Demand response(DR)using shared energy storage systems(ESSs)is an appealing method to save electricity bills for users under demand charge and time-of-use(TOU)price.A novel Stackelberg-game-based ESS sharing scheme is...Demand response(DR)using shared energy storage systems(ESSs)is an appealing method to save electricity bills for users under demand charge and time-of-use(TOU)price.A novel Stackelberg-game-based ESS sharing scheme is proposed and analyzed in this study.In this scheme,the interactions between selfish users and an operator are characterized as a Stackelberg game.Operator holds a large-scale ESS that is shared among users in the form of energy transactions.It sells energy to users and sets the selling price first.It maximizes its profit through optimal pricing and ESS dispatching.Users purchase some energy from operator for the reduction of their demand charges after operator's selling price is announced.This game-theoretic ESS sharing scheme is characterized and analyzed by formulating and solving a bi-level optimization model.The upper-level optimization maximizes operator's profit and the lower-level optimization minimizes users'costs.The bi-level model is transformed and linearized into a mixed-integer linear programming(MILP)model using the mathematical programming with equilibrium constraints(MPEC)method and model linearizing techniques.Case studies with actual data are carried out to explore the economic performances of the proposed ESS sharing scheme.展开更多
In this era of deep decarbonization,when the new mantra is green energy everywhere,can we find ourselves in a situation where we have too much green energy?Believe it or not,this is the energy paradox faced by Austral...In this era of deep decarbonization,when the new mantra is green energy everywhere,can we find ourselves in a situation where we have too much green energy?Believe it or not,this is the energy paradox faced by Australia on October 3,2024.The proliferation of photovoltaic panels on roofs is causing an over-production of electricity,threatening the grid’s stability.On that day,the peak of solar energy reached a record level,far exceeding the expected consumption level.As a result,the electric load van-ished,and the total demand seen by the dispatch center crossed the dangerous low limit set to ensure network stability.展开更多
Advanced management algorithms are required in modern power systems to sustain energy supply with the highest availability and lowest cost.These algorithms need to be capable of not only maintaining scalability,tracta...Advanced management algorithms are required in modern power systems to sustain energy supply with the highest availability and lowest cost.These algorithms need to be capable of not only maintaining scalability,tractability,and privacy,but also enabling the utilization of grid-edge aggregated flexibilities in transmission systems.This paper proposes a distributed hierarchical transactive energy management(TEM)scheme to manage peak load and line congestion problems using connected and aggregated flexibilities.In the scheme,resource owners can privately solve their respective preference problems and send their scheduled power to the corresponding node operator(NO).Afterward,NOs solve a coordination problem to harmonize the actions of resource owners at the same node.Meanwhile,the independent system operator(ISO)updates control signals to steer the scheduled power to a feasible and optimal point.To accomplish all these,a hybrid decomposition approach is further proposed based on consensus+exchange alternating direction method of multipliers(CE-ADMM)and dual decomposition(DD)(CE-ADMM+DD).Besides,a dynamically constrained cutting plane(DC-CP)update algorithm is evolved to control the feasibility condition and minimize sensitivity to initialization.The proposed hybrid decomposition approach is verified and its performance is compared with other reported approaches.Application to various networks verifies its scalability,enhanced accuracy,and convergence speed.展开更多
The increasing penetration of inverter-based resources(IBRs)and renewable energy resources poses significant challenges to the stability and controllability of modern power systems.Dynamic virtual power plants(DVPPs)h...The increasing penetration of inverter-based resources(IBRs)and renewable energy resources poses significant challenges to the stability and controllability of modern power systems.Dynamic virtual power plants(DVPPs)have emerged as a transformative solution for aggregating and controlling heterogeneously distributed energy resources(DERs)flexibly and dynamically.This paper presents a comprehensive review of DVPPs,covering their conceptual evolution—from microgrids to virtual power plants(VPPs)and fast-acting VPPs—culminating in the dynamic DVPP paradigm.This review explores key architectural frameworks,including grid-forming and grid-following roles,as well as AC/DC interfacing strategies.Emphasis is placed on secondary frequency and voltage control mechanisms,dynamic-based and market-based disaggregation,and control methodologies tailored to DERs.展开更多
This paper presents a security constrained unit commitment(SCUC)suitable for power systems with a large share of wind energy.The deterministic spinning reserve requirement is supplemented by an adjustable fraction of ...This paper presents a security constrained unit commitment(SCUC)suitable for power systems with a large share of wind energy.The deterministic spinning reserve requirement is supplemented by an adjustable fraction of the expected shortfall from the supply of wind electric generators(WEGs),computed using the stochastic feature of wind and loosely represented in the security constraint with scenarios.The optimization tool commits and dispatches generating units while simultaneously determining the geographical procurement of the required spinning reserve as well as load-following ramping reserve,by mixed integer quadratic programming(MIQP).Case studies are used to investigate various effects of grid integration on reducing the overall operation costs associated with more wind power in the system.展开更多
