Space Heating In Residential Buildings Research Articles

Analysis of the impact of demand response on the Norwegian energy system

AbstractEuropean CO2 reduction goals have led to an increase in variable energy sources such as wind and solar, and consequently to an energy system that will need more flexibility in the future. In Norway, the hydropower reservoirs will enable the country to play a crucial role in European electrification by delivering flexibility to countries in Northern Europe. A further source of flexibility is demand response (DR) accumulated in residential, commercial, and industrial sectors. The paper discusses DR, load shifting, and load shedding based on the application of a stochastic TIMES model and it evaluates the role of DR in the Norwegian energy system towards 2050. The analysis shows that cost-efficient DR operation primarily comes from space heating in residential buildings. The use of DR, which is season-dependent, increases the volume of electricity trade, including electricity export and import to neighboring countries, and it smooths electricity prices. The implementation of DR in Norway leads to decreases in expected electricity price and total system cost by exporting flexible electricity and importing low price electricity. Additionally, it affects hydropower and reservoir management.

Values of coordinated residential space heating in demand response provision

Demand side response from space heating in residential buildings can potentially provide huge amount of flexibility for the power system, particularly with deep electrification of the heat sector. In this context, this paper presents a novel distributed control strategy to coordinate space heating across numerous residential households with diversified thermal parameters. By employing an iterative algorithm under the game-theoretical framework, each household adjusts its own heating schedule through demand shift and thermal comfort compensation with the purpose of achieving individual cost savings, whereas the aggregate peak demand is effectively shaved on the system level. Additionally, an innovative thermal comfort model which considers both the temporal and spatial differences in customized thermal comfort requirement is proposed. Through a series of case studies, it is demonstrated that the proposed space heating coordination strategy can facilitate effective energy arbitrage for individual buildings, driving 13.96% reduction in system operational cost and 28.22% peak shaving. Moreover, the superiority of the proposed approach in thermal comfort maintenance is numerically analysed based on the proposed thermal comfort quantification model.

Exploring the challenges of residential space heating electrification in China: A case study in Jinan and Qingdao

De-carbonization actions, represented by the electrification of end-use energy sources, have been strongly promoted, while space heating in residential buildings is an important aspect. In this paper, Jinan and Qingdao in northern China are selected to explore the challenges that electrification of heating will bring. The electricity demand for heating of different types of buildings is simulated, with the assumption that all heating loads are provided by electric heat pumps. Then the comparison of heating electricity demand with current electricity consumption in various social sectors has been analyzed to investigate the impact of the newly added electrical load on the power grid. The annual dynamic power supply under the currently installed wind turbines and photovoltaic modules is calculated to explore the interrelationship between the power supply potential of the available renewable energy and the heating electricity demand. The results show that the implementation of heating electrification will bring a strong impact on the existing grid, with photovoltaic generation almost negligible during the heating period and wind generation severely affected by intermittency. In the future, the deployment of installed renewable energy needs to continue to be promoted, while the layout of energy storage facilities needs to be strengthened.

Effect of input parameters on energy requirements of phase change material integrated local heating system

The space heating in residential buildings in winter accounts for a considerable amount of conventional energy. Therefore, improving the performance of space heating systems with the inclusion of renewable energy sources like solar becomes crucial in order to have better occupant’s comfort while reducing energy use. Phase change material (PCM) is one of the best solutions for renewable energy, especially solar, which is intermittently available. PCM stores energy when surplus energy is available and delivers whenever it is required. It is integrated with the current system for energy storage as well as availing heat at a constant temperature. The present study will try to demonstrate the energy-saving by implementing the local heating with a spiral latent heat thermal energy storage system, when only a particular (local) space heating is of interest. In this work, an experimental as well as the numerical study of a dome over a bed was performed. Various heating coil configurations, namely floor coil, roof zig-zag, and roof spiral, were constructed to find the best configuration for the localized space heating. Experiments and simulations with the variable flow rate (0.25, 0.50, and 0.75 m/s) and varying inlet temperatures (55, 60, and 65°C) of the heat transfer fluid were carried out. It was found that the floor coil heating gives better results as compared with the other two. It was also seen that the effect of mass flow rate and inlet temperature was not that much significant after a limit. A temperature difference of 20°C was maintained between the space under consideration with the surrounding room.

