Rongling Li

Are building users prepared for energy flexible buildings—A large-scale survey in the Netherlands

Building energy flexibility might play a crucial role in demand side management for integrating intermittent renewables into smart grids. The potential of building energy flexibility depends not only on the physical characteristics of a building but also on occupant behaviour in the building. Building users will have to adopt smart technologies and to change their daily energy use behaviours or routines, if energy flexibility is to be achieved. The willingness of users to make changes will determine how much demand flexibility can be achieved in buildings and whether energy flexible buildings can be realized. This will have a considerable impact on the transition to smart grids. This study is thus to assess the perception of smart grids and energy flexible buildings by building users, and their readiness for them on a large scale. We attempted to identify the key characteristics of the ideal user of flexible buildings. A questionnaire was designed and administered as an online survey in the Netherlands. The questionnaire consisted of questions about the sociodemographic characteristics of the current users, house type, household composition, current energy use behaviour, willingness to use smart technologies, and willingness to change energy use behaviour. The survey was completed by 835 respondents, of which 785 (94%) were considered to have provided a genuine response. Our analysis showed that the concept of smart grids is an unfamiliar one, as more than 60% of the respondents had never heard of smart grids. However, unfamiliarity with smart grids increased with age, and half of the respondents aged 20–29years old were aware of the concept. Monetary incentives were identified as the biggest motivating factor for adoption of smart grid technologies. It was also found that people would be most in favour of acquiring smart dishwashers (65% of the respondents) and refrigerator/freezers (60%). Statistical analysis shows that people who are willing to use smart technologies are also willing to change their behaviour, and can thus be categorised as potentially flexible building users. Given certain assumptions, 11% of the respondents were found to be potentially flexible building users. To encourage people to be prepared for energy flexible buildings, awareness of smart grids will have to be increased, and the adoption of smart technologies may have to be promoted by providing incentives such as financial rewards.

Modelling hand skin temperature in relation to body composition

Skin temperature is a challenging parameter to predict due to the complex interaction of physical and physiological variations. Previous studies concerning the correlation of regional physiological characteristics and body composition showed that obese people have higher hand skin temperature compared to the normal weight people. To predict hand skin temperature in a different environment, a two-node hand thermophysiological model was developed and validated with published experimental data. In addition, a sensitivity analysis was performed which showed that the variations in skin blood flow and blood temperature are most influential on hand skin temperature. The hand model was applied to simulate the hand skin temperature of the obese and normal weight subgroup in different ambient conditions. Higher skin blood flow and blood temperature were used in the simulation of obese people. The results showed a good agreement with experimental data from the literature, with the maximum difference of 0.31°C. If the difference between blood flow and blood temperature of obese and normal weight people was not taken into account, the hand skin temperature of obese people was predicted with an average deviation of 1.42°C. In conclusion, when modelling hand skin temperatures, it should be considered that regional skin temperature distribution differs in obese and normal weight people.

User interaction patterns of a personal cooling system: A measurement study

Personal cooling systems provide cooling for individual office occupants to maintain thermal comfort at their workplace when cooling is needed. The indoor temperature of the office can be maintained at several degrees higher than is customary in offices today when personal cooling is available, which results in energy saving for office buildings as a whole. To better understand the individual cooling demand of building occupants and develop good control strategies for personal cooling systems, it is necessary to assess the interaction between the user and the personal cooling system. For this purpose, a personal cooling system was tested in a stable, slightly warm environment (27.5°C) in a climate chamber with 11 human subjects. The personal cooling system was controlled by the subject using a simple slider. The interaction of the user with the system was related to comfort level and perceived air quality. The subjects are categorized into groups based on gender, on comfort level, and on whether their comfort improved during the test or not. The results show that comfort level did not directly reflect in a difference in the number of interactions or level of the setting. The largest difference in setting was found between male and female subjects, where females required less cooling.

Optimal scheduling for electric heat booster under day-ahead electricity and heat pricing

Multi-energy system (MES) operation calls for active management of flexible resources across energy sectors to improve efficiency and meet challenging environmental targets. Electric heat booster, a solution for Domestic Hot Water (DHW) preparation under Low-Temperature-District-Heating (LTDH) context, is identified as one of aforementioned flexible resources for electricity and heat sectors. This paper extends the concept of optimal load scheduling under day-ahead pricing from electricity sector only to both electricity and heat sectors. A case study constructing day-ahead energy prices to shift energy consumption to low carbon content energy is provided. Results show that 0.5 DKK/kWhel add-ons on top of electricity spot price makes electricity and heat price not comparable such that electricity price variation will have no impact on load scheduling. This result suggests aforementioned concept is not feasible with current Danish electricity taxation.

Multi-variable Optimization of HVAC System Using a Genetic Algorithm

Geothermal is a fast-growing alternative heat source for HVAC systems due to higher energy efficiency than conventional heating and cooling systems. However, the initial cost of using a ground source HVAC system is higher compared to an air source system. Studies about system design and operation are necessary to reduce the initial cost and ensure that the ground source heat pump system has high efficiency, resulting in a lower total life-time cost. In this study, a multi-variable evolutionary computation algorithm is proposed for generating optimal parameters for a geothermal source HVAC system. The system consists of borehole heat exchangers (BHE), a water-to-water heat pump and a fan coil unit (FCU) and it was modeled and simulated using MATLAB. The design parameters were calculated by minimizing the energy consumption. These parameters include cold water supply temperature, FCU air flow rate and cooling water flow rate for the underground heat exchangers. In addition, based on an experimental building, a case study was presented. Using this model, the optimal set points were calculated and used as a designed system. Energy consumption of this system was reduced by about 10% compared to the system operated with a fixed supply cold water temperature (7°C). Furthermore, the relationship between system energy consumption and heat pump capacity was expressed. The result showed that the energy consumption increased due to decrease in PLR when the capacity is increased.