Publication

@article{boroukhian2025semantic,

title = {Semantic middleware for demand response systems: Enhancing data interoperability in green electricity management for manufacturing},

author = {Tina Boroukhian and Kritkorn Supyen and Christopher William Mclaughlan and Atit Bashyal and Tuan Pham and Hendro Wicaksono},

doi = {https://doi.org/10.1016/j.compind.2025.104354},

year  = {2025},

date = {2025-11-01},

urldate = {2025-01-01},

journal = {Computers in Industry},

volume = {172},

pages = {104354},

publisher = {Elsevier},

abstract = {Optimizing the consumption of green electricity across sectors, including manufacturing, is a critical strategy for achieving net-zero emissions and advancing clean production in Europe by 2050. Demand Response (DR) represents a promising approach to engaging power consumers from all sectors in the transition toward increased utilization of renewable energy sources. A functional DR system for manufacturing power consumers requires seamless data integration and communication between information systems across multiple domains, including both power consumption and generation. This paper introduces a semantic middleware specifically designed for DR systems in the manufacturing sector, using an ontology as the central information model. To develop this ontology, we adopted a strategy that reuses and unifies existing ontologies from multiple domains, ensuring comprehensive coverage of the data requirements for DR applications in manufacturing. To operationalize this strategy, we designed novel methods for effective ontology unification and implemented them within a dedicated unification tool. This process was followed by data-to-ontology mapping to construct a knowledge graph, and was further extended through the development of a querying system equipped with a natural language interface. Additionally, this paper offers insights into the deployment environment of the semantic middleware, encompassing multiple data sources and the applications that utilize this data. The proposed approach is implemented in multiple German manufacturing small and medium-sized enterprises connected to a utility company, demonstrating consistent data interpretation and seamless information integration. Consequently, the method offers practical potential for optimizing green electricity usage in the manufacturing sector and supporting the transition toward a more sustainable and cleaner future.},

keywords = {data management, demand response system, energy management, green energy, industry 4.0, industry 5.0, knowledge management, manufacturing, ontologies, semantic web, sustainability},

pubstate = {published},

tppubtype = {article}

}