Electric vehicle group scheduling method based on load classification

Abstract

The invention discloses an electric vehicle group scheduling method based on load classification. The method comprises steps of carrying out load prediction and electric vehicle behavior prediction; establishing a charging type electric vehicle load group scheduling objective function and a charging type electric vehicle load group scheduling constraint condition in G2V and V2G modes; optimizing the economic benefit of the power exchange type electric vehicle load aggregator in the G2B mode and the economic benefit of the power exchange type electric vehicle load aggregator in the B2G mode tothe maximum, and establishing a power exchange type electric vehicle load group scheduling objective function and a power exchange type electric vehicle load group scheduling constraint condition in the G2B mode and the B2G mode; determining an electric vehicle load classification scheduling method and charging and discharging schemes for rechargeable electric vehicle batteries; adopting a batterycharging, discharging and battery replacing scheme of the battery replacing type electric automobile; and enabling the aggregator to purchase and sell electricity from the power grid and optimizes the economic benefit of the aggregator. According to the method, the potential of the demand side is fully excavated, and certain guiding significance is achieved for large-scale electric vehicle accessto the power grid in the future.

Description

technical field [0001] The invention belongs to the technical field of electric vehicle group scheduling, and in particular relates to a load classification-based electric vehicle group scheduling method. Background technique [0002] As a typical flexible load resource, electric vehicles have both the characteristics of load and energy storage, and can promote the stable operation of the power grid in terms of peak shaving and valley filling, new energy consumption, and frequency regulation. When large-scale electric vehicles are connected and charged out of order, the load on the power system will be greatly increased, especially the peak load. By effectively aggregating electric vehicle loads, aggregators can participate in demand-side response in an orderly manner by rationally optimizing dispatch. A variety of smart grid technologies are used here, such as RFID, GPRS, and Ethernet technology, so that electric vehicles can communicate with the aggregator, and transmit t...

AI Technical Summary

Problems solved by technology

When modeling battery swapping electric vehicles, it is assumed that the replaced battery has run out of power, which has limitations, and does not perform charge and discharge scheduling for fully charged storage batteries. Fully charged batteries can only be idle and wait to be replaced later. This limits the flexibility of scheduling

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