This work aims to propose a pseudo-measurement modeling method for Distribution State Estimation (DSE) application embedded in a Distribution Management System (DMS). The entire system is already installed on the distribution MV network of Sanremo, in the North of Italy, within the Smartgen research project. The acquisition architecture consists of a SCADA system, which allows the data exchange from meters installed in the MV-LV substations. In order to satisfy the system observability conditions and to perform the State Estimation (SE) algorithm, real-time measures need to be integrate with the pseudo-measures of the non-monitored substations. The paper investigates a load modeling technique, based on Artificial Neural Network (ANN) and Fourier decomposition, that allow the generation of pseudomeasurements starting from the historical database of the monitored substations.
This paper describes a knowledge-based system (KBS) designed to support a federated environment for simulating critical infrastructure models. A federation of simulators is essentially a "system of systems," where each simulator represents an entity that operates independently with its own behavior and purpose. The interactions among the components of the federated system of systems exhibit critical infrastructure vulnerabilities as emergent behavior; these vulnerabilities cannot be analyzed and simulated by considering the behavior of each system component individually. The KBS, which is based on ontologies and rules, provides a semantic foundation for the federated simulation environment and enables the dynamic binding of different critical infrastructure models. The KBS-based simulation environment can be used to identify latent critical infrastructure interdependencies and to test assumptions about interdependencies.
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