The building sector is responsible for approximately 40 % of the total energy usage in Sweden. In office buildings the heating, ventilation and air conditioning system can account for up to 55 % of the energy usage. In order to reduce the energy usage of the heating, ventilation and air conditioning system different control methods are often used. One of these control methods is demand controlled ventilation, where the ventilation system is controlled with regard to occupancy with the help of motion and/or CO2 sensors. The aim of this thesis was to determine the energy savings potential of a heat recovery unit as well as demand controlled ventilation in an office building. The effect of longer intervals between sensor control signals to the ventilation system was also investigated. This is done by creating schedules, gathered from actual building occupancy, that are being used to control the occupancy and ventilation in a building model in the building performance simulation software IDA ICE. As a reference building, the fifth floor of the LU1 section of the natural science building at Umeå University is used. The reference building consists of 40 offices for which the occupancies are known. The average occupancy for all the offices combined throughout the investigated time period is determined to be 34.8 %. The results from the simulations indicate that an energy savings potential of 52.98 % can be achieved by a heat recovery unit with an efficiency of 80 % or 95 %, when compared to not having a heat recovery unit. When implementing demand controlled ventilation an energy savings potential of 2.8-11.0 % can be achieved, with the energy savings potential decreasing when the efficiency of the heat recovery unit increases. Finally, it is shown that longer intervals between sensor control signals to the ventilation system leads to a small increase in energy usage and poorer indoor air quality.

Indiana University-Purdue University Indianapolis (IUPUI) / Heat, cooling, and ventilation units are major energy consumers for commercial buildings, they can consume as much as 50% of the total annual power usage of a building. Coherent management of an air handling system’s energy is a key factor of reducing the energy costs and CO2 emissions that are associated with the demand for ventilating and conditioning the air in a building. The issue is that buildings are frequently over ventilated as a full assessment of the air handling unit (AHU) data is not evaluated by building operators. According to ASHRAE standards there are three key parameters that control indoor air quality (IAQ); these are the temperature, humidity, and CO2. Commonly occupancy setpoints implemented by building operators are focused on temperature and humidity control while neglecting the CO2 levels and their impact. While this may seem insignificant additional data proves to be important and can assist with energy management. Additionally, it can develop awareness of implementable procedures which conserve energy. Furthermore, data is not monitored in regard to the continuous assessment of the energy consumption with respect to analysis of opportunities to implement energy saving control strategies. By using these standards as a guide an AHUs energy can be managed more effectively by measuring the data and assessing the outputs compared to the standard. Previous research has shown that up to 75% savings for the ventilation fan energy is achievable when taking into account ASHRAE ventilation standards and controlling outside air ventilation, however, this research has omitted investigating the savings for other energy consumers associated with AHU’s operation. In order to assess the demand, it is required that the CO2 levels of the occupied zones be measured, and the outdoor air ventilation rate be adjusted based on real-time demand. The goal of the research is to assess the number of CO¬2 sensors needed to accurately measure demand-based needs for ventilation and determine an algorithm that will help building operators assess the energy savings by implementing demand-controlled ventilation (DCV) procedures. The scope of this research is to identify what sensors at minimum are required to collect the most pertinent data for implementation of a comprehensive energy saving algorithms and assess the impact on energy consumption of AHUs when demand-controlled ventilation procedures are implemented.

In the development of society towards renewable energy sources, the target in Sweden is 100% energy supply from renewable energy sources by the year 2040. This requires increased energy production from renewable, but also energy optimization of existing buildings. The housing and service sector which includes households and the public services account for about 40 % of Sweden’s total energy use. It is estimated that preschools and schools have an area of 35 million m² which have an energy savings potentials of 0,7-1 TWh in the electricity consumption and 0,9 TWh in energy use for heating. With regard to energy optimization, it is not only interesting to investigate a buildings total energy use on an annual or monthly basis, but also on shorter time intervals such hourly energy use, because of the uneven energy production of some renewable energy sources such as solar and wind. The purpose of this work is to study the energy usage for some of Västerås preschools and schools, and on the basis of it propose some energy optimization actions. To achieve this a literature study has been carried out to get knowledge about how energy usage is at preschools and schools, as well as to gain insight into what actions are appropriate to perform and how they savings look like. Other than that four objects has been studied, two preschools and two schools, one of each kind were chosen amongst those with the highest energy usage among Västerås city’s preschools and schools and one of each kind amongst those with the lowest usage. The annual energy usage have been calculated and been compared to the actual usage, and the monthly and hourly energy usage for district heating have been studied as well as the electricity usage along the day for different periods. The studied periods and energy usage shows that the energy usage, both for the monthly and hourly,  for the district heating moves with regards to the outdoor temperature with some exceptions. As for the electricity usage it shows that the energy usage is even with some exceptions and there is a difference between different outdoor temperature intervals. Some conclusions could be drawn among others that the objects with higher energy usage where older buildings and the objects with lower energy usage where newer ones. There are some energy optimizations actions for the objects which would lower the energy consumption, both for district heating and electricity usage.

