Multi-objective optimization method and system for regenerative type electric heating to participate in wind power accommodation

Abstract

The invention relates to a multi-objective optimization method and system for regenerative type electric heating to participate in wind power accommodation. A multi-objective optimization model for regenerative type electric heating to participate in wind power accommodation is constructed, wherein the multi-objective optimization model comprises a maximum wind power accommodation objective function, a minimum regenerative type electric heating operation cost objective function and a minimum system carbon emission objective function, and the problems that existing regenerative type electric heating participates in wind power accommodation research and mainly focuses on benefit evaluation and economy, and the objective functions are single are solved; and an NSGA-III algorithm is used for solving the multi-objective model for regenerative type electric heating to participate in wind power accommodation, and in the aspect of the algorithm, when a high-dimensional multi-objective optimization problem is processed, the problems that a traditional algorithm is insufficient in convergence and solving efficiency and the like are solved. According to the method and the system, the optimization efficiency and the wind power accommodation capability are improved, the carbon emission is effectively reduced, and the equipment operation cost is reduced.

Description

technical field [0001] The invention relates to the technical field of thermal storage electric heating, in particular to a multi-objective optimization method and system for the thermal storage electric heating to participate in wind power consumption. Background technique [0002] Accelerating the development of non-fossil energy, especially new energy such as wind power and solar power, is the key to promoting low-carbon energy transformation. As the proportion of new energy connected to the grid continues to increase, due to the seasonality and randomness of wind power output, and the limited level of wind power consumption, thermal storage electric heating can use the working characteristics of heat storage to reduce the wind power abandoned at night. It is converted into electric power and releases heat during the day, and has the function of adjusting the load to participate in the peak regulation of the power grid. It is an effective way to solve the problem of wind ...

AI Technical Summary

Problems solved by technology

[0004] To sum up, in terms of optimization models, the current research on the participation of thermal storage electric heating in wind power consumption mainly focuses on benefit evaluation and economics, and the objective function is single. , ignoring issues such as carbon emissions and equipment operating costs

In terms of algorithms, when dealing with high-dimensional multi-objective optimization problems, traditional algorithms have problems such as convergence and insufficient solution efficiency.

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