Method for evaluating demand response potential of electric vehicle cluster

Abstract

The invention discloses an electric vehicle cluster demand response potential evaluation method, comprising the following steps: firstly, a time-dependent dynamic traffic network model is establishedaccording to the road network topology information and the time-varying regional traffic information; Secondly, according to the battery capacity, mileage and other vehicle information, charging and discharging power level, charging and discharging efficiency and other facility parameters, a single electric vehicle charging model is established. Then, based on the data of residents' trip survey, the travel chain is constructed and the travel route is planned with 'the least travel time'. Combined with the travel destination of the charge and discharge demand judgment, the electric vehicle travel time and space distribution information is obtained. The invention proposes a user participation response mechanism considering three factors of the remaining travel time at the current time, the remaining battery charge state and the power price compensation, calculates the real-time response degree of the electric vehicle and the demand response potential of the electric vehicle cluster by using a fuzzy algorithm, and provides a reference for formulating a grid control strategy and carrying out the demand response.

Description

technical field [0001] The invention relates to the technical field of electric vehicles, and more specifically, to a method for assessing the demand response potential of electric vehicle clusters. Background technique [0002] Under the background of energy transformation and environmental pollution, the development of electric vehicles has become one of the major measures to implement the national energy strategy. Putting into service, electric vehicles have entered a period of steady growth, which means that more and more electric vehicles will be connected to the grid and interact with the grid in the future. On the one hand, electric vehicles are a kind of flexible electricity load, which will Obtaining electric energy from the grid is also a distributed energy storage resource. Since electric vehicles spend a lot of time in a day, they have great potential to participate in power system demand response services. [0003] At present, many scholars at home and abroad h...

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Problems solved by technology

There are three limitations in the analysis of this kind of charge-discharge and demand response research: 1) The spatial mobility of electric vehicles is not considered enough. When analyzing the demand response potential of electric vehicles, existing research often regards electric vehicles as a category with only time The fixed load or response resource with variable characteristics ignores the mobility, thus lacking spatial response analysis; 2) The subjective participation of user demand response is not considered enough. In the research, it is believed that electric vehicles can participate in demand response when they have objective control capabilities, ignoring 3) The quantitative evaluation of the response potential of electric vehicles is insufficiently considered, and the development of demand response projects first needs to evaluate the controllable potential of demand response resources

[0004] Some studies have paid attention to the different characteristics of electric vehicles and other demand response resources. The literature "Design and Implementation of Electric Vehicle Charging Behavior Simulation Software Based on Multi-Agent System" is based on multi-agent system. The interaction between the road network and the power grid reflects the spatial mobility of the vehicle. The author considers the electricity price and its own state of charge when selecting electric vehicle charging and discharging, but does not consider the time-varying dynamic characteristics of the road network.

Literature "Evaluation Model of Electric Vehicle Cluster Response Capability Considering User Travel Time and Compensation Price" and "Electric Vehicle Energy Efficiency Power Plant Model Considering User Participation" Considering two factors of travel time and compensation price, the active power and reactive power of electric vehicles However, the author regards the two factors as independent variables, and the analysis of the spatio-temporal characteristics of electric vehicle travel is insufficient, which can only reflect the time distribution characteristics of the overall electric vehicle response capability, and cannot give the spatial response potential information of specific local areas

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