strategy for coordinating and dispatching“source-load”in power system based on multiple time scales.On the basis of the analysis of the uncertainty of wind power and PV power as well as the characteristics of load side resource dispatching,the optimal model of coordinating and dispatching“source-load”in power system based on multiple time scales is established.It can simultaneously and effectively dispatch conventional generators,wind plant,PV power station,pumped-storage power station and load side resources by optimally using three time scales:day-ahead,intra-day and real-time.According to the latest predicted information of wind power,PV power and load,the original generation schedule can be rolled and amended by using the corresponding time scale.The effectiveness of the model can be verified by a real system.The simulation results show that the proposed model can make full use of“source-load”resources to improve the ability to consume wind power and PV power of the grid-connected system.
基金National Natural Science Foundation of China,Grant/Award Numbers:62073065,U20A20190National Key Research and Development Program of China,Grant/Award Number:2018YFA0702200。
文摘Due to the absence of inertia, the high proportion of electronic power equipment is a great threat to the stability of the power system. Previous studies have proposed the virtual synchronous machine (VSM) control method for the inverter-based distributed generators (DG). However, due to the capacity limitations of DG, the capability of the inverter to provide the inertia action is limited. At the same time, some controllable loads also have the ability to provide inertial support but are still not fully utilised. To get a better grid frequency response, this paper proposes a source-load coordination strategy based on the VSM and virtual asynchronous machine (VAM) concept. For that purpose, a detailed VAM model is firstly derived for the rectifier on power demand side. Not only the virtual inertia and frequency oscillation damping can be provided, but also the syn-chronisation units are not needed to obtain the unknown grid frequency. After that, a distributed consensus-based secondary control is present to regulate the frequency to converge to a reference value based on VSM and VAM. Compared with the existing frequency regulation method, the proposed scheme makes full use of the ability of the load side to participate in frequency modulation. Finally, some numerical simulations are performed to validate the feasibility of the proposed method on MATLAB/Simulink.
基金supported by Natural Science Foundation of Beijing Municipality(No.3161002)National Key R&D Program(No.2017YFB0903300).
文摘To ensure the safety and reliability of the distribution network and adapt to the uncertain development of renewable energy sources and loads,a two-stage distributionally robust optimization model is proposed for the active distribution network(ADN)optimization problem considering the uncertainties of the source and load in this paper.By establishing an ambiguity set to capture the uncertainties of the photovoltaic(PV)power,wind power and load,the piecewise-linear function and auxiliary parameters are introduced to help characterize the probability distribution of uncertain variables.The optimization goal of the model is to minimize the total expected cost under the worst-case distribution in the ambiguity set.The first-stage expected cost is obtained based on the predicted value of the uncertainty variable.The second-stage expected cost is based on the actual value of the uncertainty variable to solve the first-stage decision.The generalized linear decision rule approximates the two-stage optimization model,and the affine function is introduced to provide a closer approximation to the second-stage optimization model.Finally,the improved IEEE 33-node and IEEE 118-node systems are simulated and analyzed with deterministic methods,stochastic programming,and robust optimization methods to verify the feasibility and superiority of the proposed model and algorithm.
基金This work was supported in part by the National Natural Science Foundation of China under Grant No.51977142.
文摘An equivalent source-load MTDC system including DC voltage control units,power control units and interconnected DC lines is considered in this paper,which can be regarded as a generic structure of low-voltage DC microgrids,mediumvoltage DC distribution systems or HVDC transmission systems with a common DC bus.A reduced-order model is proposed with a circuit structure of a resistor,inductor and capacitor in parallel for dynamic stability analysis of the system in DC voltage control timescale.The relationship between control parameters and physical parameters of the equivalent circuit can be found,which provides an intuitive insight into the physical meaning of control parameters.Employing this model,a second-order characteristic equation is further derived to investigate system dynamic stability mechanisms in an analytical approach.As a result,the system oscillation frequency and damping are characterized in a straight forward manner,and the role of electrical and control parameters and different system-level control strategies in system dynamic stability in DC voltage control timescale is defined.The effectiveness of the proposed reduced-order model and the correctness of the theoretical analysis are verified by simulation based on PSCAD/EMTDC and an experiment based on a hardware low-voltage MTDC system platform.
