A power distribution network source-network-load-storage coordinated optimization scheduling method and system containing a heat storage type industrial load

By establishing a mathematical model for flexible carbon capture gas turbines and thermal storage industrial loads, the problems of low utilization rate of new energy and high peak-shaving pressure were solved, achieving efficient consumption of new energy and improving system economy.

CN118970939BActive Publication Date: 2026-05-05NANJING SUYI IND +1
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Patent Information

Application Number
CN202411121966.0
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2024-08-15
Publication Date
2026-05-05
Estimated Expiration
2044-08-15

AI Technical Summary

Technical Problem

Existing technologies have failed to effectively utilize the potential of thermal storage industrial loads and flexible carbon capture devices, resulting in low utilization of new energy sources, high peak-shaving pressure, and high complexity of optimization scheduling models, making it impossible to balance the economy and safety of system operation.

Method used

A mathematical model for the demand response of flexible carbon capture gas turbines and thermal storage industrial loads is established. Through convex relaxation and linearization, combined with a fast search density clustering algorithm, typical prediction error scenarios are extracted, and a coordinated optimization scheduling model for power grid generation, grid, load and storage is constructed.

Benefits of technology

It has increased the utilization rate of new energy sources, reduced carbon emissions, improved the economic efficiency and safety of system operation, and alleviated peak-shaving pressure.

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Abstract

This invention provides a method and system for coordinated optimization scheduling of power distribution networks, grids, loads, and storage systems, including thermal storage industrial loads. The method includes: acquiring historical prediction error data of new energy sources and loads; establishing a mathematical model of a gas turbine equipped with a flexible carbon capture device, and performing convex relaxation processing on the non-convex problem of the model when the flue gas split ratio of the carbon capture device is adjustable; constructing a mathematical model of the demand response of thermal storage industrial loads, considering daily regulation capacity, daily regulation frequency, and daily output constraints, and performing piecewise linearization processing on the nonlinear constraints of the daily production tasks of thermal storage industrial loads; obtaining a set of typical prediction error scenarios based on the acquired historical prediction error data of new energy sources and loads; and constructing a coordinated optimization scheduling model of power distribution networks, grids, loads, and storage systems, including the demand response of thermal storage industrial loads. This invention leverages flexible resources across multiple stages of the power distribution network, improving the absorption rate of new energy sources and the economic efficiency of system operation, and reducing carbon emissions, thereby contributing to the achievement of dual-carbon goals and sustainable social development.
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