PV-EV Integrated Home Energy Management Considering Residential Occupant Behaviors

Rooftop photovoltaics (PV) and electrical vehicles (EV) have become more economically viable to residential customers. Most existing home energy management systems (HEMS) only focus on the residential occupants’ thermal comfort in terms of indoor temperature and humidity while neglecting their other behaviors or concerns. This paper aims to integrate residential PV and EVs into the HEMS in an occupant-centric manner while taking into account the occupants’ thermal comfort, clothing behaviors, and concerns on the state-of-charge (SOC) of EVs. A stochastic adaptive dynamic programming (ADP) model was proposed to optimally determine the setpoints of heating, ventilation, air conditioning (HVAC), occupant’s clothing decisions, and the EV’s charge/discharge schedule while considering uncertainties in the outside temperature, PV generation, and EV’s arrival SOC. The nonlinear and nonconvex thermal comfort model, EV SOC concern model, and clothing behavior model were holistically embedded in the ADP-HEMS model. A model predictive control framework was further proposed to simulate a residential house under the time of use tariff, such that it continually updates with optimal appliance schedules decisions passed to the house model. Cosimulations were carried out to compare the proposed HEMS with a baseline model that represents the current operational practice. The result shows that the proposed HEMS can reduce the energy cost by 68.5% while retaining the most comfortable thermal level and negligible EV SOC concerns considering the occupant’s behaviors.

Improving the energy efficiency of an office building by applying a thermal comfort model

The building represents one of the main actors of global warming of the planet because of the significant amounts of energy consumed. In Benin, 44,38% of electrical energy is consumed by office and service buildings. This is explained by the excessive use of air conditioning systems due to the lack of a thermal comfort index specific to the region. This work therefore focuses on assessing the impact of the choice of a thermal comfort model on the energy efficiency of buildings. For this purpose, an office building was chosen in the south of Benin and comfort surveys were conducted among the occupants. The model selected for this purpose is the adaptive model developed by López-Pérez and al. for air-conditioned buildings in humid tropical regions. Subsequently, a monitoring campaign of meteorological, hygrothermal and energetic data of the building was carried out during six months. The results obtained show that the average temperature of the offices (Tf ≈ 24°C) during the hours of occupancy is relatively lower than the comfort temperature determined with the model (Tc = 26.2°C). Moreover, the different simulations carried out under TRNSYS by substituting the office temperatures by the comfort temperature show a reduction of about 20% of the building’s energy consumption. This shows the importance of the comfort model of López-Pérez and al. in improving the energy efficiency of the building.

Electric Heating Load Forecasting Method Based on Improved Thermal Comfort Model and LSTM

The accuracy of the electric heating load forecast in a new load has a close relationship with the safety and stability of distribution network in normal operation. It also has enormous implications on the architecture of a distribution network. Firstly, the thermal comfort model of the human body was established to analyze the comfortable body temperature of a main crowd under different temperatures and levels of humidity. Secondly, it analyzed the influence factors of electric heating load, and from the perspective of meteorological factors, it selected the difference between human thermal comfort temperature and actual temperature and humidity by gray correlation analysis. Finally, the attention mechanism was utilized to promote the precision of combined adjunction model, and then the data results of the predicted electric heating load were obtained. In the verification, the measured data of electric heating load in a certain area of eastern Inner Mongolia were used. The results showed that after considering the input vector with most relative factors such as temperature and human thermal comfort, the LSTM network can realize the accurate prediction of the electric heating load.

Tuhouse: prototipo de vivienda social sostenible de alta densidad para el trópico

This work presents the results of research made within the framework of the Solar Decathlon LAC 2019 international competition, which aimed at designing and building a prototype of a TUHOUSE (Technically Unique House Using Solar Energy) affordable dwelling, at a 1:1 scale, a house that is capable of incorporating sustainable and bioclimatic strategies for the tropical region. The methodology consisted of a design workshop with interdisciplinary work from the different architecture and engineering areas in programs at the Universities of San Buenaventura and Autonoma de Occidente (Cali, Colombia). The main contribution of the methodology was to achieve interdisciplinary work from the initial stages, alongside students and teachers participating in the construction of the prototype, before finally checking its performance using the contest’s tests. Among the results that stand out from of this experience, are an urban proposal with high habitability and density, the testing of passive design strategies focused on a prototype envelope that can be replicated in similar conditions, but also the importance of the question about the validity of the thermal comfort model proposed for tropical regions.

Modeling and Experimental Investigation of Thermal Comfort and Energy Consumption in a Battery Electric Bus

In battery electric buses (e-buses), the substantial energy consumption of the heating, ventilation, and air conditioning (HVAC) system can cause significant reductions of the available travel range. Additionally, HVAC systems are often operated at higher levels than what required for the thermal comfort of the passengers. Therefore, this paper proposes a method to experimentally investigate the influence of the HVAC system on the energy consumption and thermal comfort in a 12m e-bus. An appropriate thermal comfort model is identified and the required climatic input parameters are selected and measured with self-developed sensor stations. The energy consumption of the e-bus, the state of charge (SoC) of the battery and the available travel range are measured by an embedded data logger. Climatic measurements are then performed with heating on and off on a Berlin bus line in winter conditions. The results show that the energy consumption of the e-bus is increased by a factor of 1.9 with heating on, while both the SoC and travel range are reduced accordingly. Comparing the thermal comfort with heating on and off, a decrease from “comfortable” to “slightly uncomfortable but acceptable” is observed.

Thermal comfort in the low energy building - validation and modification of the Fanger model

Nowadays, we spend most of our time inside buildings. Thus, ensuring adequate thermal comfort is an important issue. The paper discusses the issue of thermal comfort assessment in the intelligent low energy building “Energis” of Kielce University of Technology (Poland). The tests conducted in a selected lecture theater focused on collecting anonymous questionnaires containing thermal sensation and air quality votes of the respondents as well as performing measurements of indoor air parameters (air and globe temperatures, relative humidity, air velocity and CO2 concentration). Based on the obtained data a comparison has been done between the actual sensation votes of the volunteers and the calculation results performed with the Fanger thermal comfort model. Two indices have been considered in the paper: PMV (Predicted Mean Vote) and PPD (Predicted Percentage Dissatisfied). A modification of the model has also been proposed, which considers the impact of the carbon dioxide concentration on thermal comfort.