Intelligent control method and system for electric equipment, computer equipment and medium

Abstract

The invention provides an intelligent control method and system for electric equipment, the computer equipment and a medium. The method comprises the steps of A1 obtaining the current initial openingand closing time of the electric equipment and a preset continuous value of the opening and closing time; A2 performing simulated annealing algorithm iteration on the current initial opening and closing time to obtain new opening and closing time; A3 judging whether the predicted electricity consumption cost corresponding to the new opening and closing time of the electric equipment is smaller than the initial electricity consumption cost corresponding to the current initial opening and closing time or not; A4 if yes, storing the new opening and closing time and the corresponding predicted electricity consumption cost into a memory matrix; using the new turn-on and turn-off time as the current initial turn-on and turn-off time, and executing the step A2 again until the new turn-on and turn-off time of the electric equipment is continuously stored in the memory matrix for a preset number of times; and A5 selecting the opening and closing time corresponding to the minimum expected electricity consumption cost from the memory matrix as the final opening and closing time for controlling the electric equipment.

Description

technical field [0001] The invention relates to the technical field of power control of electrical equipment, in particular to an intelligent control method and system for electrical equipment, computer equipment and media. Background technique [0002] With the development of science and technology and the improvement of people's living standards, the number and capacity of high-power household appliances for residential users are increasing year by year, which is one of the important reasons for the formation of peak load of the power grid and brings challenges to the safe operation of the power grid. At the same time, residents Electricity bills are also increasing year by year. With the continuous improvement of the intelligence of household appliances of residential users and the gradual implementation of time-of-use electricity prices, residents can reduce electricity bills through reasonable arrangements and optimized operation of household appliances, and at the same...

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Problems solved by technology

[0003] However, in the prior art, the genetic algorithm is used to solve the power consumption optimization problem. It is necessary to carry out binary coding first, and then to select, cross, and mutate the coding. The local search ability of the genetic algorithm is poor, resulting in a time-consuming simple genetic algorithm. The search efficiency is low in the later stage of evolution

The simulated annealing algorithm is derived from the principle of solid annealing and is a probability-based algorithm. The biggest shortcoming of the traditional simulated annealing algorithm lies in the contradiction between the quality of the solution and the long solution time. In order to obtain a good optimal solution, it is necessary to repeat Iterative operation, when the scale of the problem increases, there is no feasible solution

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