Large-scale new energy grid connection leads to the weakening of the system frequency regulation capability,and the system frequency stability is facing unprecedented challenges.In order to solve rapid frequency fluct...Large-scale new energy grid connection leads to the weakening of the system frequency regulation capability,and the system frequency stability is facing unprecedented challenges.In order to solve rapid frequency fluctuation caused by new energy units,this paper proposes a new energy power system frequency regulation strategy with multiple units including the doubly-fed pumped storage unit(DFPSU).Firstly,based on the model predictive control(MPC)theory,the state space equations are established by considering the operating characteristics of the units and the dynamic behavior of the system;secondly,the proportional-differential control link is introduced to minimize the frequency deviation to further optimize the frequency modulation(FM)output of the DFPSU and inhibit the rapid fluctuation of the frequency;lastly,it is verified on theMatlab/Simulink simulation platform,and the results show that the model predictive control with proportional-differential control link can further release the FM potential of the DFPSU,increase the depth of its FM,effectively reduce the frequency deviation of the system and its rate of change,realize the optimization of the active output of the DFPSU and that of other units,and improve the frequency response capability of the system.展开更多
The frequency regulation reserve setting of wind-PV-storage power stations is crucial.However,the existing grid codes set up the station reserve in a static manner,where the synchronous generator characteristics and f...The frequency regulation reserve setting of wind-PV-storage power stations is crucial.However,the existing grid codes set up the station reserve in a static manner,where the synchronous generator characteristics and frequency-step disturbance scenario are considered.Thus,the advantages of flexible regulation of renewable generations are wasted,resulting in excessive curtailment of wind and solar resources.In this study,a method for optimizing the frequency regulation reserve of wind PV storage power stations was developed.Moreover,a station frequency regulation model was constructed,considering the field dynamic response and the coupling between the station and system frequency dynamics.Furthermore,a method for the online evaluation of the station frequency regulation was proposed based on the benchmark governor fitting.This method helps in overcoming the capacity-based reserve static setting.Finally,an optimization model was developed,along with the proposal of the linearized solving algorithm.The field data from the JH4#station in China’s MX power grid was considered for validation.The proposed method achieves a 24.77%increase in the station income while ensuring the system frequency stability when compared with the grid code-based method.展开更多
In high-renewable-energy power systems,the demand for fast-responding capabilities is growing.To address the limitations of conventional closed-loop frequency control,where the integral coefficient cannot dynamically ...In high-renewable-energy power systems,the demand for fast-responding capabilities is growing.To address the limitations of conventional closed-loop frequency control,where the integral coefficient cannot dynamically adjust the frequency regulation command based on the state of charge(SoC)of energy storage units,this paper proposes a secondary frequency regulation control strategy based on variable integral coefficients for multiple energy storage units.First,a power-uniform controller is designed to ensure that thermal power units gradually take on more regulation power during the frequency regulation process.Next,a control framework based on variable integral coefficients is proposed within the secondary frequency regulation model,along with an objective function that simultaneously considers both Automatic Generation Control(AGC)command tracking performance and SoC recovery requirements of energy storage units.Finally,a gradient descent optimization method is used to dynamically adjust the gain of the energy storage integral controller,allowingmultiple energy storage units to respond in real-time to AGC instructions and SoC variations.Simulation results confirmthe effectiveness of the proposedmethod.Compared to traditional strategies,the proposed approach takes into account the SoCdiscrepancies amongmultiple energy storage units and the duration of system net power imbalances.It successfully implements secondary frequency regulation while achieving dynamic power allocation among the units.展开更多
As the development of new power systems progresses,the inherent inertia of power systems continues to diminish.Centralized frequency regulation,which relies on rapid communication and real-time control,can enable inve...As the development of new power systems progresses,the inherent inertia of power systems continues to diminish.Centralized frequency regulation,which relies on rapid communication and real-time control,can enable inverter-based thermostatically controlled load(ITCL)clusters to provide virtual inertia support to the power grid.However,ITCL clusters exhibit significant discrete response characteristics,which precludes the direct integration of load-side inertia support into the synchronous unit side.To address this issue,this paper elaborates on the existing technical framework and analyzes the underlying causes of the problem.It proposes a timestamp allocation mechanism for ITCL cluster control instructions,ensuring that many ITCL terminals can be triggered at staggered times,thereby allowing the load cluster power to adhere to the inertia analog control law at any moment.Building on this foundation,the paper further examines the impact of the inertia response delay of ITCL clusters,which is based on centralized frequency regulation,on the stability of the power system.A design scheme for inertia analog control parameters is proposed,taking into account dual constraints,frequency stability and load cluster regulation capacity.Finally,the feasibility and applicability of the proposed mechanism and parameter design scheme are investigated through simulations conducted via MATLAB/Simulink.展开更多
To enhance the frequency stability and lower the regulation mileage payment of a multiarea integrated energy system(IES)that supports the power Internet of Things(IoT),this paper proposes a data-driven cooperative met...To enhance the frequency stability and lower the regulation mileage payment of a multiarea integrated energy system(IES)that supports the power Internet of Things(IoT),this paper proposes a data-driven cooperative method for automatic generation control(AGC).The method consists of adaptive fractional-order proportional-integral(FOPI)controllers and a novel efficient integration exploration multiagent twin delayed deep deterministic policy gradient(EIE-MATD3)algorithm.The FOPI controllers are designed for each area based on the performancebased frequency regulation market mechanism.The EIE-MATD3 algorithm is used to tune the coefficients of the FOPI controllers in real time using centralized training and decentralized execution.The algorithm incorporates imitation learning and efficient integration exploration to obtain a more robust coordinated control strategy.An experiment on the four-area China Southern Grid(CSG)real-time digital system shows that the proposed method can improve the control performance and reduce the regulation mileage payment of each area in the IES.展开更多
