This paper introduces a novel fully distributed economic power dispatch(EPD)strategy for distribution networks,integrating dynamic tariffs.A two-layer model is proposed:the first layer comprises the physical power dis...This paper introduces a novel fully distributed economic power dispatch(EPD)strategy for distribution networks,integrating dynamic tariffs.A two-layer model is proposed:the first layer comprises the physical power distribution network,including photovoltaic(PV)sources,wind turbine(WT)generators,energy storage systems(ESS),flexible loads(FLs),and other inflexible loads.The upper layer consists of agents dedicated to communication,calculation,and control tasks.Unlike previous EPD strategies,this approach incorporates dynamic tariffs derived from voltage constraints to ensure compliance with nodal voltage constraints.Addi-tionally,a fast distributed optimization algorithm with an event-triggered communication protocol has been developed to address the EPD problem effectively.Through mathematical and simulation analyses,the proposed algorithm's efficiency and rapid conver-gence capability are demonstrated.展开更多
Electric vehicle(EV)is an ideal solution to resolve the carbon emission issue and the fossil fuels scarcity problem in the future.However,a large number of EVs will be concentrated on charging during the valley hours ...Electric vehicle(EV)is an ideal solution to resolve the carbon emission issue and the fossil fuels scarcity problem in the future.However,a large number of EVs will be concentrated on charging during the valley hours leading to new load peaks under the guidance of static time-of-use tariff.Therefore,this paper proposes a dynamic time-of-use tariff mechanism,which redefines the peak and valley time periods according to the predicted loads using the fuzzy C-mean(FCM)clustering algorithm,and then dynamically adjusts the peak and valley tariffs according to the actual load of each time period.Based on the proposed tariff mechanism,an EV charging optimization model with the lowest cost to the users and the lowest variance of the grid-side load as the objective function is established.Then,a weight selection principle with an equal loss rate of the two objectives is proposed to transform the multi-objective optimization problem into a single-objective optimization problem.Finally,the EV charging load optimization model under three tariff strategies is set up and solved with the mathematical solver GROUBI.The results show that the EV charging load optimization strategy based on the dynamic time-of-use tariff can better balance the benefits between charging stations and users under different numbers and proportions of EVs connected to the grid,and can effectively reduce the grid load variance and improve the grid load curve.展开更多
Technical advances and sustainable development tendency accelerate the implementation of electric trucks.However,the penetration of dynamic charging tariff policy poses a huge challenge to the cost-optimal operation o...Technical advances and sustainable development tendency accelerate the implementation of electric trucks.However,the penetration of dynamic charging tariff policy poses a huge challenge to the cost-optimal operation of the electric truck fleet.To this end,a two-stage stochastic electric vehicle routing model is formulated to support cost-efficient routing and charging decisions.Furthermore,an experimental study based on a real-world distribution network is conducted to evaluate impacts of dynamic charging tariffs on logistics planning.The results show that the daily operation cost can reduce by 3.57%to 5.55%as the number of dynamic charging stations increases.The value of stochastic solution confirms the benefits of implementing stochastic programming model,which will ensure a lower operation cost in the long-term through robust route planning.展开更多
文摘This paper introduces a novel fully distributed economic power dispatch(EPD)strategy for distribution networks,integrating dynamic tariffs.A two-layer model is proposed:the first layer comprises the physical power distribution network,including photovoltaic(PV)sources,wind turbine(WT)generators,energy storage systems(ESS),flexible loads(FLs),and other inflexible loads.The upper layer consists of agents dedicated to communication,calculation,and control tasks.Unlike previous EPD strategies,this approach incorporates dynamic tariffs derived from voltage constraints to ensure compliance with nodal voltage constraints.Addi-tionally,a fast distributed optimization algorithm with an event-triggered communication protocol has been developed to address the EPD problem effectively.Through mathematical and simulation analyses,the proposed algorithm's efficiency and rapid conver-gence capability are demonstrated.
基金Key R&D Program of Tianjin,China(No.20YFYSGX00060).
文摘Electric vehicle(EV)is an ideal solution to resolve the carbon emission issue and the fossil fuels scarcity problem in the future.However,a large number of EVs will be concentrated on charging during the valley hours leading to new load peaks under the guidance of static time-of-use tariff.Therefore,this paper proposes a dynamic time-of-use tariff mechanism,which redefines the peak and valley time periods according to the predicted loads using the fuzzy C-mean(FCM)clustering algorithm,and then dynamically adjusts the peak and valley tariffs according to the actual load of each time period.Based on the proposed tariff mechanism,an EV charging optimization model with the lowest cost to the users and the lowest variance of the grid-side load as the objective function is established.Then,a weight selection principle with an equal loss rate of the two objectives is proposed to transform the multi-objective optimization problem into a single-objective optimization problem.Finally,the EV charging load optimization model under three tariff strategies is set up and solved with the mathematical solver GROUBI.The results show that the EV charging load optimization strategy based on the dynamic time-of-use tariff can better balance the benefits between charging stations and users under different numbers and proportions of EVs connected to the grid,and can effectively reduce the grid load variance and improve the grid load curve.
基金the Key Soft Science Project of Shanghai“Science and Technology Innovation Action Plan”(No.21692195200)the Project of Chinese Academy of Engineering(No.2020-XZ-15)。
文摘Technical advances and sustainable development tendency accelerate the implementation of electric trucks.However,the penetration of dynamic charging tariff policy poses a huge challenge to the cost-optimal operation of the electric truck fleet.To this end,a two-stage stochastic electric vehicle routing model is formulated to support cost-efficient routing and charging decisions.Furthermore,an experimental study based on a real-world distribution network is conducted to evaluate impacts of dynamic charging tariffs on logistics planning.The results show that the daily operation cost can reduce by 3.57%to 5.55%as the number of dynamic charging stations increases.The value of stochastic solution confirms the benefits of implementing stochastic programming model,which will ensure a lower operation cost in the long-term through robust route planning.
