With the increase in the power receiving proportion and an insufficient peak regulation capacity of the local units, the receiving-end power grid struggles to achieve peak regulation in valley time. To solve this prob...With the increase in the power receiving proportion and an insufficient peak regulation capacity of the local units, the receiving-end power grid struggles to achieve peak regulation in valley time. To solve this problem while considering the potential of the large-scale charge load of electric vehicles(EVs), an aggregator-based demand response(DR) mechanism for EVs that are participating in the peak regulation in valley time is proposed in this study. In this aggregator-based DR mechanism, the profits for the power grid’s operation and the participation willingness of the EV owners are considered. Based on the characteristics of the EV charging process and the day-ahead unit generation scheduling, a rolling unit commitment model with the DR is established to maximize the social welfare. In addition, to improve the efficiency of the optimization problem solving process and to achieve communication between the independent system operator(ISO) and the aggregators, the clustering algorithm is utilized to extract typical EV charging patterns. Finally, the feasibility and benefits of the aggregator-based DR mechanism for saving the costs and reducing the peak-valley difference of the receiving-end power grid are verified through case studies.展开更多
Thermostatically controlled loads(TCLs)are regarded as having potential to participate in power grid regulation.This paper proposes a scheduling strategy with three-stage optimization for regional aggregators jointly ...Thermostatically controlled loads(TCLs)are regarded as having potential to participate in power grid regulation.This paper proposes a scheduling strategy with three-stage optimization for regional aggregators jointly participating in day-ahead scheduling to support demand response.The first stage is on the profit of aggregators and peak load of the grid.The line loss and voltage deviation of regulation are considered to ensure stable operation of the power grid at the second stage,which guarantees the fairness of the regulation and the comfort of users.A single tempera-ture adjustment strategy is used to control TCLs to maximize the response potential in the third stage.Finally,digital simulation based on the IEEE 33-bus distribution network system proves that the proposed three-stage scheduling strategy can keep the voltage deviation within±5%in different situations.In addition,the Gini coefficient of distribu-tion increases by 20%and the predicted percentage of dissatisfied is 48%lower than those without distribution.展开更多
In recent years,much attention has been devoted to the development and applications of smart grid technologies,with special emphasis on flexible resources such as distributed generations(DGs),energy storages,active lo...In recent years,much attention has been devoted to the development and applications of smart grid technologies,with special emphasis on flexible resources such as distributed generations(DGs),energy storages,active loads,and electric vehicles(EVs).Demand response(DR) is expected to be an effective means for accommodating the integration of renewable energy generations and mitigating their power output fluctuations.Despite their potential contributions to power system secure and economic operation,uncoordinated operations of these flexible resources may result in unexpected congestions in the distribution system concerned.In addition,the behaviors and impacts of flexible resources are normally highly uncertain and complex in deregulated electricity market environments.In this context,this paper aims to propose a DR based congestion management strategy for smart distribution systems.The general framework and procedures for distribution congestion management is first presented.A bi-level optimization model for the day-ahead congestion management based on the proposed framework is established.Subsequently,the robust optimization approach is introduced to alleviate negative impacts introduced by the uncertainties of DG power outputs and market prices.The economic efficiency and robustness of the proposed congestion management strategy is demonstrated by an actual 0.4 kV distribution system in Denmark.展开更多
The paper proposes a model for a micro-grid architecture incorporating the role of aggregators and renewable sources on the prosumer side, working together to optimize configurations and operations. The final model ta...The paper proposes a model for a micro-grid architecture incorporating the role of aggregators and renewable sources on the prosumer side, working together to optimize configurations and operations. The final model takes the form of a mixed-integer linear programming model. This model is solved using the CPLEX solver via GAMS by having a consistent data set.展开更多
基金supported by the Science and Technology Project from the State Grid Shanghai Municipal Electric Power Company of China (52094019006U)the Shanghai Rising-Star Program (18QB1400200)。
文摘With the increase in the power receiving proportion and an insufficient peak regulation capacity of the local units, the receiving-end power grid struggles to achieve peak regulation in valley time. To solve this problem while considering the potential of the large-scale charge load of electric vehicles(EVs), an aggregator-based demand response(DR) mechanism for EVs that are participating in the peak regulation in valley time is proposed in this study. In this aggregator-based DR mechanism, the profits for the power grid’s operation and the participation willingness of the EV owners are considered. Based on the characteristics of the EV charging process and the day-ahead unit generation scheduling, a rolling unit commitment model with the DR is established to maximize the social welfare. In addition, to improve the efficiency of the optimization problem solving process and to achieve communication between the independent system operator(ISO) and the aggregators, the clustering algorithm is utilized to extract typical EV charging patterns. Finally, the feasibility and benefits of the aggregator-based DR mechanism for saving the costs and reducing the peak-valley difference of the receiving-end power grid are verified through case studies.
基金supported in part by the National Natural Science Foundation of China(No.52007126 and No.U2166209).
文摘Thermostatically controlled loads(TCLs)are regarded as having potential to participate in power grid regulation.This paper proposes a scheduling strategy with three-stage optimization for regional aggregators jointly participating in day-ahead scheduling to support demand response.The first stage is on the profit of aggregators and peak load of the grid.The line loss and voltage deviation of regulation are considered to ensure stable operation of the power grid at the second stage,which guarantees the fairness of the regulation and the comfort of users.A single tempera-ture adjustment strategy is used to control TCLs to maximize the response potential in the third stage.Finally,digital simulation based on the IEEE 33-bus distribution network system proves that the proposed three-stage scheduling strategy can keep the voltage deviation within±5%in different situations.In addition,the Gini coefficient of distribu-tion increases by 20%and the predicted percentage of dissatisfied is 48%lower than those without distribution.
基金supported by National Basic Research Program of China (973 Program) (No. 2013CB228202)National Natural Science Foundsation of China (No. 51477151)+1 种基金Specialized Research Fund for the Doctoral Program of Higher Education (No. 20120101110112)a Project by China Southern Power Grid Company (No. K-GD2014-192)
文摘In recent years,much attention has been devoted to the development and applications of smart grid technologies,with special emphasis on flexible resources such as distributed generations(DGs),energy storages,active loads,and electric vehicles(EVs).Demand response(DR) is expected to be an effective means for accommodating the integration of renewable energy generations and mitigating their power output fluctuations.Despite their potential contributions to power system secure and economic operation,uncoordinated operations of these flexible resources may result in unexpected congestions in the distribution system concerned.In addition,the behaviors and impacts of flexible resources are normally highly uncertain and complex in deregulated electricity market environments.In this context,this paper aims to propose a DR based congestion management strategy for smart distribution systems.The general framework and procedures for distribution congestion management is first presented.A bi-level optimization model for the day-ahead congestion management based on the proposed framework is established.Subsequently,the robust optimization approach is introduced to alleviate negative impacts introduced by the uncertainties of DG power outputs and market prices.The economic efficiency and robustness of the proposed congestion management strategy is demonstrated by an actual 0.4 kV distribution system in Denmark.
文摘The paper proposes a model for a micro-grid architecture incorporating the role of aggregators and renewable sources on the prosumer side, working together to optimize configurations and operations. The final model takes the form of a mixed-integer linear programming model. This model is solved using the CPLEX solver via GAMS by having a consistent data set.
