| As an important branch of intelligent power technology,the energy management system of residential users has changed the traditional energy use pattern of the user side.It gradually established a two-way interaction mechanism between residential users and the power grid,which has become an indispensable part of the smart grid.It is of great significance to improve energy efficiency,promote the utilization of distributed generation,and ensure the safe and stable operation of power systems.In this context,this paper studies the multi-energy optimization scheduling problem of two types of residential users in the household and residential area.Firstly,for household users,a home energy management system including distributed photovoltaic power,energy storage devices and various electrical loads was established.On the basis of the home energy management system,a smart home with a hybrid gas boiler and electric heating system was studied.Considering the minimum energy cost and the optimal thermal comfort as the objective function,and the operational characteristics of various equipment as the constraints,a multi-objective optimization problem was formulated to optimally schedule the gas and electricity consumption of a smart home equipped with the hybrid heating system,and finally transformed to a single objective mixed integer linear programming problem.Simulation results verified the performance of the studied hybrid heating system and the effectiveness of the proposed scheduling method.It was shown that the hybrid heating system was a more economical solution,which saved 22.8% and21.0% energy costs compared to the pure electricity and pure gas heating solutions.And the scheduling model can optimize the proportion of electricity and gas consumption in the home and reduce the energy cost.In all the scenarios in the sensitivity analysis,the energy cost of the smart home with the hybrid heating system was always lower than that of the pure electricity and pure gas heating systems.In the research on the intelligent electricity consumption technology of residential areas,a residential district energy optimization scheduling strategy including electric vehicles and renewable energy distributed generations was proposed.Considering the operation characteristics of electric vehicles and the energy consumption mode of the community,the mathematical model of the multi-energy optimization scheduling problem in a residential area is established with the highest total economic benefit as the objective function.In view of the uncertain information in the actual operation,model predictive control is introduced to solve the optimization problem.Finally,several simulation examples are designed to analyze and verify the method from various aspects.Results show that the energy scheduling strategy based on model predictive control proposed in this paper can effectively improve the economy and stability of residential areas.This strategy not only improves the total energy supply income of the community,but also reduces the peak demand of the power consumption.At the same time,under the influence of the uncertain information in actual operation,the method proposed in this paper also has better optimization scheduling effect than the day-ahead scheduling. |
