Micro-grid energy management method based on Rainbow deep Q network

Abstract

The invention discloses a micro-grid energy management method based on a Rainbow deep Q network, and the method comprises the steps: taking an electric vehicle and energy storage equipment in a micro-grid of a residential area as controlled carriers; load demand, photovoltaic and wind power output, and charge state prediction data of an electric vehicle and energy storage equipment of a micro-grid in 24 hours of a day are used as state space input of a Rainbow deep Q network, and charge and discharge actions of the electric vehicle and the energy storage equipment are learned and executed through an intelligent agent. Therefore, the purpose of lowest one-day operation cost of the micro-grid on the premise of ensuring stable power and safe service life of equipment is achieved. According to the method, the problem that the micro-grid energy management model is difficult to model due to randomness and intermittency of renewable energy sources can be solved, and the method has rapid convergence after training and also has excellent generalization ability when coping with a new micro-grid energy management model; therefore, the defects of low micro-grid energy utilization rate and relatively high operation cost caused by uncertainty of renewable energy sources and diversity of energy flow and loads can be effectively overcome.

Description

technical field [0001] The invention relates to the technical field of electric power engineering, in particular to the field of microgrid operation control and energy management. Background technique [0002] In recent years, due to the shortage of global coal inventories, the power generation of power plants has continued to show negative growth, resulting in global power shortages. As a new type of energy Internet coupled with multiple energy systems and energy storage devices, microgrid can not only access clean new energy such as wind power and photovoltaic power to reduce the power purchase of the grid, but also utilize distributed resources and various Energy management means to improve energy utilization, reduce energy and economic waste. When dealing with power shortages, it can play a positive role in increasing revenue and reducing expenditure. However, it is precisely because of the multi-energy coupling characteristics of microgrids, the uncertainty of renewab...

AI Technical Summary

Problems solved by technology

However, due to the multi-energy coupling characteristics of the micro-grid, the uncertainty of renewable energy, the diversity of energy flows and loads, the scheduling of energy at different times and spaces has become a major challenge to the energy management of micro-grids.

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