The proliferation of electric vehicles(EVs)introduces transformative opportunities and challenges for the stability of distribution networks.Unregulated EV charging will further exacerbate the inherent three-phase imb...The proliferation of electric vehicles(EVs)introduces transformative opportunities and challenges for the stability of distribution networks.Unregulated EV charging will further exacerbate the inherent three-phase imbalance of the power grid,while regulated EV charging will alleviate such imbalance.To systematically address this challenge,this study proposes a two-stage bidding strategy with dispatch potential of electric vehicle aggregators(EVAs).By constructing a coordinated framework that integrates the day-ahead and real-time markets,the proposed two-stage bidding strategy reconfigures distributed EVA clusters into a controllable dynamic energy storage system,with a particular focus on dynamic compensation for deviations between scheduled and real-time operations.A bilevel Stackelberg game resolves three-phase imbalance by achieving Nash equilibrium for inter-phase balance,with Karush-Kuhn-Tucker(KKT)conditions and mixed-integer secondorder cone programming(MISOCP)ensuring feasible solutions.The proposed coordinated framework is validated with different bidding modes includes independent bidding,full price acceptance,and cooperative bidding modes.The proposed twostage bidding strategy provides an EVA-based coordinated scheduling solution that balances the economic efficiency and phase stability in electricity market.展开更多
This paper investigates the impact of electric vehicle(EV)aggregator with communication time delay on stability regions and stability delay margins of a single-area load frequency control(LFC)system.Primarily,a graphi...This paper investigates the impact of electric vehicle(EV)aggregator with communication time delay on stability regions and stability delay margins of a single-area load frequency control(LFC)system.Primarily,a graphical method characterizing stability boundary locus is implemented.For a given time delay,the method computes all the stabilizing proportional-integral(PI)controller gains,which constitutes a stability region in the parameter space of PI controller.Secondly,in order to complement the stability regions,a frequency-domain exact method is used to calculate stability delay margins for various values of PI controller gains.The qualitative impact of EV aggregator on both stability regions and stability delay margins is thoroughly analyzed and the results are authenticated by time-domain simulations and quasi-polynomial mapping-based root finder(QPmR)algorithm.展开更多
The increasing number of photovoltaic(PV)generation and electric vehicles(EVs)on the load side has necessitated an aggregator(Agg)in power system operation.In this paper,an Agg is used to manage the energy profiles of...The increasing number of photovoltaic(PV)generation and electric vehicles(EVs)on the load side has necessitated an aggregator(Agg)in power system operation.In this paper,an Agg is used to manage the energy profiles of PV generation and EVs.However,the daily management of the Agg is challenged by uncertain PV fluctuations.To address this problem,a robust multi-time scale energy management strategy for the Agg is proposed.In a day-ahead phase,robust optimization is developed to determine the power schedule.In a real-time phase,a rolling horizon-based convex optimization model is established to track the day-ahead power schedule based on the flexibilities of the EVs.A case study indicates a good scheduling performance under an uncertain PV output.Through the convexification,the solving efficiency of the real-time operation model is improved,and the over-charging and over-discharging problems of EVs can be suppressed to a certain extent.Moreover,the power deviation between day-ahead and real-time scheduling is controllable when the EV dispatching capacity is sufficient.The strategy can ensure the flexibility of the Agg for real-time operation.展开更多
This paper proposes a multi-agent cooperative operation optimization strategy for regional power grids considering the uncertainty of renewable energy output and flexibility of electric vehicle(EV)scheduling,which not...This paper proposes a multi-agent cooperative operation optimization strategy for regional power grids considering the uncertainty of renewable energy output and flexibility of electric vehicle(EV)scheduling,which not only improves the economy of networked microgrid(NMG)scheduling but also reduces the impact on active distribution network(ADN).EV condition matrix and model of the adjustable charge-anddischarge capacity of the EV may be built up by simulating the trip rule of an EV using the driving behavior of the vehicle model.In the day-ahead stage,by taking into account NMG operating cost,distribution network loss,and EV owners’payment cost,a multi-objective optimal scheduling model is developed,and the day-ahead scheduling contract for EV is obtained.Generative Adversarial Network(GAN)generates a significant number of intraday scenarios of photovoltaic(PV),load,and EV based on historical scheduling data as training data for the intra-day scheduling model multi-agent PPO(MAPPO).In the intra-day scheduling stage,intra-day ultra-short-term forecast data is input into the intra-day scheduling model,and the trained multi-agent model realizes NMG distributed real-time optimal scheduling.Finally,the economy and effectiveness of the proposed strategy are verified by Day-after optimal scheduling results.展开更多
With the increasing use of renewable resources and electric vehicles(EVs), the variability and uncertainty in their nature put forward a high requirement for flexibility in AC distribution system incorporating voltage...With the increasing use of renewable resources and electric vehicles(EVs), the variability and uncertainty in their nature put forward a high requirement for flexibility in AC distribution system incorporating voltage source converter(VSC) based multi-terminal direct current(MTDC) grids. In order to improve the capability of distribution systems to cope with uncertainty, the flexibility enhancement of AC-MTDC distribution systems considering aggregated EVs is studied. Firstly, the charging and discharging model of one EV is proposed considering the users' demand difference and traveling needs. Based on this, a vehicle-to-grid(V2G) control strategy for aggregated EVs to participate in the flexibility promotion of distribution systems is provided. After that, an optimal flexible dispatching method is proposed to improve the flexibility of power systems through cooperation of VSCs, controllable distributed generations(CDGs), aggregated EVs, and energy storage systems(ESSs). Finally, a case study of an AC-MTDC distribution system is carried out. Simulation results show that the proposed dispatching method is capable of effectively enhancing the system flexibility, reducing renewable power curtailment, decreasing load abandonment, and cutting down system cost.展开更多
基金supported by Science and Technology Project of State Grid Corporation of China(No.5400-202318246A-1-1-ZN)。
文摘The proliferation of electric vehicles(EVs)introduces transformative opportunities and challenges for the stability of distribution networks.Unregulated EV charging will further exacerbate the inherent three-phase imbalance of the power grid,while regulated EV charging will alleviate such imbalance.To systematically address this challenge,this study proposes a two-stage bidding strategy with dispatch potential of electric vehicle aggregators(EVAs).By constructing a coordinated framework that integrates the day-ahead and real-time markets,the proposed two-stage bidding strategy reconfigures distributed EVA clusters into a controllable dynamic energy storage system,with a particular focus on dynamic compensation for deviations between scheduled and real-time operations.A bilevel Stackelberg game resolves three-phase imbalance by achieving Nash equilibrium for inter-phase balance,with Karush-Kuhn-Tucker(KKT)conditions and mixed-integer secondorder cone programming(MISOCP)ensuring feasible solutions.The proposed coordinated framework is validated with different bidding modes includes independent bidding,full price acceptance,and cooperative bidding modes.The proposed twostage bidding strategy provides an EVA-based coordinated scheduling solution that balances the economic efficiency and phase stability in electricity market.
