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A strong heat load in buildings and cities during the summer is not a new phenomenon. However, prolonged heat waves and increasing urbanization are intensifying the heat island effect in our cities; hence, the heat exposure in residential buildings. The thermophysiological load in the interior and exterior environments can be reduced in the medium and long term, through urban planning and building physics measures. In the short term, an increasingly vulnerable population must be effectively informed of an impending heat wave. Building simulation models can be favorably used to evaluate indoor heat stress. This study presents a generic simulation model, developed from monitoring data in urban multi-unit residential buildings during a summer period and using statistical methods. The model determines both the average room temperature and its deviations and, thus, consists of three sub-models: cool, average, and warm building types. The simulation model is based on the same mathematical algorithm, whereas each building type is described by a specific data set, concerning its building physical parameters and user behavior, respectively. The generic building model may be used in urban climate analyses with many individual buildings distributed across the city or in heat–health warning systems, with different building and user types distributed across a region. An urban climate analysis (with weather data from a database) may evaluate local differences in urban and indoor climate, whereas heat–health warning systems (driven by a weather forecast) obtain additional information on indoor heat stress and its expected deviations.
We present an electrochemical model of a lithium iron phosphate/graphite (LFP/C6) cell that includes combined aging mechanisms: (i) Electrochemical formation of the solid electrolyte interphase (SEI) at the anode, leading to loss of lithium inventory, (ii) breaking of the SEI due to volume changes of the graphite particles, causing accelerated SEI growth, and (iii) loss of active material due to of loss percolation of the liquid electrolyte resulting from electrode dry-out. The latter requires the introduction of an activity-saturation relationship. A time-upscaling methodology is developed that allows to simulate large time spans (thousands of operating hours). The combined modeling and simulation framework is able to predict calendaric and cyclic aging up to the end of life of the battery cells. The aging parameters are adjusted to match literature calendaric and cyclic aging experiments, resulting in quantitative agreement of simulated nonlinear capacity loss with experimental data. The model predicts and provides an interpretation for the dependence of capacity loss on temperature, cycling depth, and average SOC. The introduction of a percolation threshold in the activity-saturation relationship allows to capture the strong nonlinearity of aging toward end of life (“sudden death”).
There is a strong interaction between the urban atmospheric canopy layer and the building energy balance. The urban atmospheric conditions affect the heat transfer through exterior walls, the long-wave heat transfer between the building surfaces and the surroundings, the short-wave solar heat gains, and the heat transport by ventilation. Considering also the internal heat gains and the heat capacity of the building structure, the energy demand for heating and cooling and the indoor thermal environment can be calculated based on the urban microclimatic conditions. According to the building energy concept, the energy demand results in an (anthropogenic) waste heat; this is directly transferred to the urban environment. Furthermore, the indoor temperature is re-coupled via the building envelope to the urban environment and affects indirectly the urban microclimate with a temporally lagged and damped temperature fluctuation. We developed a holistic building model for the combined calculation of indoor climate and energy demand based on an analytic solution of Fourier's equation and implemented this model into the PALM model.
Thermisch angetriebene (Adsorptions-)Kältemaschinen können mit einem verhältnismäßig geringen elektrischen Energieaufwand bzw. mit einer hohen elektrischen Leistungszahl Kälte bereitstel-len. Wird die zum Antrieb erforderliche Wärme aus industrieller Abwärme bereitgestellt, ist diese Kältebereitstellung energetisch effizienter als die Kältebereitstellung über eine Kompressionskäl-temaschine. Wird die Wärme jedoch in Kraft-Wärme-Kopplung bereitgestellt, ist die primärenergetische Bewertung sowohl von mehreren Teilwirkungsgraden als auch den Primärenergiefaktoren für den eingesetzten Brennstoff und die erzeugte bzw. bezogene elektrische Energie abhängig. Eine umfangreiche Messkampagne im Sommer 2018 liefert unter realitätsnahen Randbedingungen in einer Labor umgebung detaillierte Energiekennzahlen für einen typischen Tagesgang des Kältebedarfs. Damit gelingt es, Teilenergiekennwerte für die Planungspraxis abzuleiten und das Gesamtsystem energetisch mit einer konventionellen Kompressionskältemaschine zu vergleichen.