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
A mixed integer linear programming(MILP)approach for the joint simulation of electric control reserve and electricity wholesale markets is presented.This generation dispatch model extends an existing integrated grid a...A mixed integer linear programming(MILP)approach for the joint simulation of electric control reserve and electricity wholesale markets is presented.This generation dispatch model extends an existing integrated grid and electricity market(IGEM)model covering the Continental European electric power system.By explicitly incorporating the markets for primary and secondary control reserves(PCR and SCR),the model can reproduce the decisions of generating unit operators on which markets get involved.Besides,the introduction of the integrality conditions allows considering start-up costs and the calculus of generating units to pass through the economically unattractive periods with low or even negative prices in order to avoid another start-up.Since this model is too large to be solved with common MILP solvers for the intended simulation time of one year,temporal and geographical interdependencies are used to solve it heuristically.The heuristic therefore splits the model into various sub-problems so that on the one hand,the number of variables,especially of integer variables,per sub-problem is reduced significantly and on the other hand,the relevant interdependencies remain considered.The heuristic is evaluated in terms of accuracy and computation time by means of two case studies.Both case studies show satisfactory accuracy and significant advantages in computation time.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.
文摘A mixed integer linear programming(MILP)approach for the joint simulation of electric control reserve and electricity wholesale markets is presented.This generation dispatch model extends an existing integrated grid and electricity market(IGEM)model covering the Continental European electric power system.By explicitly incorporating the markets for primary and secondary control reserves(PCR and SCR),the model can reproduce the decisions of generating unit operators on which markets get involved.Besides,the introduction of the integrality conditions allows considering start-up costs and the calculus of generating units to pass through the economically unattractive periods with low or even negative prices in order to avoid another start-up.Since this model is too large to be solved with common MILP solvers for the intended simulation time of one year,temporal and geographical interdependencies are used to solve it heuristically.The heuristic therefore splits the model into various sub-problems so that on the one hand,the number of variables,especially of integer variables,per sub-problem is reduced significantly and on the other hand,the relevant interdependencies remain considered.The heuristic is evaluated in terms of accuracy and computation time by means of two case studies.Both case studies show satisfactory accuracy and significant advantages in computation time.
