一种考虑需求响应的多能互补虚拟电厂经济调度方法

By constructing a two-layer optimization model of virtual power plant and flexible load, and iteratively solving the upper and lower layer models, the balance between demand response and operating costs in the virtual power plant is solved by coordinating traditional energy and renewable energy, thus achieving efficient operation of the virtual power plant.

CN117332937BActive Publication Date: 2026-07-17GUANGZHOU POWER SUPPLY BUREAU GUANGDONG POWER GRID CO LTD

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
GUANGZHOU POWER SUPPLY BUREAU GUANGDONG POWER GRID CO LTD
Filing Date
2023-08-02
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

Existing technologies lack multi-energy complementary virtual power plant scheduling methods that take demand response into account, resulting in an imbalance between demand response and operating costs. This makes it difficult to effectively coordinate the complementary and collaborative scheduling between traditional and renewable energy sources, and thus fails to maximize the operational benefits of virtual power plants.

Method used

A two-layer optimization model of virtual power plant and flexible load is constructed. By iteratively solving the upper and lower layer models, traditional energy and renewable energy are coordinated, power fluctuations are mitigated, and the operating efficiency of the virtual power plant is optimized.

Benefits of technology

It achieves coordination between traditional and renewable energy sources, suppresses power fluctuations, balances demand response and operating costs, and maximizes the operational efficiency of virtual power plants.

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Abstract

本发明公开了一种考虑需求响应的多能互补虚拟电厂经济调度方法,包括:步骤1、构建虚拟电厂和柔性负载双层优化模型,虚拟电厂和柔性负载双层优化模型包括上层模型和下层模型;步骤2、对虚拟电厂和柔性负载双层优化模型进行迭代求解:上层模型求解之后,将求解得到的决策变量值传递到下层模型中来求解下层模型,下层模型求解完成后,再将求解出的决策变量值返回给上层模型重新求解上层模型;按该顺序反复求解上层模型和下层模型,直至满足终止条件,得到最终的决策变量值;步骤3、按模型求解结果对虚拟电厂中各机组进行控制调度。本发明在考虑需求响应的前提下,使虚拟电厂的运行效益最大化,使需求响应和运行成本相互兼顾平衡。
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