An alternating current(AC)microgrid is a system that integrates renewable power,power converters,controllers and loads.Hierarchical control can manage the frequency of the microgrid to prevent imbalance and collapse o...An alternating current(AC)microgrid is a system that integrates renewable power,power converters,controllers and loads.Hierarchical control can manage the frequency of the microgrid to prevent imbalance and collapse of the system.The existing frequency control methods use traditional proportion integration(PI)controllers,which cannot adjust PI parameters in real-time to respond to the status changes of the system.Hierarchical control driven by fuzzy logic allows real-time adjustment of the PI parameters and the method used a two-layer control structure.The primary control used droop control to adjust power distribution,and fuzzy logic was used in the voltage loop of the primary control.The secondary control was added to make up for frequency deviation caused by droop control,and fuzzy logic was used in the secondary frequency control to deal with the dynamic change of frequency caused by the disturbances of loads.The proposed method was simulated in Matlab/Simulink.In the primary control,the proposed method reduced the total harmonic distortion(THD)of two cycles of the output voltage from 4.19%to 3.89%;in the secondary control,the proposed method reduced the frequency fluctuation of the system by about 0.03 Hz and 0.04 Hz when the load was increased and decreased,respectively.The results show that the proposed methods have a better effect on frequency maintenance and voltage control of the AC microgrid.展开更多
During electric vehicle(EV)-assisted grid frequency modulation,inconsistent state of charge(SOC)among EVs can result in overcharging and discharging of the batteries,affecting the stability of the electrical system.As...During electric vehicle(EV)-assisted grid frequency modulation,inconsistent state of charge(SOC)among EVs can result in overcharging and discharging of the batteries,affecting the stability of the electrical system.As a solution,this paper proposes a priority-based frequency regulation strategy for EVs.Firstly,models for the primary and secondary frequency regulation of EV-assisted power grids are established.Secondly,a consensus algorithm is used to construct a distributed com-munication system for EVs.Target SOC values are used to obtain a local frequency regulation priori-ty list.The list is used in an optimal control plan allowing individual EVs to participate in frequency regulation.Finally,a simulation of this strategy under several scenarios is conducted.The results indicate that the strategy ensures uniform SOC among the participating group of EVs,thereby avoi-ding overcharging and discharging of their batteries.It also reduces frequency fluctuations in the electrical system,making the system more robust compared with the frequency regulation strategy that is not priority-based.展开更多
The increasing integration of renewable energy sources poses great challenges to the power system frequency se curity.However,the existing electricity market mechanism lacks integration and incentives for emerging fre...The increasing integration of renewable energy sources poses great challenges to the power system frequency se curity.However,the existing electricity market mechanism lacks integration and incentives for emerging frequency regula tion(FR)resources such as wind power generators(WPGs),which may reduce their motivation to provide frequency sup port and further deteriorate the frequency dynamics.In this pa per,a market scheduling and pricing method for comprehen sive frequency regulation services(FRSs)is proposed.First,a modeling approach for flexible FR capabilities of WPGs is pro posed based on the mechanism of inertia control and power re serve control.Subsequently,considering the differences in in verter control strategies,a novel system frequency response model with grid-following and grid-forming inverters is estab lished.Combined with the automatic generation control,the fre quency security constraints of the whole FR process are de rived,and integrated into the market scheduling model to cooptimize the energy and FRSs.Finally,by distinguishing the contributions of various types of resources in different FR stag es,a differentiated pricing scheme is proposed to incentivize producers with various regulation qualities to provide FRSs.The effectiveness of the proposed method is verified on the mod ified IEEE 6-bus system and the IEEE RTS-79 system.展开更多
Data centers are promising demand-side flexible resources that can provide frequency regulation services to power grids.While most existing studies focus on individual data centers,coordinating multiple geo-distribute...Data centers are promising demand-side flexible resources that can provide frequency regulation services to power grids.While most existing studies focus on individual data centers,coordinating multiple geo-distributed data centers can significantly enhance operational flexibility and market participation.However,the inherent uncertainty in both data center workloads and regulation signals pose significant challenges to maintaining effective operations,let alone determining regulation capacity offerings.To address these challenges,this paper proposes a coordinated bidding strategy for electricity purchases and regulation capacity offerings for multiple geo-distributed data centers in electricity markets.This strategy expands the feasible region of operational decisions,including workload dispatch,server activation,and cooling behaviors.To enhance the participation of data centers in frequency regulation services under uncertainty,chance-constrained programming is adopted.This paper presents explicit models for these uncertainties involved,starting with the Poisson-distributed workloads and then addressing the unpredictable regulation signals.Numerical experiments based on real-world datasets validate the effectiveness of the proposed strategy compared with state-of-the-art strategies.展开更多
The increasing penetration of renewable energy resources and reduced system inertia pose risks to frequency security of power systems,necessitating the development of fast frequency regulation(FFR)methods using flexib...The increasing penetration of renewable energy resources and reduced system inertia pose risks to frequency security of power systems,necessitating the development of fast frequency regulation(FFR)methods using flexible resources.However,developing effective FFR policies is challenging because different power system operating conditions require distinct regulation logics.Traditional fixed-coefficient linear droop-based control methods are suboptimal for managing the diverse conditions encountered.This paper proposes a dynamic nonlinear P-f droop-based FFR method using a newly established meta-reinforcement learning(meta-RL)approach to enhance control adaptability while ensuring grid stability.First,we model the optimal FFR problem under various operating conditions as a set of Markov decision processes and accordingly formulate the frequency stability-constrained meta-RL problem.To address this,we then construct a novel hierarchical neural network(HNN)structure that incorporates a theoretical frequency stability guarantee,thereby converting the constrained meta-RL problem into a more tractable form.Finally,we propose a two-stage algorithm that leverages the inherent characteristics of the problem,achieving enhanced optimality in solving the HNN-based meta-RL problem.Simulations validate that the proposed FFR method shows superior adaptability across different operating conditions,and achieves better trade-offs between regulation performance and cost than benchmarks.展开更多
