An operation optimization method for regenerative electric boiler participating in power system peak regulation

Abstract

The invention proposes an operation optimization method for a regenerative electric boiler participating in peak regulation of a power system, which belongs to the field of operation optimization for flexible resources participating in peak regulation. This method first uses the historical data of the predicted value of the ambient temperature and the actual value of the ambient temperature to convert through the empirical probability distribution function, and constructs the joint probability distribution function of the converted predicted value of the ambient temperature and the actual value of the ambient temperature, and calculates the actual ambient temperature of the next day. The empirical distribution of the model; then establish the operation optimization model of the regenerative electric boiler participating in the peak regulation of the power system, which is composed of the objective function and the constraint conditions, and solve the model after the distribution robust optimization of the objective function of the model, and obtain the heat storage in each period The optimal solution of the reported power when the electric boiler participates in peak regulation, and finally obtains the bidding power curve of the regenerative electric boiler participating in the peak regulation market, and the optimization is completed. The invention can reduce the influence of ambient temperature uncertainty on the regenerative electric boiler's participation in peak regulation, and give full play to the peak regulation capability of the regenerative electric boiler.

Description

technical field [0001] The invention belongs to the field of operation optimization in which flexible resources participate in peak regulation, and in particular relates to an operation optimization method in which a heat storage electric boiler participates in peak regulation in a power system. Background technique [0002] In recent years, renewable energy has developed vigorously, and the high proportion of renewable energy access has brought great pressure to the power system for peak regulation. In northern China, wind power tends to have a higher output power at night in winter, while thermal power units are limited in their peak shaving capacity due to night heating. Since the power generation resources of the power system in northern my country are mainly thermal power units, the lack of peak-shaving capacity at night during the heating period has become a key factor restricting wind power consumption. At the same time, the heat-storage electric boiler load in the n...

AI Technical Summary

Problems solved by technology

However, when the current research optimizes the power curve of the regenerative electric boiler, the temperature of the weather forecast is often used as the deterministic input condition, and the temperature prediction error is not considered.

Such a method may cause the actual power curve of the regenerative electric boiler to deviate from the power curve reported before the day, and cannot fully utilize the peak-shaving capability of the regenerative electric boiler

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