考虑差异化工业高载能负荷灵活性挖掘的市场实施及调度模型研究综述

doi:10.19595/j.cnki.1000-6753.tces.240537

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摘要

利用差异化工业高载能负荷进行需求响应是需求侧参与电网灵活互动的重要途径,尤其是对于高比例可再生能源的系统,具有重要意义。本研究首先介绍了差异化工业高载能负荷的基本概念,并对三种典型工业高载能负荷进行了灵活性分析;然后探讨了差异化工业高载能负荷优化调度方法的主要目标及在市场层面的实施情况;此外,介绍了三种典型工业高载能负荷的优化调度模型,并对求解算法、求解器的研究现状进行了评述;最后,总结了目前差异化工业高载能负荷灵活性挖掘研究中的现有挑战,并对未来的研究方向进行了展望。

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	赵旭东
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关键词 ：差异化工业高载能负荷, 灵活性分析, 优化调度方法, 求解算法

Abstract：

With the global rise in new energy generation, power systems increasingly face challenges in accommodating a high share of renewable sources. The intermittent nature of renewables like wind and solar presents significant difficulties for grid stability and reliability. Stimulating the demand response flexibility of industrial energy-intensive loads has become crucial for effectively integrating these renewables. By scheduling these loads based on new energy output and system supply-demand dynamics, the grid's capacity to absorb renewable energy and maintain operational stability is enhanced.
Differentiated industrial energy-intensive loads are defined, and a comprehensive flexibility analysis is conducted on three typical types: cement plants, aluminum electrolysis plants, and refineries. These industries consume substantial electrical energy and possess varying degrees of operational flexibility suitable for demand response. Their optimization scheduling objectives—such as minimizing operational costs, reducing peak demand, and improving energy efficiency—are explored, along with their market participation characteristics, including responsiveness to price signals and provision of ancillary services.
Scheduling models for these industrial loads are introduced, considering specific operational constraints, production requirements, and flexibility potentials. For example, the cement plant model accounts for kiln thermal characteristics and clinker storage capacity, while the aluminum electrolysis model addresses electrolytic cell sensitivity to power interruptions. The refinery model incorporates processing unit complexities and product demands. Existing solution algorithms and solvers are analyzed, discussing the pros and cons of traditional optimization methods, heuristic algorithms, and their applicability in solving these models.
The application challenges and future development directions of these loads in power systems are summarized. Emphasis is placed on designing effective incentive mechanisms—such as dynamic pricing and financial incentives—to motivate industry participation in demand response programs. Enhancing data management capabilities is crucial, as accurate and timely data on energy consumption and market prices are essential for effective scheduling. The dissemination of operational skills among industry personnel is also highlighted to facilitate the adoption of advanced scheduling practices.
This study fills a domestic gap in reviews on demand response flexibility for industrial energy-intensive loads, providing significant theoretical support for policymakers, researchers, and industry practitioners. Leveraging the demand response potential of these industries promotes the green and low-carbon transformation of the power system, contributing to sustainable energy development and environmental protection goals.
The findings enhance understanding of the role of industrial energy-intensive loads in demand response and offer practical insights into optimizing their participation in the electricity market. Integrating industrial load flexibility improves renewable energy accommodation, reduces operational costs, and enhances grid stability. Future research directions include developing advanced scheduling models that better capture industrial complexities and uncertainties, exploring novel incentive schemes aligning industry and power system operator interests, and integrating emerging technologies like big data analytics and artificial intelligence to enhance predictive capabilities.
By addressing these aspects, the study contributes to the transition toward a more flexible, efficient, and sustainable power system. Effective engagement of industrial energy-intensive loads in demand response benefits the power system and provides economic and environmental advantages for the industries, fostering a mutually beneficial relationship between energy providers and consumers.
In summary, stimulating industrial load flexibility is pivotal in transitioning to greener power systems. Addressing challenges and seizing opportunities can lead to significant advancements in energy efficiency, economic savings, and environmental protection. This analysis serves as a foundation for future efforts to integrate industrial demand response into power system planning and operation, ultimately contributing to global sustainability objectives.

Key words： Differentiated industrial energy-intensive load flexibility analysis optimization scheduling methods solution algorithms

收稿日期: 2024-04-02

PACS:

TM73

基金资助:

国家自然科学基金面上项目资助（52477178）

通讯作者: 王艺博男,1989年生,副教授,硕士生导师,研究方向为电力系统需求侧响应、可再生能源整合、电力市场、风电特性分析等。 E-mail：wangyibofangyuan@126.com

作者简介: 赵旭东男,1999年生,助理实验师,硕士研究生,研究方向为电力系统需求侧响应、可再生能源整合。E-mail：XudongZhao8181@163.com

引用本文:

赵旭东, 王艺博, 王博闻, 刘闯, 赵一如. 考虑差异化工业高载能负荷灵活性挖掘的市场实施及调度模型研究综述[J]. 电工技术学报, 0, (): 20240537-20240537. Zhao Xudong, Wang Yibo, Wang Bowen, Liu Chuang, Zhao Yiru. Review of Market Implementation and Scheduling Models Considering the Flexibility Extraction of Differentiated Industrial Energy-Intensive Loads. Transactions of China Electrotechnical Society, 0, (): 20240537-20240537.

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