As global energy systems transition toward high shares of renewable energy,maintaining frequency stability becomes increasingly challenging in the case of the reduced inertia and dispatchability of inverter-based reso...As global energy systems transition toward high shares of renewable energy,maintaining frequency stability becomes increasingly challenging in the case of the reduced inertia and dispatchability of inverter-based resources.Power generation,including renewable energy technologies as well as thermal power generation,continues to serve a vital role in frequency regulation of power grids but confronts accelerating operational issues,especially when tackling frequent,rapid cycling.Flywheels with their fast response,high power density,long cycle life,and minimal environmental drawbacks,have emerged as promising auxiliary resources for enhancing flexibility in frequency regulation challenges.This paper presents a comprehensive review of flywheel technology development and its limitations,followed by an introduction to the diverse types of grid-scale high-power flywheel energy storage systems.Overviews of the flywheel-assisted power grid paradigm,focusing on advanced flywheel technologies,coordinated control strategies,and economic optimizations in electrical trading markets,are also summarized.The electricity trading market mechanisms,including ancillary service reforms and capacity payments,which reshape power grid balancing by leveraging the role of fastresponse storage,are further investigated and discussed.Finally,practical pilot implementations are examined in regions such as Shanxi and Ningxia,China,and Bacon,the United States,demonstrating the efficacy of the independent Flywheel Energy Storage System(FESS)and assisted power generation.This insight expands the research landscape and provides new directions including the interoperability of FESS with low-inertia grids,comprehensive lifecycle assessment,integration within hybrid storage topologies,and the design of investment incentives to promote large-scale adoption.展开更多
This study investigates a safe reinforcement learning algorithm for grid-forming(GFM)inverter based frequency regulation.To guarantee the stability of the inverter-based resource(IBR)system under the learned control p...This study investigates a safe reinforcement learning algorithm for grid-forming(GFM)inverter based frequency regulation.To guarantee the stability of the inverter-based resource(IBR)system under the learned control policy,a modelbased reinforcement learning(MBRL)algorithm is combined with Lyapunov approach,which determines the safe region of states and actions.To obtain near optimal control policy,the control performance is safely improved by approximate dynamic programming(ADP)using data sampled from the region of attraction(ROA).Moreover,to enhance the control robustness against parameter uncertainty in the inverter,a Gaussian process(GP)model is adopted by the proposed algorithm to effectively learn system dynamics from measurements.Numerical simulations validate the effectiveness of the proposed algorithm.展开更多
The virtual power plant(VPP)facilitates the coordinated optimization of diverse forms of electrical energy through the aggregation and control of distributed energy resources(DERs),offering as a potential resource for...The virtual power plant(VPP)facilitates the coordinated optimization of diverse forms of electrical energy through the aggregation and control of distributed energy resources(DERs),offering as a potential resource for frequency regulation to enhance the power system flexibility.To fully exploit the flexibility of DER and enhance the revenue of VPP,this paper proposes a multi-temporal optimization strategy of VPP in the energy-frequency regulation(EFR)market under the uncertainties of wind power(WP),photovoltaic(PV),and market price.Firstly,all schedulable electric vehicles(EVs)are aggregated into an electric vehicle cluster(EVC),and the schedulable domain evaluation model of EVC is established.A day-ahead energy bidding model based on Stackelberg game is also established for VPP and EVC.Secondly,on this basis,the multi-temporal optimization model of VPP in the EFR market is proposed.To manage risks stemming from the uncertainties of WP,PV,and market price,the concept of conditional value at risk(CVaR)is integrated into the strategy,effectively balancing the bidding benefits and associated risks.Finally,the results based on operational data from a provincial electricity market demonstrate that the proposed strategy enhances comprehensive revenue by providing frequency regulation services and encouraging EV response scheduling.展开更多
With the increased penetration of renewable energy sources,the grid-forming(GFM)energy storage(ES)has been considered to engage in primary frequency regulation(PFR),often necessitating the use of a frequency deadband(...With the increased penetration of renewable energy sources,the grid-forming(GFM)energy storage(ES)has been considered to engage in primary frequency regulation(PFR),often necessitating the use of a frequency deadband(FDB)to prevent excessive battery charging cycling and mitigate frequency oscillations.Implementing the FDB is relatively straightforward in grid-following(GFL)control.However,implementing the FDB in GFM control presents a significant challenge since the inverter must abstain from providing active power at any frequency within the FDB.Therefore,in this paper,the performance of PFR control in the GFM-ES inverter is analyzed in detail first.Then,the FDB is implemented for GFM inverters with various types of synchronization methods,and the need for inertia response is also considered.Moreover,given the risk of oscillations near the FDB boundary,different FDB setting methods are proposed and examined,where an improved triangular hysteresis method is proposed to realize the fast response and enhanced stability.Finally,the simulation and experiment results are provided to verify the effectiveness of the above methods.展开更多
Islanded microgrids(IMGs)offer a viable and efficient energy self-sustaining solution for distributed resources in remote areas.While without utility grid support,the frequency of IMG is susceptible to mismatches betw...Islanded microgrids(IMGs)offer a viable and efficient energy self-sustaining solution for distributed resources in remote areas.While without utility grid support,the frequency of IMG is susceptible to mismatches between demand and generation.Moreover,IMGs encounter uncertain and nonlinear load disturbances together with system parameter perturbation,which further compromises frequency stability.To this aim,this paper proposes a robust multi-virtual synchronous generators(multi-VSGs)coordinated control strategy for distributed secondary frequency regulation(DSFR)in IMGs,which exhibits minimal model dependency and avoids reliance on global information.Two critical methods are developed:(1)a robust VSG control framework that incorporates the linear active disturbance rejection control(LADRC)technique,which enables the estimation and effective elimination of uncertain load disturbances and system's parameter perturbations;(2)a novel secondorder consensus algorithm-based control law for robust secondary frequency regulation,which is featured with proper power sharing among different participants,suppressed power oscillation caused by response disparities,and reduced reliance on complex communication system.Building on methods(1)and(2),a novel multi-VSGs coordinated control strategy is proposed,providing a robust solution for IMG's frequency restoration,and its dynamic characteristics are explored in detail.The correctness and effectiveness of the proposal are verified by both simulation and the hardware-in-the-loop(HIL)experiment results across typical scenarios.展开更多
