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Energy Market Integration Deployment Scenario

The Energy Market Integration deployment scenario describes how a utility might integrate Energy Market Transaction Servers with utility operational systems, discussing the management of what data is exchanged and how data is exchanged.

Energy markets are in a state of flux at this time, and will most likely never result in a single market environment. Therefore, this deployment scenario raises interesting questions about how much can or should be standardized and how much must be left to changing circumstances. Although these questions are true to some degree for all environments, the market operations environment is particularly changeable.

Therefore, a uniform strategy for complete energy market transaction service integration may not be possible. While it is clear that CME based transaction servers can be integrated with the CIM with much difficulty, ETSO and eTagging-based energy trading systems present the a more complex deployment scenario from the point of view of managing semantic heterogeneity. The reason is that unlike internal application or data integration where data semantics can be assimilated, the exact meaning of external energy trading may not be able to be modified. That is, instead of creating adapters to transform the meaning of data, energy market data must be reproduced more exactly for use in analysis applications.

At the same time, energy market semantics do often conflict with operational semantics. For example, ETSO and NERC eTagging messaging models were developed independently of the CIM. As a result, utilities may not be able to achieve complete harmonization of market and operational semantics. In this case, the best that can be done is to precisely describe the differences rather than attempt to change the different semantics. Fortunately, as described in Section 3, RDF and OWL provide this capability.

In practice RDF and OWL can be used to describe the differences in information models in a precise computer digestible way. Since both ETSO and NERC have only defined a set of message schemas and not unified information models, an information model will need to be derived from the message schemas and then linked to the CIM/CME classes and properties.

With regard to how data is exchanged, generally IntelliGrid Architecture-based energy market server integration recommends the use of information model technologies by market applications, including the use of electronically available metadata of these information models so that their names, structures, and differences are discoverable. Specifically, instead of using a simple message passing API to link applications, IntelliGrid Architecture-based application integration employs a complex model-enabled message passing and data access APIs such as IEC61970 Generic Eventing and Subscription and Generic Data Access. Note that both cross-industry as well as the model-enabled GID APIs are generic in that they can be applied to any message type and do not hard code message specific semantics into the API.

The diagram below depicts an ETSO ebXML or NERC eTagging-based Energy Market network:


Figure 22 ETSO ebXML Or NERC eTagging Based Energy Market Server



Figure 22 illustrates a utility energy market server communicating with external trading partners via the Internet. In order to perform analysis, this energy market data must be integrated with the rest of the utility enterprise (subject to the market rules on authorized access).

Figure 23 CME Based Integrated Energy Market Systems


Figure 23 illustrates a GID based adapter that exposes a CME information model. That is, the GID has the capability to expose a namespace created in accordance with harmonized CIM/CME models.


Figure 24 ETSO or eTagging Based Integrated Energy Market Systems


Figure 24 illustrates a GID based adapter that not only exposes an eTagging or ETSO information model but also their exact semantic relationship to CIM/CME. That is, the GID has the capability to not only expose a single information model, but also multiple associated models as well as their inter relationship.

The question remains how well an analysis application can perform over this semantic infrastructure. In the case of a CME based market server, an analysis application can perform calculations based on a set of known facts. In the case of an ETSO or eTagging based market server, an analysis application can only perform calculations based on a set of inferences. An inference is a conclusion based on data that is not completely semantically uniform. Inferencing technology is a rapidly growing field of study particularly as it applies to analysis and searching of Web based resources. However, its use has yet to be tested or proven in a more critical environment.

Again, security, network/enterprise management, and data management requirements need to be incorporated in this Use Case. The security requirements are shown in IntelliGrid Architecture RTO to Market Participants Environment are much more extensive than for the previous Use Cases, and include:

       Identity Establishment Service

       Authorization Service for Access Control

       Information Integrity Service

       Confidentiality Service

       Security Against Denial-of-Service Service

       Inter-Domain Security Service

       Non-repudiation Service

       Security Assurance Service  

       Audit Service 

       Security Policy Service

       Path and Routing Quality of Security

       Firewall Transversal

       Privacy Service

       User Profile and User Management

       Security Protocol mapping

       Security Discovery

Network and enterprise management requirements, as also shown in IntelliGrid Architecture RTO to Market Participants Environment, can rely on readily available standard technologies, such as the IETFs Simple Network Management Protocol (SNMP) and Web-Based Enterprise Management (WBEM).

Data management requirements, as discussed in this Use Case, is much more difficult than in the other Use Cases described in this section, since common information models will most likely never be standardized or implemented globally. Therefore, data management will have to rely much more heavily on metadata discovery of the individual market information models, and as much automated mapping as possible through the capabilities described above, and through technologies such as RDF. Again, the need for guidelines, tools, and automated methodologies is paramount to simplifying this complex task.


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Copyright EPRI 2004