The importance of energy efficiency in the operation of the built environment is becoming increasingly important. Energy use in the building sector has exceeded both transportation and industry, while within buildings heating, ventilation, and air conditioning has the greatest share. In light of the recent pandemic forcing governments to issue quarantines and stay-at-home orders people are spending even more time indoors, this further emphasizes the importance of proper ventilation and the impacts on energy use. The purpose of this research was to perform a case study of a low environmental impact demonstration house to compare the energy performance of various ventilation strategies. The ventilation strategies varied by overall airflow rate, control strategy, and the presence of heat recovery. Performance was evaluated by establishing a model in IDA ICE, an equation-based modeling tool for the simulation of indoor thermal climate and energy use. The results showed energy savings due to demand-control with a reduction of 12.5%. Results also showed similar savings with a heat recovery system, indicating that any savings in heat loss due to heat recovery is at the expense of increased auxiliary energy. In this particular case, the benefit of upgrading to a heat recovery system from simple demand control set up is not readily apparent. Results also demonstrated trends and possible complications useful to future research plans that aim to measure real world ventilation performance, including how differences in the number and location of sensors impact the efficacy of the demand-controlled systems. A secondary aim was to observe how a newly constructed, low environmental impact home built in Sweden performs according the residential LEED energy budget. The results demonstrated that constructing a house using low impact materials with low embodied energy does not have to negatively impact energy performance, scoring extremely well in the Energy and Atmosphere category of a widely used sustainable building rating system.

The motivation of this project is found on the past trend of growing greenhouse gases emissions and, also growing, energy use over the world that still remains. This trend overlaps with a more recent increase in the awareness regarding the effects of human activities towards the Earth ecosystems. Thus, the upgrade of the already-in-use systems is necessary to move towards greener and more modern technologies that permit continue with the economic growth while building more sustainable societies. Thereby, the research focuses on the improvement of the ventilation system of a warehouse building and a cooking school located in the same plot, in an industrial area in Gävle, Sweden. The current system conditions, even consisting in some cases in recirculating air handling units, doesn’t permit the utilisation of the waste heat by bringing it back to the system. The strategy used during the project follows a case study scheme: looking the system, understanding it in a complete way and designing the proper solution that fulfils the requirements. The study was approached as an energy audit: with several meetings with the company, collecting airflows data with the thermo-anemometer device, sketching the required building drawings and designing the optimal solution for the company. Finally, the project resulted in the selection of the proper air handling unit, equipped with a heat recovery system, and the design of its ventilation duct system that permit a heat energy savings derived of the heat demand used to heat the makeup air of about 67 %. Furthermore, the occupancy study helped design the new scheduling for the ventilation periods that reduce the electricity demand of the ventilation system by 30 %. Thus, was obtained a significant energy use reduction that results in a sizeable energy cost saving.

The aim of this project was to develop a holistic approach to building-performance assessment without limiting it to energy use (usually expressed in kWh/m2/year), but rather include more parameters that represent the following aspects: Economic, environmental, and quality of service provided to the occupant/client. If it can be shown that buildings can be operated not only in an energy-efficient way, but also in a way that takes into consideration the needs of the occupants, a case could be built that a higher quality of indoor environment does not necessarily mean a higher economic impact. It is also important to show that having access to high-quality building-performance data leads to high-quality analysis and visualisation, and consequently to a chance to detect faults and improve building operation. To answer these questions, a large office building in Stockholm, Sweden was used as a case study. The building was equipped with energy meters and 1,700 sensor points, uniformly distributed over the occupied areas, that measured room temperature, duct temperature, occupancy presence/absence and supply airflow, in addition to other states. The data was processed using RStudio, and various types of visualisation plots were used, including carpet plots, masked scatter plots, bar plots, line graphs, and boxplots. The data pointed to some interesting results. First, just knowing the energy use is not sufficient for understanding the quality of the service provided to the occupants. Second, performing a thorough analysis of room unit data can detect faults. Third, using carpet plots for energy-data visualisation is effective for energy-use pattern recognition. Finally, visualising the building performance parameters in a parallel coordinate plot is a more informative representation of integrated building performance compared to the energy performance certificates typically used today. / <p>QC 20160916</p>

It is a dilemma problem to achieve both these two goals: a) to maintain a best indoor air quality and b) to use a most efficient energy for a house at the same time. One of the outstanding components involving these goals is a smart ventilation system in the house. Smart ventilation strategies, including demand-controlled ventilation (DCV), have been of great interests and some studies believe that DCV strategies have the potential for energy reductions for all ventilation systems. This research aims to improve smart ventilation system, in aspects of energy consumption, indoor CO2 concentrations and living comfortness, by analyzing long-term sensor data. Based on a case study on an experimental house -- Dalarnas Villa, this research investigates how the current two ventilations modes work in the house and improves its ventilation system by developing customized ventilation schedules. A variety of data analysis methods were used in this research. Clustering analysis is used to identify the CO2 patterns and hence determine the residents living patterns; correlation analysis and regression analysis are used to quantify a model to estimate fan energy consumption; a mathematical model is built to simulation the CO2 decreasing when the house is under 0 occupancy. And finally, two customized schedules are created for a typical workday and holiday, respectively, which show advantages in all aspects of energy consumption, CO2 concentrations and living comfortness, compared with the current ventilation modes.