Continuous increase of wind power penetration brings high randomness to power system,and also leads to serious shortage of primary frequency regulation(PFR)reserve for power system whose reserve capacity is typically ...Continuous increase of wind power penetration brings high randomness to power system,and also leads to serious shortage of primary frequency regulation(PFR)reserve for power system whose reserve capacity is typically provided by conventional units.Considering large-scale wind power participating in PFR,this paper proposes a unit commitment optimization model with respect to coordination of steady state and transient state.In addition to traditional operation costs,losses of wind farm de-loaded operation,environmental benefits and transient frequency safety costs in high-risk stochastic scenarios are also considered in the model.Besides,the model makes full use of interruptible loads on demand side as one of the PFR reserve sources.A selection method for high-risk scenarios is also proposed to improve the calculation efficiency.Finally,this paper proposes an inner-outer iterative optimization method for the model solution.The method is validated by the New England 10-machine system,and the results show that the optimization model can guarantee both the safety of transient frequency and the economy of system operation.展开更多
As the penetration of renewable energy continues to increase,stochastic and intermittent generation resources gradually replace the conventional generators,bringing significant challenges in stabilizing power system f...As the penetration of renewable energy continues to increase,stochastic and intermittent generation resources gradually replace the conventional generators,bringing significant challenges in stabilizing power system frequency.Thus,aggregating demand-side resources for frequency regulation attracts attentions from both academia and industry.However,in practice,conventional aggregation approaches suffer from random and uncertain behaviors of the users such as opting out control signals.The risk-averse multi-armed bandit learning approach is adopted to learn the behaviors of the users and a novel aggregation strategy is developed for residential heating,ventilation,and air conditioning(HVAC)to provide reliable secondary frequency regulation.Compared with the conventional approach,the simulation results show that the risk-averse multiarmed bandit learning approach performs better in secondary frequency regulation with fewer users being selected and opting out of the control.Besides,the proposed approach is more robust to random and changing behaviors of the users.展开更多
Battery energy storage systems(BESSs)can provide instantaneous support for frequency regulation(FR)because of their fast response characteristics.However,purely pursuing a better FR effect calls for continually rapid ...Battery energy storage systems(BESSs)can provide instantaneous support for frequency regulation(FR)because of their fast response characteristics.However,purely pursuing a better FR effect calls for continually rapid cycles of BESSs,which shortens their lifetime and deteriorates the operational economy.To coordinate the lifespan savings and the FR effect,this paper presents a control strategy for the FR of BESSs based on fuzzy logic and hierarchical controllers.The fuzzy logic controller improves the effect of FR by adjusting the charging/discharging power of the BESS with a higher response speed and precision based on the area control error(ACE)signal and the change rate of ACE in a non-linear way.Hierarchical controllers effectively reduce the life loss by optimizing the depth of discharge,which ensures that the state of charge(SOC)of BESS is always in the optimal operating range,and the total FR cost is the lowest at this time.The proposed method can achieve the optimal balance between ACE reduction and operational economy of BESS.The effectiveness of the proposed strategy is verified in a two-area power system.展开更多
With various components and complex topologies,the applications of high-voltage direct current(HVDC)links bring new challenges to the interconnected power systems in the aspect of frequency security,which further infl...With various components and complex topologies,the applications of high-voltage direct current(HVDC)links bring new challenges to the interconnected power systems in the aspect of frequency security,which further influence their reliability performances.Consequently,this paper presents an approach to evaluate the impacts of the HVDC link outage on the reliability of interconnected power system considering the frequency regulation process during system contingencies.Firstly,a multi-state model of an HVDC link with different available loading rates(ALRs)is established based on its reliability network.Then,dynamic frequency response models of the interconnected power system are presented and integrated with a novel frequency regulation scheme enabled by the HVDC link.The proposed scheme exploits the temporary overload capability of normal converters to compensate for the imbalanced power during system contingencies.Moreover,it offers frequency support that enables the frequency regulation reserves of the sending-end and receiving-end power systems to be mutually available.Several indices are established to measure the system reliability based on the given models in terms of abnormal frequency duration,frequency deviation,and energy losses of the frequency regulation process during system contingencies.Finally,a modified two-area reliability test system(RTS)with an HVDC link is adopted to verify the proposed approach.展开更多
The air conditioning cluster(ACC)is a potential candidate to provide frequency regulation reserves.However,the effective assessment of the ACC willing reserve capacity is often an obstacle for existing demand response...The air conditioning cluster(ACC)is a potential candidate to provide frequency regulation reserves.However,the effective assessment of the ACC willing reserve capacity is often an obstacle for existing demand response(DR)programs,influenced by incentive prices,temperatures,etc.In this paper,the complex relationship between the ACC willing reserve capacity and its key influence factors is defined as a demand response characteristic(DRC).To learn about DRC along with real-time frequency regulation,an online deep learning-based DRC(ODLDRC)modeling methodology is designed to continuously retrain the deep neural network-based model.The ODL-DRC model trained by incoming new data does not require massive historical training data,which makes it more time-efficient.Then,the coordinate operation between ODL-DRC modeling and optimal frequency regulation(OFR)is presented.A robust decentralized sliding mode controller(DSMC)is designed to manage the ACC response power in primary frequency regulation against any ACC response uncertainty.An ODL-DRC model-based OFR scheme is formulated by taking the learning error into consideration.Thereby,the ODL-DRC model can be applied to minimize the total operational cost while maintaining frequency stability,without waiting for a well-trained model.The simulation cases validate the superiority of the OFR based on characterizing the ACC by online learning,which can capture the real DRC and simultaneously optimize the regulation performance with strong robustness against any ACC response uncertainty and learning error.展开更多
基金supported by the National Natural Science Foundation of China(Project No.52377082)the Scientific Research Program of Jilin Provincial Department of Education(Project No.JJKH20230123KJ).