基金This work was supported by the Project of Scientific and Technological Research Council of Turkey(TUBITAK)(No.118E744).
文摘This paper investigates the impact of electric vehicle(EV)aggregator with communication time delay on stability regions and stability delay margins of a single-area load frequency control(LFC)system.Primarily,a graphical method characterizing stability boundary locus is implemented.For a given time delay,the method computes all the stabilizing proportional-integral(PI)controller gains,which constitutes a stability region in the parameter space of PI controller.Secondly,in order to complement the stability regions,a frequency-domain exact method is used to calculate stability delay margins for various values of PI controller gains.The qualitative impact of EV aggregator on both stability regions and stability delay margins is thoroughly analyzed and the results are authenticated by time-domain simulations and quasi-polynomial mapping-based root finder(QPmR)algorithm.
基金supported in part by the National Natural Science Foundation of China(No.51877078)the Fundamental Research Funds for the Central Universities(No.2018MS012)
文摘The increasing number of photovoltaic(PV)generation and electric vehicles(EVs)on the load side has necessitated an aggregator(Agg)in power system operation.In this paper,an Agg is used to manage the energy profiles of PV generation and EVs.However,the daily management of the Agg is challenged by uncertain PV fluctuations.To address this problem,a robust multi-time scale energy management strategy for the Agg is proposed.In a day-ahead phase,robust optimization is developed to determine the power schedule.In a real-time phase,a rolling horizon-based convex optimization model is established to track the day-ahead power schedule based on the flexibilities of the EVs.A case study indicates a good scheduling performance under an uncertain PV output.Through the convexification,the solving efficiency of the real-time operation model is improved,and the over-charging and over-discharging problems of EVs can be suppressed to a certain extent.Moreover,the power deviation between day-ahead and real-time scheduling is controllable when the EV dispatching capacity is sufficient.The strategy can ensure the flexibility of the Agg for real-time operation.
基金supported by the Science and Technology Project of State Grid Corporation of China(5100-202155320A-0-0-00).
文摘This paper proposes a multi-agent cooperative operation optimization strategy for regional power grids considering the uncertainty of renewable energy output and flexibility of electric vehicle(EV)scheduling,which not only improves the economy of networked microgrid(NMG)scheduling but also reduces the impact on active distribution network(ADN).EV condition matrix and model of the adjustable charge-anddischarge capacity of the EV may be built up by simulating the trip rule of an EV using the driving behavior of the vehicle model.In the day-ahead stage,by taking into account NMG operating cost,distribution network loss,and EV owners’payment cost,a multi-objective optimal scheduling model is developed,and the day-ahead scheduling contract for EV is obtained.Generative Adversarial Network(GAN)generates a significant number of intraday scenarios of photovoltaic(PV),load,and EV based on historical scheduling data as training data for the intra-day scheduling model multi-agent PPO(MAPPO).In the intra-day scheduling stage,intra-day ultra-short-term forecast data is input into the intra-day scheduling model,and the trained multi-agent model realizes NMG distributed real-time optimal scheduling.Finally,the economy and effectiveness of the proposed strategy are verified by Day-after optimal scheduling results.
基金supported in part by the National Natural Science Foundation of China (No.U2166202)S&T Program of Hebei (No.20312102D)。
文摘With the increasing use of renewable resources and electric vehicles(EVs), the variability and uncertainty in their nature put forward a high requirement for flexibility in AC distribution system incorporating voltage source converter(VSC) based multi-terminal direct current(MTDC) grids. In order to improve the capability of distribution systems to cope with uncertainty, the flexibility enhancement of AC-MTDC distribution systems considering aggregated EVs is studied. Firstly, the charging and discharging model of one EV is proposed considering the users' demand difference and traveling needs. Based on this, a vehicle-to-grid(V2G) control strategy for aggregated EVs to participate in the flexibility promotion of distribution systems is provided. After that, an optimal flexible dispatching method is proposed to improve the flexibility of power systems through cooperation of VSCs, controllable distributed generations(CDGs), aggregated EVs, and energy storage systems(ESSs). Finally, a case study of an AC-MTDC distribution system is carried out. Simulation results show that the proposed dispatching method is capable of effectively enhancing the system flexibility, reducing renewable power curtailment, decreasing load abandonment, and cutting down system cost.
