Jean-Louis Scartezzini

TL;DR: In this paper, an algorithm for the simulation of occupant presence, to be later used as an input for future occupant behaviour models within building simulation tools, is described, where occupant presence is considered as an inhomogeneous Markov chain interrupted by occasional periods of long absence, the model generates a time series of the state of presence of each occupant of a zone, for each zone of any number of buildings.

TL;DR: In this paper, a stochastic-robust optimization method was developed to consider both low impact variations and extreme events, and applied to 30 cities in Sweden, by considering 13 climate change scenarios, reveal that uncertainties in renewable energy potential and demand can lead to a significant performance gap brought by future climate variations and a drop in power supply reliability due to extreme weather events.

TL;DR: A comprehensive review of available tools for modelling outdoor human comfort and thermal stress is presented, explains the physical equations that drive these models, and shows their applicability based on climate and the findings of previous research.

TL;DR: In this paper, a bottom-up modelling approach together with a set of calibration methodologies is presented to predict residential building occupants' time-dependent activities, for use in dynamic building simulations.

TL;DR: Wang et al. as mentioned in this paper investigated the performance of a representative apartment building in the city of Shanghai and evaluated the optimum solutions by using a developed optimization approach, which includes three major steps of 1) setting the model for multi-objective optimization, 2) sensitivity analysis for reducing the dimension of input variables, and 3) multiorientive optimization by using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) coupled with the Artificial Neural Network (ANN), among which a novel indicator for evaluating the annual indoor thermal comfort of residential buildings of Shanghai named Comfort Time