文摘Large-scale new energy grid connection leads to the weakening of the system frequency regulation capability,and the system frequency stability is facing unprecedented challenges.In order to solve rapid frequency fluctuation caused by new energy units,this paper proposes a new energy power system frequency regulation strategy with multiple units including the doubly-fed pumped storage unit(DFPSU).Firstly,based on the model predictive control(MPC)theory,the state space equations are established by considering the operating characteristics of the units and the dynamic behavior of the system;secondly,the proportional-differential control link is introduced to minimize the frequency deviation to further optimize the frequency modulation(FM)output of the DFPSU and inhibit the rapid fluctuation of the frequency;lastly,it is verified on theMatlab/Simulink simulation platform,and the results show that the model predictive control with proportional-differential control link can further release the FM potential of the DFPSU,increase the depth of its FM,effectively reduce the frequency deviation of the system and its rate of change,realize the optimization of the active output of the DFPSU and that of other units,and improve the frequency response capability of the system.
基金supported by the Scientific Research Project of China Three Gorges Group Co.LTD(Contract Number:202103368).
文摘The frequency regulation reserve setting of wind-PV-storage power stations is crucial.However,the existing grid codes set up the station reserve in a static manner,where the synchronous generator characteristics and frequency-step disturbance scenario are considered.Thus,the advantages of flexible regulation of renewable generations are wasted,resulting in excessive curtailment of wind and solar resources.In this study,a method for optimizing the frequency regulation reserve of wind PV storage power stations was developed.Moreover,a station frequency regulation model was constructed,considering the field dynamic response and the coupling between the station and system frequency dynamics.Furthermore,a method for the online evaluation of the station frequency regulation was proposed based on the benchmark governor fitting.This method helps in overcoming the capacity-based reserve static setting.Finally,an optimization model was developed,along with the proposal of the linearized solving algorithm.The field data from the JH4#station in China’s MX power grid was considered for validation.The proposed method achieves a 24.77%increase in the station income while ensuring the system frequency stability when compared with the grid code-based method.
文摘In high-renewable-energy power systems,the demand for fast-responding capabilities is growing.To address the limitations of conventional closed-loop frequency control,where the integral coefficient cannot dynamically adjust the frequency regulation command based on the state of charge(SoC)of energy storage units,this paper proposes a secondary frequency regulation control strategy based on variable integral coefficients for multiple energy storage units.First,a power-uniform controller is designed to ensure that thermal power units gradually take on more regulation power during the frequency regulation process.Next,a control framework based on variable integral coefficients is proposed within the secondary frequency regulation model,along with an objective function that simultaneously considers both Automatic Generation Control(AGC)command tracking performance and SoC recovery requirements of energy storage units.Finally,a gradient descent optimization method is used to dynamically adjust the gain of the energy storage integral controller,allowingmultiple energy storage units to respond in real-time to AGC instructions and SoC variations.Simulation results confirmthe effectiveness of the proposedmethod.Compared to traditional strategies,the proposed approach takes into account the SoCdiscrepancies amongmultiple energy storage units and the duration of system net power imbalances.It successfully implements secondary frequency regulation while achieving dynamic power allocation among the units.
基金supported by the Key Scientific and Technological Projects(2024KJGG27)of Tianfu Yongxing Laboratorythe Experimental Platform Open Innovation Funding(209042025003)of Sichuan Energy Internet Research Institute,Tsinghua University.
文摘As the development of new power systems progresses,the inherent inertia of power systems continues to diminish.Centralized frequency regulation,which relies on rapid communication and real-time control,can enable inverter-based thermostatically controlled load(ITCL)clusters to provide virtual inertia support to the power grid.However,ITCL clusters exhibit significant discrete response characteristics,which precludes the direct integration of load-side inertia support into the synchronous unit side.To address this issue,this paper elaborates on the existing technical framework and analyzes the underlying causes of the problem.It proposes a timestamp allocation mechanism for ITCL cluster control instructions,ensuring that many ITCL terminals can be triggered at staggered times,thereby allowing the load cluster power to adhere to the inertia analog control law at any moment.Building on this foundation,the paper further examines the impact of the inertia response delay of ITCL clusters,which is based on centralized frequency regulation,on the stability of the power system.A design scheme for inertia analog control parameters is proposed,taking into account dual constraints,frequency stability and load cluster regulation capacity.Finally,the feasibility and applicability of the proposed mechanism and parameter design scheme are investigated through simulations conducted via MATLAB/Simulink.
基金upported by National Natural Science Foundation of China(52307118).
文摘To enhance the frequency stability and lower the regulation mileage payment of a multiarea integrated energy system(IES)that supports the power Internet of Things(IoT),this paper proposes a data-driven cooperative method for automatic generation control(AGC).The method consists of adaptive fractional-order proportional-integral(FOPI)controllers and a novel efficient integration exploration multiagent twin delayed deep deterministic policy gradient(EIE-MATD3)algorithm.The FOPI controllers are designed for each area based on the performancebased frequency regulation market mechanism.The EIE-MATD3 algorithm is used to tune the coefficients of the FOPI controllers in real time using centralized training and decentralized execution.The algorithm incorporates imitation learning and efficient integration exploration to obtain a more robust coordinated control strategy.An experiment on the four-area China Southern Grid(CSG)real-time digital system shows that the proposed method can improve the control performance and reduce the regulation mileage payment of each area in the IES.
