**7. Conclusions and Outlook**

The paper presents a methodology to identify and characterize energy flexibility measures in the industrial systems that constitute a production facility. The methodology is meant to be the basis of an industrial energy audit focusing on the topic of energy flexibility and hence providing vital information for enterprises to implement and exploit the energy flexibility capabilities of their production facilities. The proposed methodology follows a similar procedure than the current standards in industrial energy auditing aimed to improve industrial energy management and identify energy efficiency measures [28,29]. As those standards, and as previously stated in the requirements, the proposed methodology needed to be systematic, agile, current operation friendly, applicable to the plethora of industrial systems and its outcomes needed to be relevant for the industrial stakeholders. The methodology starts by establishing the available industrial systems in the facility. Allowing the definition of different system boundaries depending on the morphology of the analyzed production facility, and hence adapting to the heterogenous nature of industrial systems. The fact that the expected implementation objectives from energy flexible operation are incorporated in the methodology provides a clear end goal for the analyzed production facilities, and hence prioritizes outcomes to the specific company needs, providing relevancy to its outcomes. The suitability analysis allows focusing only on those relevant industrial systems, reducing the analysis duration contributing to its agility. This acts as a counterpart to the "big-consumers" approach usually used in energy efficiency auditing which might be misleading in the case of energy flexibility. The analysis of the physical and operative characteristics of the industrial system and the production characteristics of the facility allows considering the current operative nature of the analyzed industrial systems, guaranteeing its affinity with the current operation approach. Moreover, it provides a more agile approach to analyze the dynamic nature of industrial systems than building a dedicated system model. Overall, the methodology is systematic as it follows a linear approach where decisions are made following previously defined criteria and allowing a multi-level analysis of the industrial systems to identify the available EFMs. EFM-categories are analyzed and only discarded under specific techno-economic considerations, not on biased assumptions. The creation of the characterization framework, that consistently delimits the scope of each EFM, facilitates the subsequent evaluation, implementation and management.

The methodology is currently being implemented to identify and characterize EFMs in several production facilities within the framework of the second phase of Kopernikus-project "SynErgie". The results are expected to be used to evaluate the benefit-based performance of each EFM to then prioritize and facilitate their implementation [42]. The characterization parameters of the EFMs will also be used as input in the simulation of the production facility under energy flexible operation using digital twinning modelling. Moreover, the outcomes of the proposed methodology will also be used to develop energy management and optimization strategies for the analyzed production facilities. Continuous improvement of the methods and tools described in this article is expected as more production facilities are audited.

**Author Contributions:** A.T. and F.H. worked on the conceptualization of the methodology. A.T. developed the general structure and wrote the first draft of the manuscript. F.H. supported the review and editing of the manuscript. A.T. and F.H. worked together in the validation of the methodology, visualization and the application in practical examples. A.S. provided the idea, supervised the work of A.T., helped to review the article and was instrumental in the funding of this work. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the German Federal Ministry of Education and Research (BMBF), Grant No. 03SFK3G1.

**Acknowledgments:** The authors gratefully acknowledge the financial support of the Kopernikus-project "SynErgie" by the Federal Ministry of Education and Research (BMBF), and the project supervision of the project management organization Projektträger Jülich (PtJ).

**Conflicts of Interest:** The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