基金supported by the National Natural Science Foundation of China(U21A20478)Zhejiang Provincial Nature Science Foundation of China(LZ21F030004)Key-Area Research and Development Program of Guangdong Province(2018B010107002)。
文摘Demand response(DR)using shared energy storage systems(ESSs)is an appealing method to save electricity bills for users under demand charge and time-of-use(TOU)price.A novel Stackelberg-game-based ESS sharing scheme is proposed and analyzed in this study.In this scheme,the interactions between selfish users and an operator are characterized as a Stackelberg game.Operator holds a large-scale ESS that is shared among users in the form of energy transactions.It sells energy to users and sets the selling price first.It maximizes its profit through optimal pricing and ESS dispatching.Users purchase some energy from operator for the reduction of their demand charges after operator's selling price is announced.This game-theoretic ESS sharing scheme is characterized and analyzed by formulating and solving a bi-level optimization model.The upper-level optimization maximizes operator's profit and the lower-level optimization minimizes users'costs.The bi-level model is transformed and linearized into a mixed-integer linear programming(MILP)model using the mathematical programming with equilibrium constraints(MPEC)method and model linearizing techniques.Case studies with actual data are carried out to explore the economic performances of the proposed ESS sharing scheme.
文摘In this era of deep decarbonization,when the new mantra is green energy everywhere,can we find ourselves in a situation where we have too much green energy?Believe it or not,this is the energy paradox faced by Australia on October 3,2024.The proliferation of photovoltaic panels on roofs is causing an over-production of electricity,threatening the grid’s stability.On that day,the peak of solar energy reached a record level,far exceeding the expected consumption level.As a result,the electric load van-ished,and the total demand seen by the dispatch center crossed the dangerous low limit set to ensure network stability.
基金supported by the National Sciences and Engineering Council of Canada(NSERC)(No.Alliance-ALLRP 567550-21)Innovation en Ener-gie Electrique(Innovéé),Québec,Canada(No.PSO-2101)。
文摘Advanced management algorithms are required in modern power systems to sustain energy supply with the highest availability and lowest cost.These algorithms need to be capable of not only maintaining scalability,tractability,and privacy,but also enabling the utilization of grid-edge aggregated flexibilities in transmission systems.This paper proposes a distributed hierarchical transactive energy management(TEM)scheme to manage peak load and line congestion problems using connected and aggregated flexibilities.In the scheme,resource owners can privately solve their respective preference problems and send their scheduled power to the corresponding node operator(NO).Afterward,NOs solve a coordination problem to harmonize the actions of resource owners at the same node.Meanwhile,the independent system operator(ISO)updates control signals to steer the scheduled power to a feasible and optimal point.To accomplish all these,a hybrid decomposition approach is further proposed based on consensus+exchange alternating direction method of multipliers(CE-ADMM)and dual decomposition(DD)(CE-ADMM+DD).Besides,a dynamically constrained cutting plane(DC-CP)update algorithm is evolved to control the feasibility condition and minimize sensitivity to initialization.The proposed hybrid decomposition approach is verified and its performance is compared with other reported approaches.Application to various networks verifies its scalability,enhanced accuracy,and convergence speed.
文摘The increasing penetration of inverter-based resources(IBRs)and renewable energy resources poses significant challenges to the stability and controllability of modern power systems.Dynamic virtual power plants(DVPPs)have emerged as a transformative solution for aggregating and controlling heterogeneously distributed energy resources(DERs)flexibly and dynamically.This paper presents a comprehensive review of DVPPs,covering their conceptual evolution—from microgrids to virtual power plants(VPPs)and fast-acting VPPs—culminating in the dynamic DVPP paradigm.This review explores key architectural frameworks,including grid-forming and grid-following roles,as well as AC/DC interfacing strategies.Emphasis is placed on secondary frequency and voltage control mechanisms,dynamic-based and market-based disaggregation,and control methodologies tailored to DERs.
文摘This paper presents a security constrained unit commitment(SCUC)suitable for power systems with a large share of wind energy.The deterministic spinning reserve requirement is supplemented by an adjustable fraction of the expected shortfall from the supply of wind electric generators(WEGs),computed using the stochastic feature of wind and loosely represented in the security constraint with scenarios.The optimization tool commits and dispatches generating units while simultaneously determining the geographical procurement of the required spinning reserve as well as load-following ramping reserve,by mixed integer quadratic programming(MIQP).Case studies are used to investigate various effects of grid integration on reducing the overall operation costs associated with more wind power in the system.
