Problems with inaccurate prediction of electricity generation from photovoltaic (PV) farms cause severe operational, technical, and financial risks, which seriously affect both their owners and grid operators. Proper prediction results are required for optimal planning the spinning reserve as well as managing inertia and frequency response in the case of contingency events. In this work, the impact of a number of meteorological parameters on PV electricity generation in Poland was analyzed using the Pearson coefficient. Furthermore, seven machine learning models using Lasso Regression, K–Nearest Neighbours Regression, Support Vector Regression, AdaBoosted Regression Tree, Gradient Boosted Regression Tree, Random Forest Regression, and Artificial Neural Network were developed to predict electricity generation from a 0.7 MW solar PV power plant in Poland. The models were evaluated using determination coefficient ($R^2$), the mean absolute error ($MAE$), and root mean square error ($RMSE$). It was found out that horizontal global irradiation and water saturation deficit have a strong proportional relationship with the electricity generation from PV systems. All proposed machine learning models turned out to perform well in predicting electricity generation from the analyzed PV farm. Random Forest Regression was the most reliable and accurate model, as it received the highest $R^2$ (0.94) and the lowest $MAE$ (15.12 kWh) and $RMSE$ (34.59 kWh).

Nowadays, we can observe a growing interest in passive buildings due to global climate change, environmental concerns, and growing energy costs. However, developing a passive building is associated with meeting many Passive House requirements, which results in their increased complexity as well as many challenges and risks which could threaten the successful completion of the project. Risk management is a key tool enabling meeting today’s challenging passive house project’s demands connected with quality, costs, deadlines, and legal issues. In this paper, a new model of risk management dedicated for passive buildings based is proposed, in which a novel Fuzzy Fault Tree integrated with risk response matrix was developed. We proposed 171 risk remediation strategies for all 16 recognized risks in passive buildings projects. We show how to apply the proposed model in practice on one passive building example. Thanks to applying the proposed risk management model an effective reduction of the risks of the basic event is enabled, leading to a significant reduction of the top event risk. The proposed model is useful for architects, installation designers, contractors, and owners who are willing to develop attainable and successful passive buildings projects that benefit all stakeholders.

This paper presents experimental and theoretical studies of heat transfer through single- and double-glazed windows with electrical heating of the internal surfaces. Heating is achieved by applying a voltage to the low emissivity coating of the inner glass. A thermophysical model has been developed to simulate the heat transfer through these units, allowing us to determine their thermal characteristics. Experimental data are used to validate the numerical model. The resulting heat flux and temperature distributions on the external and internal surfaces of electrically heated double-glazed units are analysed. According to the results of experimental and numerical studies, it was found that the adopted electric heating scheme allows 83–85% of the heat to enter the room and 15–17% is removed to the outside. This makes it possible to increase the radiation component of the heat flow from the window to the room and improve the thermal comfort in the room. In general, this article shows that existing industrial windows with low-emissivity glass surface coating can be upgraded with simple and inexpensive modernisation, without compromising the main function of the window—efficient transmission of visible light—and create an additional (backup) heating device that can work effectively together with the existing heating system in the event of a sudden cold snap at low temperatures (below −20 °C), to prevent condensation of water vapour in the windows, and to prevent condensation on the surface of the window facade wall. Formally, a back-up (emergency) heating system is created in the room, which contributes to the energy sustainability of the building and therefore to energy security in general.

Wooden construction constitutes a specific branch of the building industry that focuses on high-quality materials, a developed sense of aesthetics connected with comfort and functionality, and concern for ecology and durability. This type of construction has a positive effect on human quality of life. This article focuses on modular frame construction and technological aspects of wooden houses built according to Canadian or Scandinavian technologies. Taking weather conditions of Scandinavian countries into consideration, timber is a popular building material, which, when preserving certain parameters such as density of rings, may provide durability of a modular wooden building even up to 200–300 years. This article is a review and presents the possibility of producing frame buildings in Europe (Poland) in accordance with the applicable standards, including a heat transfer coefficient U = 2 [W/(m²·K]. In Poland, wooden frame buildings can be traced back to the 14th century. Wooden frame buildings and modular wooden frame buildings were produced even earlier in Norway. Wooden construction continued in the mid-1800s in various forms (with wooden filling and/or panels). In the mid-1900s (1941), certain dimensioning became regulated by law, which then applied to different types of insulation fillings. Prefabricated modular wood frame houses were common in the 1960s.

The indoor environment of buildings significantly affects the well-being and health of room users. Experiencing thermal discomfort reduces concentration and productivity during study or work, causing drowsiness, fatigue or deterioration in general well-being. The study focuses on presenting the results of the questionnaire study on the symptoms of sick building syndromes (SBS), namely: dizziness, nausea, eye pain and nasal mucosa, experienced by 69 students during a lecture in a large and modern auditorium of Kielce University of Technology. The results show that many students experienced SBS symptoms, which seem to have affected their concentration during the class. The article also discusses the thermal sensations of the students with a focus on comparing the obtained results with the Fanger model of thermal comfort. The discrepancy between the model calculation results and the experimental data has been observed and discussed.