Linking energy efficiency indicators with policy evaluation – A combined top-down and bottom-up analysis of space heating consumption in residential buildings

This paper studies the factors underlying the evolution of the energy consumption for space heating in residential buildings by linking top-down analysis, based on meso-indicators, and bottom-up analysis, based on policy evaluations. The top-down analysis (i.e. the perspective from energy statistics) allows one to separate the change in total energy use into activity level, societal factors and energy efficiency gains. The explanatory power of the resulting meso-(statistical) indicators is often limited, if the underlying factors are not examined (e.g. changes in heating levels and patterns, weather effects, cost of energy and policies regarding insulation and heating system standards). We overcome most of these drawbacks by conducting a bottom-up analysis (i.e the perspective from single policy measures), which enables us to discern the contribution of energy efficiency policies to the changes observed with the meso-analysis. We focus on space heating consumption in the residential sectors for Germany and Switzerland. A major aim of this analysis is to show the contribution of energy efficiency policies (such as thermal building regulation, subsidy programmes, fiscal measures etc.) towards the changes in this indicator. The results show that the progress in energy efficiency (both autonomous and policy induced) in both countries had the greatest effect (-776 PJ for Germany, −42 PJ for Switzerland) regarding the change in energy consumption for space heating in the period from 2000 to 2016. However, the impacts of “technical and comfort” rebounds (+436 PJ for Germany, N/A for Switzerland) and other developments such as societal changes (+316 PJ for Germany, +35.5 PJ for Switzerland) were found to compensate for a significant part of the energy efficiency gains. In both countries, it was possible to link physical energy efficiency indicators to policy evaluation, but limitations were also identified which are primarily related to data gaps.

Applicability and comparison of solar-air source heat pump systems between cold and warm regions of plateau by transient simulation and experiment

Solar-air source heat pump (solar-ASHP) system has a potential application in the field of hot water and space heating in residential buildings. Such system features the complementary advantages to solve the discontinuous operation of the single solar system and the frosting issue of the single ASHP system. This paper built the solar-ASHP systems in Kunming and Shangri-La, and tested the system performance under different weather conditions in these two regions of plateau. Meanwhile, the transient heat balance models of the system were established under the sunlight time and non-sunlight time and were verified by the experimental results. Moreover, the verified model was applied to reveal the energy balance performance between the energy supply and building heat demand. The law of the system performance affected by the ambient temperature, effective heat collecting area, and cumulative heating capacity of collector was explored by the validated model. The results indicate that when the ambient temperature decreases by 1 °C during non-sunlight time, the energy efficiency ratio decreases by about 0.07. A square meter decline in the effective heat collecting area pushes an increase in the heating capacity of 5.75 MJ. Meanwhile, the cumulative heating capacity of collector increases by 5 MJ, and the ASHP energy consumption decreases by 0.54 kWh. The dynamic changes of the ambient temperature and instantaneous solar radiation are the main reasons of the heat balance errors. Therefore, both the developed system and model are feasible and reliable in different climate regions.

Solar seasonal thermal energy storage for space heating in residential buildings: Optimization and comparison with an air-source heat pump

ABSTRACT This study evaluates the techno-economics of replacing an air-source heat pump (ASHP) system with a solar seasonal thermal energy storage (STES) system for space heating in Hangzhou, China. Three heating systems, solar STES, ASHP, and ASHP with short-term storage of solar energy, are developed using TRNSYS for a house with 240 m2 of floor area. The ratio of tank volume to collector area (RVA) of the STES is optimized for the lowest equivalent annual cost over a lifespan of 20 y. The determined optimal RVA is 0.33 m3/m2, although it depends on the system and electricity prices. The optimized STES reduces the electricity demand to 1,269 kWh (74% reduction). Despite the superior energy performance, the economic benefit is only possible with large STES systems, which enjoy low tank prices due to scale effects. The results suggest that policy support is needed for STES, where district scaling is not an option.

