Photovoltaic power station three-period energy management method based on time-of-use power prices and load characteristics

Abstract

The invention provides a photovoltaic power station three-period energy management method based on time-of-use power prices and load characteristics. The method comprises dividing a day according to aphotovoltaic output, time-of-use power price information, and load distribution, wherein since the time-of-use power prices generally correspond to the peak and valley periods of the loads, one day is divided into three periods based on the photovoltaic output and the load characteristics, wherein t1-t2 is a photovoltaic output period, t2-t3 is an evening peak period without photovoltaic output,and t3-t4 is a valley period without photovoltaic output, the t1, t2, t3, and t4 correspond to 06:00, 18:00, 24:00, and 06:00 of the next day respectively; according to the real-time energy managementrequirement of a charging station, setting 1440 management cycle a day, wherein each duration of each cycle is 1 min. The method dynamically optimizes and distributes the power of the charging station, does not rely on predictive data, consumes local photovoltaic output while managing the orderly charging of electric vehicles in the station, and reduces the peak-to-valley difference of a power grid.

Description

technical field [0001] The invention belongs to the technical field of power systems, in particular to a three-period energy management method for a photovoltaic power station based on time-of-use electricity prices and load characteristics. Background technique [0002] In recent years, the global energy crisis has become increasingly prominent, the harm of air pollution and global temperature rise has been increasing, and people's attention to energy and environmental issues has also been increasing. In the context of the global energy crisis, the powerful combination of renewable energy and new energy vehicles will undoubtedly promote the development of electric vehicles. Electric vehicles can not only reduce the impact of transportation network on climate change because of their energy supply from low-carbon grids, but also greatly reduce the dependence of transportation on fossil fuels. As a sustainable and environmentally friendly means of transportation, it has attra...

AI Technical Summary

Problems solved by technology

However, due to the strong randomness of electric vehicle parking behavior and charging behavior, the optimization results may not be applicable to the real-time situation of charging stations.

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