Household energy management optimization method based on renewable energy sharing model

Abstract

The invention discloses a household energy management optimization method based on a renewable energy sharing model. The method comprises the steps that: uniformly dividing one-day time into 48 time periods, and obtaining a scheduling space; dividing intelligent electric appliances into rigid electric appliances and flexible electric appliances according to the working modes of the intelligent electric appliances expected by a user, and setting the day-ahead working data of the flexible electric appliances, including the start-stop time of each flexible electric appliance and the time requiredfor completing the work; enabling an operator to acquire the working data of the electric appliances of the user through an intelligent electric meter and calculate the total power of electricity utilization of the user; predicting a day-ahead photovoltaic power generation amount by using an Ostwald physical prediction strategy, and obtaining a real-time electricity price and a peak power limit published by a power grid to generate an optimal scheduling model; and optimizing and solving the optimal scheduling model by utilizing an improved binary particle swarm algorithm to obtain an optimalhousehold energy management solution. According to the improved binary particle swarm algorithm, the next generation of particles are directly updated by adopting a dynamic probability method on the basis of integrating individual and global optimal particle positions, so that the algorithm convergence speed is higher, and the optimization effect is better.

Description

technical field [0001] The invention relates to the technical field of home energy optimization, in particular to a home energy management optimization method based on a renewable energy sharing model. Background technique [0002] As an extension of the smart grid on the residential user side, the home energy management system can improve the ability of residential users to participate in demand response, improve the power consumption efficiency of the residential user side, and reduce energy waste through the optimal dispatch of household electrical loads. However, in the traditional home energy management system, users need to invest in the installation of hardware facilities such as renewable energy power generation systems and energy storage systems, which is not only expensive but also requires responsible maintenance, which is time-consuming and labor-intensive. And there is no energy sharing channel among users, which leads to the inability of efficient and reasonabl...

AI Technical Summary

Problems solved by technology

However, in the traditional home energy management system, users need to invest in the installation of hardware facilities such as renewable energy power generation systems and energy storage systems, which is not only expensive but also requires responsible maintenance, which is time-consuming and laborious.

And there is no energy sharing channel between users, which leads to the inability of efficient and reasonable use of renewable energy power generation

In addition, the traditional household energy management system only focuses on the optimization of power consumption by a single user to minimize the cost of electricity consumption, ignoring the impact of "surplus power grid" on the distribution network

A large number of distributed renewable energy generation connected to the distribution network will cause a series of power quality problems such as harmonic distortion of grid current, voltage fluctuation, and voltage deviation.

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