Thermal adaptations and logistic regression analysis of thermal comfort in severe cold area based on two case studies

In recent years, the indoor air temperature in residential buildings for space heating rose gradually in the severe cold area of China. Would people feel comfortable in a warmer environment? This paper focuses on the appropriate indoor air temperature in winter.Two field investigations were conducted on the indoor thermal environment and human adaptation in residential buildings with district heating in Harbin during two winter seasons from 2011 to 2014. Ten apartments and their residents were chosen as samples in each investigation. The investigations included measurements of physical environmental parameters as well as subjective questionnaires. The results show that when the indoor air temperature was higher than 24 °C, people would have a sensitive response and preferred a lower temperature.An ordinal logistic regression model was used to examine the result of the linear regression model. The neutral temperature derived from the logistic model is 0.5 °C higher than that from the linear model and the adjusted neutral temperature is 0.8 °C higher than the linear model. Detecting whether people felt “cool” or not and “warm” or not is relatively accurate with the logistic model. It is not sensitive to judge whether people felt “neutral” in low air temperatures.Thermal neutral temperature is not a suitable set-point of indoor air temperature. In the severe cold area of China, the indoor air temperature of 20 °C is suggested as the standard for space heating in residential buildings in terms of comfort and energy saving.

Measured and modeled performance of internal mass as a thermal energy battery for energy flexible residential buildings

To increase the penetration of photovoltaic renewable energy (PV RE) in the residential building sector energy mix, the mismatch between mid-day production and evening electrical energy demand must be bridged. The use of heat pumps for space heating of residential buildings creates an opportunity for energy flexible residential buildings that rely on low-cost thermal energy storage systems. This paper explores the ‘building as battery’ concept (BaB), i.e. the use of the structural thermal capacity as a heat storage medium in winter. In these systems the building internal mass is preheated during solar daytime hours (using a PV RE powered heat pump) and cooled by discharge into the room air after sunset, for space heating. This study presents measured and simulated performance of BaB systems used for thermal energy storage in living rooms of three different apartment buildings with variable thermal insulation levels, ranging from typical southern Europe 1980s construction to a insulated apartment (Passive House certified). To assist in interpreting the results and facilitate their integration in simplified simulation of BaB systems in smart grids the model parameters of a simplified Resistance-Capacitance model were found by fitting the experimental results. The results show that, for apartments with high thermal mass, thermal insulation is the key driver of BaB system thermal efficiency, with the highly insulated apartment reaching BaB efficiencies of 60–80%. For existing apartments with a low thermal insulation, the BaB approach is only effective when space heating is required right after sunset (just when PV RE powered heat pump charging finishes).

Towards practical model predictive control of residential space heating: Eliminating the need for weather measurements

Model-based control schemes such as model predictive control (MPC) can assist smart-energy systems in achieving higher efficiency and utilization of renewable energy sources. A practical barrier for deploying such control schemes for space heating of residential buildings is the costs related to obtaining the weather data measurements needed for identifying a model that describes the dynamic behaviour of the building. Therefore, this paper reports on a simulation-based study investigating whether there is a significant impact on the performance of MPC schemes when substituting these weather measurements with data from meteorological weather services. Since access to weather forecasts is necessary during the operation of the MPC scheme, this implementation approach draws on data already available to remove the need for weather measurements. The results indicated that this approach only led to a minor performance impact in that heating savings were reduced by 4% while comfort violations increased by less than 0.1 Kh per day on average. The results thereby suggest that the use of data from meteorological forecast services for model identification may constitute a cost-efficient alternative to on-site or near-by weather measurements.

