Research On Models And Strategies Of Electric Energy Coordinated Consumption With Electric Vehicles Integrated In Power System

Electric Vehicle (EV) is an important part of the world's energy technology revolution and the national renewable energy strategy. It is one of the seven Emerging strategic acquisitions in China. Scales of EV charging will effect the power system significantly. Interaction of integration of renewable energy, security and economic of power system operation, charging and discharging of EVs is an important problem in development of EV and active power system. Concentrating on coordinated consumption of electric power energy with EV intergrated, this paper has conducted the following research:According to the control strategy of thermal load, the idea of average power value in large time scale is not a strict constraint to the average power in small time scale is proposed first. Applying this idea, based on statistics and analysis of driving and charging behaviors of different kinds of EVs, physical reality and mechanism of flexibility and adjustability of EV charging load are revealed. Controlling objective of coordinated charging and discharging is pinpointed.A steady-state model is established based on Thevenin equivalent circuit of EV battery. Charging power under different state of charge (SOC) and charging mode and energy accumulate process is discribed. A single EV charging demand model is established considering maximum charging power of battery and charger under variable charging power so that users'demand on energy and charging time and constraints of charging power can be reflected precisely. As EV charging is a follow-up-effect process, charging behavior forecast approach is proposed based on time sequence analysis theory. And a model of charging demand forecast of scales of EVs in an area is established. This work provides feasible region constraint to charging power planning.A coordinated EV charging power control strategy in active city power system is proposed. A double-layer control system is presented. Constraints between two control layers are revealed. And decoupling of charging power planning and real-time power control is achieved. On the system layer, aiming at maximum utilization rate of renewable energy, stabilizing load fluctuation and economic dispatch of thermal generators, considering power system operation and charging demand constraints, a muti-objective optimazation model is established. A nevel constrained multi-objective differential evolution (CMODE) algorithm is proposed to get the pareto solution of the multi-objective optimazation problem. A comentropy weighted technique for order preference by similarity to an ideal solution decision-making method is applied to select optimal solution from pareto solutions, so that the optimal day-ahead charging plan is obtained. On the user layer, according to analysis of battery charging power and users' psychological enduring capacity, a piecewise weighted power dispatching (PWPD) approach is proposed. Different priority and power dispatch strategies are employed in the light of battery state and charging period. As a result, charging demand can be met, fairness among users are satisfied, and EVs can provide a maximum adjustable power to the system layer control.In microgrids, a sheme of local reactive power compensation utilizing off-board fast chargers is put forward. Considering reactive power compensation capacity of the chargers, the objective of var/voltage control (VVC) is formulated as minimizing system power loss while regulating voltage profile within acceptable limits. The centralized VVC scheme is a two-phase control scheme where gradient based Phase I control targets at regulating voltages and linear programming (LP)-based Phase II optimization aims at minimizing power loss. Effects of step length caused by linearization is discussed, and the way to determine step length in linear programming is given.A coordinated charging control system based on Web is designed and developed in this paper. This system serves for charging station which is near the substation and charge for priviate electric cars and electric taxies. Data platform including collection, administration and analysis is built in SQL Server. Control strategy of coordinated charging is modified to adapt the situation of charging station. Smart control algorithm program are coded in C#. EVs charging in the station can be controlled by the program, so that coordinated charging is realized. Besides, this system also integrates imformation management, smart guiding and visual monitoring. Coordinated, smart, visual consumption of electric power in EV charging stations is achieved.