Search

The monitoring of the indoor air quality against the presence of contaminant sources is of paramount importance since it directly influences the occupants’ comfort, productivity, health and safety. Various approaches exist in the literature for monitoring and controlling the building environment. However, there is an identified lack of automated tools for evaluating, testing and comparing such approaches. This paper presents COMOB (COntaminat MOnitoring in Buildings), a developed MATLAB toolbox for sensor placement and contaminant monitoring in buildings. Specifically, the COMOB toolbox realizes an offline sensor placement procedure for positioning the contaminant sensors inside the building, such that the harmful effects due to a possible airborne contaminant event are minimized. In addition, an online contaminant monitoring approach is also implemented for detecting and isolating contaminant events in the building interior. Besides the aforementioned algorithms, the modularity of the COMOB toolbox facilitates the implementationof various other algorithms related to air-quality monitoring in buildings. In particular, the COMOB toolbox is able to generate multiple airflow and contaminant concentration data-sets by varying the building parameters; thus enabling the comprehensive and systematic evaluation and testing of the developed algorithms. Finally, the functionalities of the COMOB toolbox are demonstrated through a case-study corresponding to a real building model. COMOB is released under an open-source license, and is available at https://github.com/KIOS-Research/COMOB-Toolbox.

Grid-scale Battery Energy Storage Systems(BESSs) are gaining increasing consideration over the last fewyears since their connection has been shown to improve thedynamic behavior of the power grid. However, existingIntentional Controlled Islanding (ICI) approaches do notconsider the changes in structure and operation that modernpower systems are experiencing due to the increasing integrationof grid-scale BESSs. In this paper a previously proposed ICIalgorithm (for minimal power-flow disruption) is modified toconsider the impact of BESSs on the power system. Morespecifically, the proposed modified ICI algorithm aims todetermine the optimal islanding solution that minimizes thepower imbalance between the generation (i.e., synchronousgenerators and the BESSs) and the consumption (i.e., loads andBESSs) within each island. This is achieved through determiningthe island that each BESS should be, and the optimal activepower set-points for the BESSs that minimize the powerimbalance in the formed islands.