This paper is a review of the different single and three-phase harmonic load flow formulations of the bibliography. It presents the data, unknowns, and equations of these formulations in balanced network consideration. The influence of the main harmonic load flow hypothesis (harmonic interaction and fundamental power consumption consideration) in the final load flow results is studied in an example.

Self-healing is capacity of the network to restore automatically the network when an outage occurs. Smart grids makes power restoration on the one hand more complex due to distributed generation, distributed storage and mobile loads (electrical vehicles), but on the other hand the observability is improved with the introduction of smart meters and IEDs (intelligent electronic devices). The relevant differences between traditional distribution networks and smart grids for power restoration are reviewed. This paper formulates the problem of self-healing in smart grids. Furthermore, the network features and constraints are explained. Moreover, the restoration goals are given. In short the contribution of this paper are: a definition of self-healing, the formalization of this concept (graph, constraints, goals), a description of the relevant smart grid features and discussion of the complexity of the problem.

This paper presents a complete methodology, together with its implementation as a web application, for monitoring smart buildings. The approach uses unfold-Principal Component Analysis (unfold-PCA) as a batch projection method and two statistics, Hotelling’s T-squared (T²) and the squared prediction error (SPE), for alarm generation resulting in two simple control charts independently on the number of variables involved. The method consists of modelling the normal operating conditions of a building (entire building, room or subsystem) with latent variables described expressing the principal components. Thus, the method allows detecting faults and misbehaviour as a deviation of previously mentioned statistics from their statistical thresholds. Once a fault or misbehaviour is detected, the isolation of sensors that mostly contribute to such detection is proposed as a first step for diagnosis. The methodology has been implemented under a SaaS (software as a service) approach to be offered to multiple buildings as an on-line application for facility managers. The application is general enough to be used for monitoring complete buildings, or parts of them, using on-line data. A complete example of use for monitoring the performance of the air handling unit of a lecture theatre is presented as demonstrative example and results are discussed