Skip to content

Process Reconfiguration of Industrial Users to Support the Low-carbon Transition of Power Systems

Sep 2026 · DOAJ (DOAJ: Directory of Open Access Journals)
Integrated Energy Systems Optimization

Abstract

SignificanceAgainst the backdrop of the carbon peaking and carbon neutrality goals, power systems are integrating a high share of renewable energy. However, renewable power generation is uncertain, variable, and intermittent. This makes it difficult to maintain supply-demand balance in power systems. Therefore, power systems urgently need flexible resources that can provide effective balancing support. Supply-side flexibility still relies heavily on thermal power units. These units are increasingly constrained by carbon reduction requirements and technical limits. It is therefore necessary to further unlock the flexibility potential of demand-side resources. Industrial users are characterized by substantial electricity consumption, substantial carbon-reduction potential, considerable adjustable capacity, and mature automation and control systems. At the technical level, industrial users can improve their process routes. At the operational level, they can reschedule production batches and adjust equipment power. These measures create flexibility for power-system balancing and low-carbon operation. Therefore, industrial users have become a major focus for developing demand-side flexibility for carbon reduction. Industrial users are evolving from conventional loads into integrated resources that can function as generation, load, and energy storage. This transition gives industrial users three main resource attributes. Distributed energy, self-owned power plants, and waste-heat generation provide on-site power. Adjustable production loads can coordinate production with system dispatch. Electrical, thermal, hydrogen, and intermediate-product storage enable energy transfer across time. Therefore, this paper provides a review of the process reconfiguration of industrial users in supporting the low-carbon transition of power systems.ProgressFirst, from the perspective of the transition of industrial users from consumers to prosumers, their basic connotation and main resource classifications are summarized. Second, representative industrial scenarios are examined, including iron and steel, electrolytic aluminum, and cement. For each scenario, the process characteristics and flexibility mechanisms are analyzed. For the steel industry, special attention is given to the flexibility differences among three process routes: the blast furnace-basic oxygen furnace long-process route, the scrap-based short-process route, and the hydrogen-based direct reduced iron (H‒DRI) short-process route. This research also examines the multi-level regulation capability of electrolytic aluminum. This capability mainly comes from the thermal inertia of aluminum reduction cells. It also discusses the flexibility of the cement industry in terms of start-stop scheduling and smooth power adjustment. The industries differ in their dominant flexibility mechanisms. Long-process steelmaking mainly relies on self-generation fueled by by-product gases. Scrap-based electric-arc-furnace (EAF) production can shift loads through batch scheduling. In H‒DRI processes, electrolyzers, hydrogen storage, and intermediate-product storage can be coordinated to provide flexibility. Electrolytic aluminum provides fast frequency response and different levels of load adjustment under cell thermal constraints. Cement plants mainly adjust crushing, raw-material preparation, and grinding. Clinker kilns generally remain in continuous operation. For flexibility potential assessment based on the process reconfiguration of industrial users, this paper proposes a three-dimensional modeling framework for industrial users. The framework covers physical characteristics, economic incentives, and carbon benefits. The physical dimension focuses on coupling constraints among material flows and energy flows. The economic dimension considers the willingness of users to provide flexibility. The dimension of carbon benefit captures how carbon reduction benefits affect feasible regulation boundaries. The assessment should distinguish theoretical potential from actually available potential. Physical modeling identifies the feasible regulation region under equipment, production, material-balance, and energy-coupling constraints. Economic modeling accounts for energy costs, production adjustment losses, operational risks, and management costs. Carbon benefit modeling needs to further incorporate marginal carbon emissions, green electricity consumption, carbon market compliance, and product carbon footprint accounting. For flexibility control strategies enabled by the process reconfiguration of industrial users, coordination should be designed across short-, medium-, and long-term time scales. At short timescales, electrolytic aluminum is a representative resource for rapid frequency response. At medium timescales, batch processes such as EAF steelmaking can enable intraday load shifting. At long timescales, electrolysis combined with hydrogen storage can support cross-seasonal balancing. These decisions must also account for multiple uncertainties. These include renewable energy output, market prices, product demand, equipment states, and material supply. The interactions among multiple market mechanisms, including electricity and carbon markets, should also be considered.Conclusions and ProspectsBy participating in power system flexibility regulation, industrial users can promote renewable energy integration, reduce the carbon footprint of industrial products, and support the coordinated low-carbon transition of both the industrial and power sectors. Future research should develop a unified model that captures material flows, energy flows, and industrial production constraints. Furthermore, it is essential to promote the deep integration of artificial intelligence with industrial production and power system control. Meanwhile, credible accounting frameworks for industrial carbon emissions and product carbon footprints must be established, alongside the improvement of multi-market benefit allocation mechanisms. Ultimately, these efforts will enable the large-scale, normalized, and market-driven participation of industrial users in power system flexibility regulation.

View source

Similar papers

#artificial intelligence Open access May 2023

Evaluating the Performance of Large Language Models on GAOKAO Benchmark

GAOKAO-Bench is introduced, an intuitive benchmark that employs questions from the Chinese GAOKAO examination as test samples, including both subjective and objective questions that contribute a robust evaluation benchmark for future large language models and offers valuable insights into the advantages and limitations of such models.

Xiaotian Zhang, Chun-yan Li, Yi Zong et al. · 216 citations · ⚡17
#artificial intelligence Open access Jul 2024

Gender, Race, and Intersectional Bias in Resume Screening via Language Model Retrieval

This work investigates the possibilities of using LLMs in a resume screening setting via a document retrieval framework that simulates job candidate selection and finds that the MTEs are biased, significantly favoring White-associated names in 85% of cases and female-associated names in only 11.1% of cases.

Kyra Wilson, Aylin Caliskan · 131 citations · ⚡8

PRISM: Self-Pruning Intrinsic Selection Method for Training-Free Multimodal Data Selection

Empirically, PRISM reduces the end-to-end time for data selection and model tuning to just 30% of conventional pipelines, and achieves this efficiency while simultaneously enhancing performance, surpassing models fine-tuned on the full dataset across eight multimodal and three language understanding benchmarks.

Jinhe Bi, Yifan Wang, Danqi Yan et al. · 73 citations · ⚡4
#artificial intelligence Conference Open access Apr 2020

ECCOLA - a Method for Implementing Ethically Aligned AI Systems

The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.

Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson · 64 citations · ⚡6

Let the Flows Tell: Solving Graph Combinatorial Optimization Problems with GFlowNets

This paper designs Markov decision processes (MDPs) for different combinatorial problems and proposes to train conditional GFlowNets to sample from the solution space and demonstrates that GFlowNet policies can efficiently find high-quality solutions.

Dinghuai Zhang, H. Dai, Esmeralda S. Whitammer et al. · 59 citations · ⚡8

Ethically Aligned Design of Autonomous Systems: Industry viewpoint and an empirical study

An empirical study on the current state of practice in artificial intelligence ethics is conducted by means of a multiple case study of five case companies, which indicates a gap between research and practice in the area.

Ville Vakkuri, Kai-Kristian Kemell, Joni Kultanen et al. · 56 citations · ⚡6

Related blog posts

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.