基金National Natural Science Foundation of China(No.62303107)Fundamental Research Funds for the Central Universities,China(Nos.2232022G-09 and 2232021D-38)Shanghai Sailing Program,China(No.21YF1400100)。
文摘An alternating current(AC)microgrid is a system that integrates renewable power,power converters,controllers and loads.Hierarchical control can manage the frequency of the microgrid to prevent imbalance and collapse of the system.The existing frequency control methods use traditional proportion integration(PI)controllers,which cannot adjust PI parameters in real-time to respond to the status changes of the system.Hierarchical control driven by fuzzy logic allows real-time adjustment of the PI parameters and the method used a two-layer control structure.The primary control used droop control to adjust power distribution,and fuzzy logic was used in the voltage loop of the primary control.The secondary control was added to make up for frequency deviation caused by droop control,and fuzzy logic was used in the secondary frequency control to deal with the dynamic change of frequency caused by the disturbances of loads.The proposed method was simulated in Matlab/Simulink.In the primary control,the proposed method reduced the total harmonic distortion(THD)of two cycles of the output voltage from 4.19%to 3.89%;in the secondary control,the proposed method reduced the frequency fluctuation of the system by about 0.03 Hz and 0.04 Hz when the load was increased and decreased,respectively.The results show that the proposed methods have a better effect on frequency maintenance and voltage control of the AC microgrid.
基金Supported by the China Postdoctoral Science Foundation(No.2022M710039).
文摘During electric vehicle(EV)-assisted grid frequency modulation,inconsistent state of charge(SOC)among EVs can result in overcharging and discharging of the batteries,affecting the stability of the electrical system.As a solution,this paper proposes a priority-based frequency regulation strategy for EVs.Firstly,models for the primary and secondary frequency regulation of EV-assisted power grids are established.Secondly,a consensus algorithm is used to construct a distributed com-munication system for EVs.Target SOC values are used to obtain a local frequency regulation priori-ty list.The list is used in an optimal control plan allowing individual EVs to participate in frequency regulation.Finally,a simulation of this strategy under several scenarios is conducted.The results indicate that the strategy ensures uniform SOC among the participating group of EVs,thereby avoi-ding overcharging and discharging of their batteries.It also reduces frequency fluctuations in the electrical system,making the system more robust compared with the frequency regulation strategy that is not priority-based.
基金supported by the National Key Research and Development Program of China(No.2023YFB2406800).
文摘The increasing integration of renewable energy sources poses great challenges to the power system frequency se curity.However,the existing electricity market mechanism lacks integration and incentives for emerging frequency regula tion(FR)resources such as wind power generators(WPGs),which may reduce their motivation to provide frequency sup port and further deteriorate the frequency dynamics.In this pa per,a market scheduling and pricing method for comprehen sive frequency regulation services(FRSs)is proposed.First,a modeling approach for flexible FR capabilities of WPGs is pro posed based on the mechanism of inertia control and power re serve control.Subsequently,considering the differences in in verter control strategies,a novel system frequency response model with grid-following and grid-forming inverters is estab lished.Combined with the automatic generation control,the fre quency security constraints of the whole FR process are de rived,and integrated into the market scheduling model to cooptimize the energy and FRSs.Finally,by distinguishing the contributions of various types of resources in different FR stag es,a differentiated pricing scheme is proposed to incentivize producers with various regulation qualities to provide FRSs.The effectiveness of the proposed method is verified on the mod ified IEEE 6-bus system and the IEEE RTS-79 system.
基金supported in part by the Science and Technology Development FundMacao SARChina(No.001/2024/SKL,No.0053/2022/AMJ)。
文摘Data centers are promising demand-side flexible resources that can provide frequency regulation services to power grids.While most existing studies focus on individual data centers,coordinating multiple geo-distributed data centers can significantly enhance operational flexibility and market participation.However,the inherent uncertainty in both data center workloads and regulation signals pose significant challenges to maintaining effective operations,let alone determining regulation capacity offerings.To address these challenges,this paper proposes a coordinated bidding strategy for electricity purchases and regulation capacity offerings for multiple geo-distributed data centers in electricity markets.This strategy expands the feasible region of operational decisions,including workload dispatch,server activation,and cooling behaviors.To enhance the participation of data centers in frequency regulation services under uncertainty,chance-constrained programming is adopted.This paper presents explicit models for these uncertainties involved,starting with the Poisson-distributed workloads and then addressing the unpredictable regulation signals.Numerical experiments based on real-world datasets validate the effectiveness of the proposed strategy compared with state-of-the-art strategies.
基金supported by the Key Research and Development Program of Inner Mongolia,China(No.2021ZD0039).
文摘The increasing penetration of renewable energy resources and reduced system inertia pose risks to frequency security of power systems,necessitating the development of fast frequency regulation(FFR)methods using flexible resources.However,developing effective FFR policies is challenging because different power system operating conditions require distinct regulation logics.Traditional fixed-coefficient linear droop-based control methods are suboptimal for managing the diverse conditions encountered.This paper proposes a dynamic nonlinear P-f droop-based FFR method using a newly established meta-reinforcement learning(meta-RL)approach to enhance control adaptability while ensuring grid stability.First,we model the optimal FFR problem under various operating conditions as a set of Markov decision processes and accordingly formulate the frequency stability-constrained meta-RL problem.To address this,we then construct a novel hierarchical neural network(HNN)structure that incorporates a theoretical frequency stability guarantee,thereby converting the constrained meta-RL problem into a more tractable form.Finally,we propose a two-stage algorithm that leverages the inherent characteristics of the problem,achieving enhanced optimality in solving the HNN-based meta-RL problem.Simulations validate that the proposed FFR method shows superior adaptability across different operating conditions,and achieves better trade-offs between regulation performance and cost than benchmarks.
基金supported in part by the National Natural Science Foundation of China(No.52376007).