Investigating the performance of scenario-based model predictive control of space heating in residential buildings

This paper investigates the performance of scenario-based model predictive control (SB-MPC) for space heating operation to address the inherent uncertainty of weather forecasts and predictions of occupancy. In contrast to existing reported studies, this study relied on a sophisticated meteorological model and a higher order Markov chain occupancy model to generate stochastic disturbance scenarios. When applying the SB-MPC scheme for energy-efficient operation, simulation results suggested a slight increase in energy consumption (from approx. 27.7 kWh/m2 to 28.0 kWh/m2) when using one and 100 disturbance scenarios, respectively, while thermal comfort violations were reduced significantly (from 60°Ch to 10°Ch). Furthermore, the SB-MPC scheme was tailored to provide demand response and thereby achieved cost savings of 16.1% and 13.1% compared to conventional proportional-integral control when considering one and 100 disturbance scenarios, respectively. Choosing the appropriate number of disturbance scenarios thus relies on a consideration of the trade-off between the acceptable thermal comfort violations and energy-related benefits.

Techno-economic analysis of air source heat pump applied for space heating in northern China

To meet the demand of clean heating in cold regions of northern China, high efficiency and environment-friendly low temperature air source heat pump heating system has been proposed and applied. In this paper, the technical feasibility and economical applicability of low temperature air source heat pump heating mode were studied and compared with conventional heating systems. A mathematical model of technical and economic analysis of different heating modes was established. With the mathematical model, different heating systems were compared with their primary energy consumption, pollution emissions, initial investment and annual running cost. The results showed that the low temperature air source heat pump heating system can stably and reliably meet the demand of space heating in residential buildings when outdoor air temperature is −15°C. In terms of energy efficiency, the primary energy consumption of low temperature air source heat pump heating mode is lower than coal-fired boiler, gas boiler, direct electric heating mode, but higher than combined heat and power generation. Comparing the pollution emissions, low temperature air source heat pump heating mode move the pollution source from residential areas to power plant, and has the relative low dioxide pollution emissions. Comparison results also show that the low temperature air source heat pump heating system is the most economical way among the candidates.

Multi-market demand response using economic model predictive control of space heating in residential buildings

Several studies have evaluated the potential for residential buildings participating in demand response programs based on the day-ahead electricity market prices. However, little is known about the benefits of residential buildings providing demand response by engaging in trading on the intraday market. This paper presents a simulation-based study of the performance of an economic model predictive control scheme used to enable demand response through parallel utilization of day-ahead market prices and intraday market trading. The performance of the control scheme was evaluated by simulating ten apartments in a residential building located in Denmark through a heating season (four months) using historical market data. The results showed that the addition of intraday trading to the more conventional day-ahead market price-based control problem increased the total cost savings from 2.9% to 5.6% in the existing buildings, and 13%–19% in retrofitted buildings with higher energy-efficiency. In the existing building the proposed control scheme traded on average 12.7kWh/m2 on the intraday market throughout the simulation corresponding to 21% of the reference consumption. For a retrofitted building the traded volume was 9.6kWh/m2 which corresponds to 52% of the reference consumption. These results suggest that the benefits of considering intraday market trading as a demand response incentive mechanism apply to a wide range of buildings.

Data mining of space heating system performance in affordable housing

The space heating in residential buildings accounts for a considerable amount of the primary energy use. Therefore, understanding the operation and performance of space heating systems becomes crucial in improving occupant comfort while reducing energy use. This study investigated the behavior of occupants adjusting their thermostat settings and heating system operations in a 62-unit affordable housing complex in Revere, Massachusetts, USA. The data mining methods, including clustering approach and decision trees, were used to ascertain occupant behavior patterns. Data tabulating ON/OFF space heating states was assessed, to provide a better understanding of the intermittent operation of space heating systems in terms of system cycling frequency and the duration of each operation. The decision tree was used to verify the link between room temperature settings, house and heating system characteristics and the heating energy use. The results suggest that the majority of apartments show fairly constant room temperature profiles with limited variations during a day or between weekday and weekend. Data clustering results revealed six typical patterns of room temperature profiles during the heating season. Space heating systems cycled more frequently than anticipated due to a tight range of room thermostat settings and potentially oversized heating capacities. The results from this study affirm data mining techniques are an effective method to analyze large datasets and extract hidden patterns to inform design and improve operations.

