Zur semantischen Interoperabilität in der Energiebranche: CIM IEC 61970

This contribution provides an introduction to the Common Information Model CIM which is an international standard maintained by the International Electrotechnical Commission IEC. Today’s market requirements towards the model are discussed, furthermore, we give an introduction to the history of the CIM, its serializations and scope of application. The contribution concludes with an overview of future use of the CIM for both science and commerce. Briefly, we focus on:

Message-based loose coupling of information systems

Exchange of power grid topologies with minimal communication and data overhead

Data quality assurance using ontology-based meta annotations and

Integration of heterogeneous standards in the utility domain. The contribution presents solutions to the use cases providing a better information management for the utility utilizing the Common Information Model.

     

Business process model abstraction: a definition, catalog, and survey

The discipline of business process management aims at capturing, understanding, and improving work in organizations by using process models as central artifacts. Since business-oriented tasks require different information from such models to be highlighted, a range of abstraction techniques has been developed over the past years to manipulate overly detailed models. At this point, a clear understanding of what distinguishes these techniques and how they address real world use cases has not yet been established. In this paper we systematically develop, classify, and consolidate the use cases for business process model abstraction and present a case study to illustrate the value of this technique. The catalog of use cases that we present is based on a thorough evaluation of the state of the art, as well as on our cooperation with end users in the health insurance sector. It has been subsequently validated by experts from the consultancy and tool vendor domains. Based on our findings, we evaluate how the existing business process model abstraction approaches support the discovered use cases and reveal which areas are not adequately covered, as such providing an agenda for further research in this area.     

From fine-grained to abstract process models: A semantic approach

Organizations actively managing their business processes face a rapid growth of the number of process models that they maintain. Business process model abstraction has proven to be an effective means to generate readable, high-level views on business process models by showing coarse-grained activities and leaving out irrelevant details. In this way, abstraction facilitates a more efficient management of process models, as a single model can provide for many relevant views. Yet, it is an open question how to perform abstraction in the same skillful way as experienced modelers combine activities into more abstract tasks. This paper presents an approach that uses semantic information of a process model to decide on which activities belong together, which extends beyond existing approaches that merely exploit model structural characteristics. The contribution of this paper is twofold: we propose a novel activity aggregation method and suggest how to discover the activity aggregation habits of human modelers. In an experimental validation, we use an industrial process model repository to compare the developed activity aggregation method with actual modeling decisions, and observe a strong correlation between the two. The presented work is expected to contribute to the development of modeling support for the effective process model abstraction.     

Automatic data collection for enterprise architecture models

Enterprise Architecture (EA) is an approach used to provide decision support based on organization-wide models. The creation of such models is, however, cumbersome as multiple aspects of an organization need to be considered, making manual efforts time-consuming, and error prone. Thus, the EA approach would be significantly more promising if the data used when creating the models could be collected automatically—a topic not yet properly addressed by either academia or industry. This paper proposes network scanning for automatic data collection and uses an existing software tool for generating EA models (ArchiMate is employed as an example) based on the IT infrastructure of enterprises. While some manual effort is required to make the models fully useful to many practical scenarios (e.g., to detail the actual services provided by IT components), empirical results show that the methodology is accurate and (in its default state) require little effort to carry out.     

A distributed simplex algorithm for degenerate linear programs and multi-agent assignments

In this paper we propose a novel distributed algorithm to solve degenerate linear programs on asynchronous peer-to-peer networks with distributed information structures. We propose a distributed version of the well-known simplex algorithm for general degenerate linear programs. A network of agents, running our algorithm, will agree on a common optimal solution, even if the optimal solution is not unique, or will determine infeasibility or unboundedness of the problem. We establish how the multi-agent assignment problem can be efficiently solved by means of our distributed simplex algorithm. We provide simulations supporting the conjecture that the completion time scales linearly with the diameter of the communication graph.     

Direction of Arrival Estimation using EM-ESPRIT with Nonuniform Arrays

This paper deals with the problem of the Direction Of Arrival (DOA) estimation with nonuniform linear arrays. The proposed method is based on the Expectation Maximization method where ESPRIT is used in the maximization step. The key idea is to iteratively interpolate the data to a virtual uniform linear array in order to apply ESPRIT to estimate the DOA. The iterative approach allows one to improve the interpolation using the previously estimated DOA. One of this method’s novelties lies in its capacity of dealing with any nonuniform array geometry. This technique manifests significant performance and computational advantages over previous algorithms such as Spectral MUSIC, EM-IQML and the method based on manifold separation technique. EM-ESPRIT is shown to be more robust to additive noise. Furthermore, EM-ESPRIT fully exploits the advantages of using a nonuniform array over a uniform array: simulations show that for the same aperture and with a smaller number of sensors, the nonuniform array presents almost identical performance as the equivalent uniform array.     

Corrosion in alkanolamine used for acid gas removal: From natural gas processing to CO2 capture

The aim of this paper is to review some of the parameters influencing the corrosivity of alkanolamine solvents used for natural gas purification or for CO₂ capture. In the light of literature data and of new experimental results, the influences of temperature and of acid gas loading are discussed. These two parameters appear to have a strong impact on corrosion rates of carbon steel, with extrapolated corrosion rates of several tens of mm/year for the highest temperature and acid gas loading condition. It is then proposed to discuss about similarities and differences between natural gas processing and CO₂ capture from flue gas. For both applications, alkanolamine processes are used. Still, differences can be found in operating parameters. The most significant gap concerns the lean amine sections. In acid gas treatment, the regeneration of the solvent is often performed down to zero loading. Under these conditions, an extremely low corrosivity of the lean solvent is expected. On the contrary, CO₂ capture from flue gas requires only a partial stripping of the CO₂ in the regeneration section, due to energy efficiency reasons. Then, the lean solvent still contains some acid gas, and subsequently a higher corrosivity. Finally, the general principles for material selection for the different parts of acid gas removal units are discussed, considering both cases of natural gas processing or CO₂ capture.