Entity

Time filter

Source Type


Yao W.,Zhejiang University | Zhao J.,Zhejiang University | Wen F.,Zhejiang University | Xue Y.,State Grid Electric Power Research Institute of China | Xin J.,Jiangxi Electric Power Research Institute
Dianli Xitong Zidonghua/Automation of Electric Power Systems | Year: 2012

The extensive integration of numerous plug-in electric vehicles (PEVs) into a power system could produce significant negative impacts on the secure and economic operation of the power system concerned, if the charging procedures of PEVs are uncoordinated. Given this, the hierarchical and zonal dispatching architecture is adopted and a new bi-level optimization model is presented for coordinating the charging/discharging schedules of the PEVs. The upper-level model is devoted to minimizing the system load variance so as to implement peak load shifting by dispatching each electric vehicle aggregator (EVA), and the lower one is aimed at tracing the dispatching scheme determined by the upper decision-maker through figuring out an appropriate charging and discharging schedules throughout a specified day. Two highly efficient commercial solvers, AMPL/IPOPT and AMPL/CPLEX respectively, are employed to solve the developed optimization problem. Finally, a modified IEEE 30-bus system with 5 EVAs is employed to demonstrate the basic characteristics of developed model and method. © 2012 State Grid Electric Power Research Institute Press. Source


Cai Q.,South China University of Technology | Wen F.,Zhejiang University | Xue Y.,State Grid Electric Power Research Institute of China | Xin J.,Jiangxi Electric Power Research Institute
Dianli Xitong Zidonghua/Automation of Electric Power Systems | Year: 2012

As plug-in hybrid electric vehicles (PHEVs) are expected to be widely used in the near future, a mathematical model is developed based on the traditional security constrained unit commitment (SCUC) formulation to address the power system dispatching problem with PHEVs taken into account. With the premise of power system secure operation, both the economic benefits for PHEV users and the carbon-emission costs are taken into account. Then, the features of PHEVs as mobile energy storage units are applied to decouple the developed model into two sub-models, involving the unit commitment model and the charging and discharging scheduling model that includes AC power flow constraints. The optimal plug-in capacities for PHEVs and the schemes, including when and where charging and discharging occur, are obtained through a mixed integer programming algorithm and the Newton-Raphson load flow algorithm in addition to the optimal day-ahead unit commitment scheme. Finally, the feasibility and efficiency of the proposed model are verified with a 6-bus test system and the IEEE 118-bus test system. © 2012 State Grid Electric Power Research Institute Press. Source


Su Y.-C.,Jiangxi Electric Power Research Institute | Wang X.-M.,Jiangxi Super High Voltage Electrical Power Company
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | Year: 2011

A method of panorama data acquisition scheme for the intelligent substation is proposed and implemented. A communication server is used to access various application subsystems with different structures in the substation and the received data are modeled according to IEC61850 standard. The external interface is supplied in accordance with IEC 61970 GID and IEC 61850 MMS. By this way, requirement of data acquisition in intelligent substation is satisfied. Structure and function of the communication server are demonstrated. The detailed realization method of data acquisition is also presented. The whole scheme has been realized in Xingguo digital substation in Jiangxi province. Source


Liu Z.,South China University of Technology | Wen F.,Zhejiang University | Xue Y.,State Grid Electric Power Research Institute of China | Xin J.,Jiangxi Electric Power Research Institute
Dianli Xitong Zidonghua/Automation of Electric Power Systems | Year: 2012

A two-step screening method with the environmental factors and service radius of electric vehicle charging stations considered is presented to identify the candidate sites of electric vehicle charging stations. A mathematical model for optimizing electric vehicle charging stations is developed and solved by a modified primal-dual interior point algorithm. This model takes the minimization of electric vehicle charging stations total cost (including investment cost, operation cost and maintenance cost) and the network loss cost as the objective function, and some related constraints are considered. The modified IEEE 123-node distribution system illustrates the essential features of the developed model and algorithm. © 2012 State Grid Electric Power Research Institute Press. Source


Lu L.,Zhejiang University | Wen F.,Zhejiang University | Xue Y.,China Electric Power Research Institute | Xin J.,Jiangxi Electric Power Research Institute
Dianli Xitong Zidonghua/Automation of Electric Power Systems | Year: 2011

Introducing large-scale plug-in electric vehicle (PEV) into a power system would produce extensive impacts on power system planning, operation as well as electricity market development. Hence, it appears necessary to properly control the PEV charging and discharging behaviors. A new unit commitment model and a solving approach are developed with the optimal PEV charging and discharging controls taken into account, and the objective is to minimize a combination of the operating cost as well as CO2 emission amount of generators. A 10-unit 24-hour unit commitment problem is employed to demonstrate the feasibility and efficiency of the developed model and approach, and the impacts of the wide applications of PEV on the operating costs as well as the emission amounts of the power system examined. In addition, the impacts of different PEV penetration levels in the power system and different PEV charging modes, i. e. fully controlled charging mode, uncontrolled charging mode, delayed charging mode and continuous charging mode, on the results of the unit commitment problem are investigated. © 2011 State Grid Electric Power Research Institute Press. Source

Discover hidden collaborations