Improving the residential natural gas consumption forecasting models by using solar radiation

Natural gas is known as a clean energy source used for space heating in residential buildings. Residential sector is a major natural gas consumer that usually demands significant amount of total natural gas supplied in distribution systems. Since demands of all consumers should be satisfied and distribution systems have limited capacity, accurate planning and forecasting in high seasons has become critical and important. In this paper, the influence of solar radiation on forecasting residential natural gas consumption was investigated. Solar radiation impact was tested on two data sets, namely on natural gas consumption data of a model house, and on natural gas consumption data of a local distribution company. Various forecasting models with one day ahead forecasting horizon were compared in this study, including linear models (auto-regressive model with exogenous inputs, stepwise regression) and nonlinear models (neural networks, support vector regression). Results confirmed that solar radiation clearly influences natural gas consumption, and included as input variable in the forecasting model improves the forecasting results. Consequently it is recommended to use solar radiation as input variable in building forecasting models.

Thermal responses to different residential environments in Harbin

In China, adding space heating in residential buildings is normally scheduled at the end of October each year, with heat supplied by district heating systems. This paper describes a field study of thermal comfort conducted in Harbin during the winter from 2009 to 2010 before and after the space heating is added. The aim is to study human responses to thermal conditions in the two periods in cold climates. 23 buildings in six communities were investigated. 199 occupants from 135 families and 174 occupants from 104 families participated in the two surveys during the two periods, respectively. The neutral air temperature before adding the space heating is 25.1 °C, while during the space heating, it is 20.4 °C. The clothing insulation is 0.77 clo and 0.88 clo, respectively. If they were 0.88 clo instead of 0.77 clo before adding the space heating, the neutral air temperature should be 21.1 °C. Before and during space heating, more than 80% felt acceptable at the air temperature range between 17.5–24.0 °C and 19.0–26.5 °C for the two periods. The residents’ physiological acclimation may contribute to the differences. The preferred temperature is within the range of 23.0–24.0 °C and 21.5–24.0 °C, respectively. The preferred humidity is 47.7% and 40.5% during the two surveys. People felt cold generally before heating, while they felt comfortable at the same temperature range during space heating period. People often felt dry during heating when the relative humidity is lower than 30%, while they felt comfortable at the same relative humidity before heating.

Energy demand for space heating through a statistical approach: application to residential buildings

This study deals with the statistical analysis of a data set of residential buildings to find simplified correlations for the assessment of the energy demand for space heating. The analyzed data come from a sample of 50 multi-family residential buildings of the local social housing company, built in different periods between the end of the 19th century and the end of the last century. Relationships are searched between the age of the building and its main geometric and thermo-physical properties: the shape ratio, the volume, the opaque and glazed surfaces, their transmittances, the external and internal temperatures. These properties are suitably combined to find out statistical relations. Moreover, starting from standard deterministic equations, this study revises them and simplifies the most involved terms. This simplification is carried out making a statistical analysis of the energy quantities that affect the performance of a building. In such a way the solution of the energy balance is simplified, making the calculation easier and faster. Results are compared with those calculated using the rigorous Standard procedure, showing a good agreement. Moreover, the assessed energy demand is compared with the actual metered energy consumption. The present statistical model estimates in a simple and prompt way the energy demand for space heating of residential buildings, in particular the existing ones. It may represent a useful tool for their energy certification.

98/01553 Active solar space heating of residential buildings in northern Hellas—a case study: Argiriou, A. et al. Energy and Buildings, 1997, 26, (2), 215–221

98/01553 Active solar space heating of residential buildings in northern Hellas—a case study: Argiriou, A. et al. Energy and Buildings, 1997, 26, (2), 215–221

Active solar space heating of residential buildings in northern Hellas—a case study

The final energy consumption in Hellenic residential and tertiary sector buildings represents almost one-third of the total energy budget. From this, space and water heating represents 70% of the total. Space heating and electricity generation in Hellas are based on fossil fuels, with a serious environmental impact. Despite the popularity of simple solar domestic hot water systems, active solar space heating remains, for various reasons, marginal. The aim of this paper is to demonstrate the potential of combined active space and domestic hot water solar systems, both technically and economically. An assessment of the reduction of the environmental impact is also included. The results confirm that modern solar technology constitutes a viable option for energy retrofit in the building sector in Hellas.