文摘As global energy systems transition toward high shares of renewable energy,maintaining frequency stability becomes increasingly challenging in the case of the reduced inertia and dispatchability of inverter-based resources.Power generation,including renewable energy technologies as well as thermal power generation,continues to serve a vital role in frequency regulation of power grids but confronts accelerating operational issues,especially when tackling frequent,rapid cycling.Flywheels with their fast response,high power density,long cycle life,and minimal environmental drawbacks,have emerged as promising auxiliary resources for enhancing flexibility in frequency regulation challenges.This paper presents a comprehensive review of flywheel technology development and its limitations,followed by an introduction to the diverse types of grid-scale high-power flywheel energy storage systems.Overviews of the flywheel-assisted power grid paradigm,focusing on advanced flywheel technologies,coordinated control strategies,and economic optimizations in electrical trading markets,are also summarized.The electricity trading market mechanisms,including ancillary service reforms and capacity payments,which reshape power grid balancing by leveraging the role of fastresponse storage,are further investigated and discussed.Finally,practical pilot implementations are examined in regions such as Shanxi and Ningxia,China,and Bacon,the United States,demonstrating the efficacy of the independent Flywheel Energy Storage System(FESS)and assisted power generation.This insight expands the research landscape and provides new directions including the interoperability of FESS with low-inertia grids,comprehensive lifecycle assessment,integration within hybrid storage topologies,and the design of investment incentives to promote large-scale adoption.
基金funded in part by the CURENT Research Center and in part by the National Science Foundation(NSF)(No.ECCS-2033910)。
文摘This study investigates a safe reinforcement learning algorithm for grid-forming(GFM)inverter based frequency regulation.To guarantee the stability of the inverter-based resource(IBR)system under the learned control policy,a modelbased reinforcement learning(MBRL)algorithm is combined with Lyapunov approach,which determines the safe region of states and actions.To obtain near optimal control policy,the control performance is safely improved by approximate dynamic programming(ADP)using data sampled from the region of attraction(ROA).Moreover,to enhance the control robustness against parameter uncertainty in the inverter,a Gaussian process(GP)model is adopted by the proposed algorithm to effectively learn system dynamics from measurements.Numerical simulations validate the effectiveness of the proposed algorithm.
基金supported in part by the National Natural Science Foundation of China(No.52477115)(Shanxi)Regional Innovation and Development Joint Fund Project(No.U21A600003).
文摘The virtual power plant(VPP)facilitates the coordinated optimization of diverse forms of electrical energy through the aggregation and control of distributed energy resources(DERs),offering as a potential resource for frequency regulation to enhance the power system flexibility.To fully exploit the flexibility of DER and enhance the revenue of VPP,this paper proposes a multi-temporal optimization strategy of VPP in the energy-frequency regulation(EFR)market under the uncertainties of wind power(WP),photovoltaic(PV),and market price.Firstly,all schedulable electric vehicles(EVs)are aggregated into an electric vehicle cluster(EVC),and the schedulable domain evaluation model of EVC is established.A day-ahead energy bidding model based on Stackelberg game is also established for VPP and EVC.Secondly,on this basis,the multi-temporal optimization model of VPP in the EFR market is proposed.To manage risks stemming from the uncertainties of WP,PV,and market price,the concept of conditional value at risk(CVaR)is integrated into the strategy,effectively balancing the bidding benefits and associated risks.Finally,the results based on operational data from a provincial electricity market demonstrate that the proposed strategy enhances comprehensive revenue by providing frequency regulation services and encouraging EV response scheduling.
基金supported by the Science and Technology of State Grid(No.4000-202432066A-1-1-Z)。
文摘With the increased penetration of renewable energy sources,the grid-forming(GFM)energy storage(ES)has been considered to engage in primary frequency regulation(PFR),often necessitating the use of a frequency deadband(FDB)to prevent excessive battery charging cycling and mitigate frequency oscillations.Implementing the FDB is relatively straightforward in grid-following(GFL)control.However,implementing the FDB in GFM control presents a significant challenge since the inverter must abstain from providing active power at any frequency within the FDB.Therefore,in this paper,the performance of PFR control in the GFM-ES inverter is analyzed in detail first.Then,the FDB is implemented for GFM inverters with various types of synchronization methods,and the need for inertia response is also considered.Moreover,given the risk of oscillations near the FDB boundary,different FDB setting methods are proposed and examined,where an improved triangular hysteresis method is proposed to realize the fast response and enhanced stability.Finally,the simulation and experiment results are provided to verify the effectiveness of the above methods.
基金supported by the National Natural Science Foundation of China(Grant Nos.U22B20104,52407080,52277090,52207097)the International Science and Technology Cooperation Program of China(Grant No.2022YFE0129300)+2 种基金the Science and Technology Innovation Program of Hunan Province(Grant No.2023RC3102)the Excellent Innovation Youth Program of Changsha of China(Grant No.kq2209010)the Key Research and Development Program of Hunan Province(Grant No.2023GK2007)。
文摘Islanded microgrids(IMGs)offer a viable and efficient energy self-sustaining solution for distributed resources in remote areas.While without utility grid support,the frequency of IMG is susceptible to mismatches between demand and generation.Moreover,IMGs encounter uncertain and nonlinear load disturbances together with system parameter perturbation,which further compromises frequency stability.To this aim,this paper proposes a robust multi-virtual synchronous generators(multi-VSGs)coordinated control strategy for distributed secondary frequency regulation(DSFR)in IMGs,which exhibits minimal model dependency and avoids reliance on global information.Two critical methods are developed:(1)a robust VSG control framework that incorporates the linear active disturbance rejection control(LADRC)technique,which enables the estimation and effective elimination of uncertain load disturbances and system's parameter perturbations;(2)a novel secondorder consensus algorithm-based control law for robust secondary frequency regulation,which is featured with proper power sharing among different participants,suppressed power oscillation caused by response disparities,and reduced reliance on complex communication system.Building on methods(1)and(2),a novel multi-VSGs coordinated control strategy is proposed,providing a robust solution for IMG's frequency restoration,and its dynamic characteristics are explored in detail.The correctness and effectiveness of the proposal are verified by both simulation and the hardware-in-the-loop(HIL)experiment results across typical scenarios.
