**5. Experimental evaluation**

In order to validate the approach, we have developed intelligent control platform in an electrical power system. This system integrates management knowledge into network resource specifications. We study an example of alarm detection and intelligent resolution of incidents related to a private network. We have used a telecommunications network belonging to a company in the electricity sector Sevillana-Endesa (SE), a Spanish electricity company. OntoEnter is used to optimize the operation of hundreds of connected sensors currently installed. Many of these sensors are wireless because they can be installed more quickly and at less cost than their wired equivalents, often with no required downtime. These low-cost wireless sensors and accompanying analytics can dramatically improve plant performance, increase safety, and pay for themselves within months. The Spanish electricity grid has a wireless network in the regional high voltage grid. Part of the long distance traffic in this network is controlled by a wireless intelligent system distributed through this private network. The use of knowledge integration in agents can help the system administrator to use the maximum capabilities of the intelligent network management platform without having to use another specification language to customize the application [35].

The intelligent development of the system must meet the following requirements: it must be robust, and the management activity should not interfere with the normal operations of the network and should only intervene when necessary. We will use the SCADA system due to management limitations of the network communication equipment. SCADA consists of the following subsystems **Figure 7**.


SCADA systems are configured around standard basic functions such as data acquisition, monitoring and event processing, archiving and data storage analysis, etc. The RTU encodes sensor inputs in protocol format and sends them to the SCADA master. The fundamental role of an RTU is the acquisition of various types of power process data, accumulation, packaging,

**Figure 7.** Elements of the prototype.

The profile agent is an environment, in which software agents can be executed to retrieve E-learning resources and which is wrapped by a Web service. This configuration contains the user requirements that typically described the relative needs, tasks, and goals of the user for an individual search. Profile agents help students with the search, according to the specifications they made. Search parameters in a profile, the initiation of a search, or access to the list of retrieved learning objects can be controlled by invoking appropriate search operations that extract learning resource metadata. Ideally, profile agents learn from their experiments, communicate and cooperate with other agents, around in DL. A profile agent uses a registry to locate learning searches. The agent compares the metadata and the search keywords for possible matches and presents the search results to the user. For this, a statistical analysis has been done to determine the importance values and establishing specified

In order to validate the approach, we have developed intelligent control platform in an electrical power system. This system integrates management knowledge into network resource specifications. We study an example of alarm detection and intelligent resolution of incidents related to a private network. We have used a telecommunications network belonging to a company in the electricity sector Sevillana-Endesa (SE), a Spanish electricity company. OntoEnter is used to optimize the operation of hundreds of connected sensors currently installed. Many

user requirements.

**5. Experimental evaluation**

**Figure 6.** User profiles, graphical user interface.

136 Knowledge Management Strategies and Applications

and data conversion in a form that can be communicated back to the master, interpretation and output of the commands received from the master, local filtering performance, calculation, and processes to allow specific functions to be performed locally. The supervision below and RTU includes all network devices and substation and feeder levels like circuit breakers, reclosers, autosectionalizers, the local automation distributed at these devices, and the communications infrastructure [36].

OntoEnter can monitor, in real time, the network's main parameters, making use of the information supplied by the SCADA, placed on the main company building, and the RTUs are installed at different stations. From the information provided, the operator can take action to solve any errors that may arise or send a technician to repair the station equipment. OntoEnter allows the operator to search for information, alarms, or digital and analog parameters of measurement, registered in each IA or RTU. The system has the ability to select the IA that is best suited to satisfy the client's requirements, without the client being aware of the details about the agent. In addition, the AI is able to communicate and negotiate with the other IAs. Collaborative IAs are useful, especially when a task involves several systems in the network.
