Coal power adjustable capacity prediction method and system having same

By establishing a set of scenarios for predicting thermal coal prices and an optimization model, the problem of the impact of coal quality changes in predicting the adjustable capacity of coal-fired power plants was solved. This enabled the optimization of economic efficiency and power generation efficiency under high coal prices, ensuring the stability and adjustable capacity of the power system.

CN116307144BActive Publication Date: 2026-06-26STATE GRID ENERGY RES INST CO LTD +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
STATE GRID ENERGY RES INST CO LTD
Filing Date
2023-03-02
Publication Date
2026-06-26

AI Technical Summary

Technical Problem

Existing technologies fail to effectively consider the impact of coal quality changes on the adjustable capacity of coal-fired power plants from the perspectives of economy, environmental protection, and power generation efficiency. This leads to coal-fired power plants purchasing inferior coal types when coal prices are high, resulting in reduced peak power generation capacity of units, increased blocked capacity, and impact on power system stability.

Method used

A set of price prediction scenarios for typical thermal coal varieties is established. Prices are predicted using an autoregressive moving average model. A coal blending optimization model is constructed by combining boiler calorific value, ash content, and sulfur content constraints to solve for the optimal coal blending strategy. A linear regression model is used to predict the hindered capacity, calculate the adjustable capacity coefficient of coal-fired power plants, and evaluate the power generation capacity.

Benefits of technology

Taking into account the impact of coal price changes and coal quality, we can optimize coal blending, predict the adjustable capacity of coal-fired power plants, improve the economic efficiency and power generation efficiency of power generation enterprises, and ensure the stability of the power system.

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Abstract

The application provides a coal power adjustable capacity prediction method. The method comprises the following steps: establishing a prediction scene set of typical power coal variety prices to obtain predicted prices of the typical power coal varieties; establishing an objective function of minimizing the coal blending and burning power generation cost, and establishing a coal blending optimization model according to the power coal consumption constraint, the boiler calorific value, the boiler ash content and the boiler sulfur content constraint, solving the coal blending optimization model to obtain an optimal coal blending strategy; establishing a linear regression model of the blocked capacity of the coal power unit during the peak output period and the power coal quality according to the historical data of the adjustable capacity and the power coal quality of the coal power unit in the power system during the peak output period; predicting the corresponding blocked capacity through the linear regression model; calculating the coal power adjustable capacity of each coal power unit in the power system to obtain the adjustable capacity coefficient of the power system, and evaluating the coal power generation capacity according to the adjustable capacity coefficient.
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