基金supported by the Six Talent Peaks Project in Jiangsu Province(No.XNY-020)the State Key Laboratory of Smart Grid Protection and Control
文摘Continuous increase of wind power penetration brings high randomness to power system,and also leads to serious shortage of primary frequency regulation(PFR)reserve for power system whose reserve capacity is typically provided by conventional units.Considering large-scale wind power participating in PFR,this paper proposes a unit commitment optimization model with respect to coordination of steady state and transient state.In addition to traditional operation costs,losses of wind farm de-loaded operation,environmental benefits and transient frequency safety costs in high-risk stochastic scenarios are also considered in the model.Besides,the model makes full use of interruptible loads on demand side as one of the PFR reserve sources.A selection method for high-risk scenarios is also proposed to improve the calculation efficiency.Finally,this paper proposes an inner-outer iterative optimization method for the model solution.The method is validated by the New England 10-machine system,and the results show that the optimization model can guarantee both the safety of transient frequency and the economy of system operation.
基金supported by the National Natural Science Foundation of China(No.51907026)Natural Science Foundation of Jiangsu(No.BK20190361)+1 种基金Jiangsu Provincial Key Laboratory of Smart Grid Technology and EquipmentGlobal Energy Interconnection Research Institute(No.SGGR0000WLJS1900107)
文摘As the penetration of renewable energy continues to increase,stochastic and intermittent generation resources gradually replace the conventional generators,bringing significant challenges in stabilizing power system frequency.Thus,aggregating demand-side resources for frequency regulation attracts attentions from both academia and industry.However,in practice,conventional aggregation approaches suffer from random and uncertain behaviors of the users such as opting out control signals.The risk-averse multi-armed bandit learning approach is adopted to learn the behaviors of the users and a novel aggregation strategy is developed for residential heating,ventilation,and air conditioning(HVAC)to provide reliable secondary frequency regulation.Compared with the conventional approach,the simulation results show that the risk-averse multiarmed bandit learning approach performs better in secondary frequency regulation with fewer users being selected and opting out of the control.Besides,the proposed approach is more robust to random and changing behaviors of the users.
基金This work was supported by Open Research Project of State Key Laboratory of Control and Simulation of Power Systems and Generation Equipments,Tsinghua University(No.SKLD20M20)Xinjiang Uygur Autonomous Region Natural Science Key Project of University Research Program(No.XJEDU2020I004).
文摘Battery energy storage systems(BESSs)can provide instantaneous support for frequency regulation(FR)because of their fast response characteristics.However,purely pursuing a better FR effect calls for continually rapid cycles of BESSs,which shortens their lifetime and deteriorates the operational economy.To coordinate the lifespan savings and the FR effect,this paper presents a control strategy for the FR of BESSs based on fuzzy logic and hierarchical controllers.The fuzzy logic controller improves the effect of FR by adjusting the charging/discharging power of the BESS with a higher response speed and precision based on the area control error(ACE)signal and the change rate of ACE in a non-linear way.Hierarchical controllers effectively reduce the life loss by optimizing the depth of discharge,which ensures that the state of charge(SOC)of BESS is always in the optimal operating range,and the total FR cost is the lowest at this time.The proposed method can achieve the optimal balance between ACE reduction and operational economy of BESS.The effectiveness of the proposed strategy is verified in a two-area power system.
基金supported by the National Science Foundation of China (No.51807173)the Foundation Research Funds for Central Universities (No.2021QNA4012)the Project of State Grid Zhejiang Electric Power Co.,Ltd. (No.2021ZK11)。
文摘With various components and complex topologies,the applications of high-voltage direct current(HVDC)links bring new challenges to the interconnected power systems in the aspect of frequency security,which further influence their reliability performances.Consequently,this paper presents an approach to evaluate the impacts of the HVDC link outage on the reliability of interconnected power system considering the frequency regulation process during system contingencies.Firstly,a multi-state model of an HVDC link with different available loading rates(ALRs)is established based on its reliability network.Then,dynamic frequency response models of the interconnected power system are presented and integrated with a novel frequency regulation scheme enabled by the HVDC link.The proposed scheme exploits the temporary overload capability of normal converters to compensate for the imbalanced power during system contingencies.Moreover,it offers frequency support that enables the frequency regulation reserves of the sending-end and receiving-end power systems to be mutually available.Several indices are established to measure the system reliability based on the given models in terms of abnormal frequency duration,frequency deviation,and energy losses of the frequency regulation process during system contingencies.Finally,a modified two-area reliability test system(RTS)with an HVDC link is adopted to verify the proposed approach.
基金This work was supported by State Grid Corporation of China Project Research on Coordinated Technology for Dynamic Demand Response in Frequency Control.
文摘The air conditioning cluster(ACC)is a potential candidate to provide frequency regulation reserves.However,the effective assessment of the ACC willing reserve capacity is often an obstacle for existing demand response(DR)programs,influenced by incentive prices,temperatures,etc.In this paper,the complex relationship between the ACC willing reserve capacity and its key influence factors is defined as a demand response characteristic(DRC).To learn about DRC along with real-time frequency regulation,an online deep learning-based DRC(ODLDRC)modeling methodology is designed to continuously retrain the deep neural network-based model.The ODL-DRC model trained by incoming new data does not require massive historical training data,which makes it more time-efficient.Then,the coordinate operation between ODL-DRC modeling and optimal frequency regulation(OFR)is presented.A robust decentralized sliding mode controller(DSMC)is designed to manage the ACC response power in primary frequency regulation against any ACC response uncertainty.An ODL-DRC model-based OFR scheme is formulated by taking the learning error into consideration.Thereby,the ODL-DRC model can be applied to minimize the total operational cost while maintaining frequency stability,without waiting for a well-trained model.The simulation cases validate the superiority of the OFR based on characterizing the ACC by online learning,which can capture the real DRC and simultaneously optimize the regulation performance with strong robustness against any ACC response uncertainty and learning error.
