Heating Sector Research Articles

Does energy poverty influence decarbonisation through electrification of the heating Sector?

Cleaner end-uses of energy, including electrified heating, represent a cornerstone of a decarbonised energy transition. On the other hand, many governments have adopted measures to mitigate energy poverty and facilitate access to modern energy services, including heating. Both objectives may be interrelated, since energy poor people are less likely to use cleaner (and costlier) heating fuels. This paper analyses the impact of energy poverty on the decision to use different heating sources and identifies whether the events of COVID and the Ukraine war have affected this decision. Thus, a multinomial probit model is estimated using information from a large database of Spanish households in 2019, 2021 and 2022. The results show that being energy poor increases the probability to use carbon-intensive energy sources for heating compared to electricity, and that COVID and the war in Ukraine have affected this relationship. The increase in energy poverty over those years has negatively affected the decarbonisation goal with respect to heating choices. The influence of those events on the probability to use electric heating depends on some household and dwelling features. Therefore, mitigating energy poverty increases the welfare of energy poor people while supporting the choice of cleaner heating.

Multi-tier life cycle assessment for evaluating low carbon strategies in soil remediation

Addressing soil pollution and achieving global carbon neutrality requires low carbon remediation practices. When selecting the optimal remediation techniques, a comprehensive model is required to assess the environmental and economic impacts accurately. In the present study, a spatial three-tier framework that combines process cycle assessment (PLCA), Input output analysis (IOA) and Multi-Regional Input Output analysis (MRIOA) has been used to evaluate the greenhouse gas (GHG) emissions of three commonly used remediation alternatives at a contaminated site in Hubei Province, China, as well as the indirect GHG emissions of the industry chain at provincial and national scale. The three remediation techniques were coprocessing in a cement kiln (CCK), ex-situ solidification and stabilization (ESS), and soil washing (SLW). Using a tiered hybrid life cycle assessment (THLCA) approach, the results demonstrated the importance of including off-site emissions in life cycle assessments. It was found that CCK had the lowest total GHG emissions among the three alternatives. Off-site greenhouse gas (GHG) emissions associated with three soil remediation alternatives vary significantly, with CCK exhibiting the lowest levels and ESS the highest. Soil remediation emissions mainly affected Hubei Province, with varying spillover effects on other regions, such as Inner Mongolia, Shanxi, Liaoning, and Gansu, which supplied material resources and power supply for the soil remediation project. The production and supply of electricity and heat (PSE) sector contributed the most to off-site emissions, accounting for 56.05%, 67.76%, and 67.30% of total emissions for CCK, ESS, and SLW, respectively. Overall, the present study provides fresh insights to support a more holistic low-carbon assessment of soil remediation options.

Evaluation of thermal comfort during showering with system-related temperature fluctuations

With the decarbonization of heating sector with temperature-sensitive heat pump, comfort must be considered. For users, comfort is a decisive criterion that can hinder the decision for a supply system using renewable energies. Instantaneous domestic hot water heater pose a particular challenge here, as load changes can easily lead to temperature fluctuations. Therefore, the following study aims to determine the perception of temperature fluctuations during showering and to classify them for an assessment procedure. For this purpose, we carried out tests with 120 persons in a controlled environment. The test subjects showered at their desired temperature and gave direct feedback on imposed temperature fluctuations. Positive and negative changes with different rates of change were examined. We reported clear individual differences in the set desired temperatures as well as in the noticed and tolerated temperature fluctuations. The average desired temperature was 38.5 °C, with a quite large variation of ±5.5 K. While 2 % of the test subjects already noticed fluctuations <0.5 K and found them uncomfortable, for others (≈40 %) deviations of 4 K were still comfortable. Therefore, the resulting evaluation was based on a proportion of dissatisfied subjects according to the procedure described by the ISO 7730. This study represents a first step towards the introduction of standardized assessment of instantaneous water heaters and the comfort criteria would allow a comparison of control quality for different applications.

Is District Heating a cost-effective solution to decarbonise Irish buildings?

Achieving decarbonisation of the heating sector is a major challenge, especially in Ireland, which has the lowest proportion of renewable heat in Europe. In economically pursuing ambitious and equitable climate targets, Ireland’s Climate Action Plan 2023 set a goal of reaching 2.5 TWh of district heating by 2030, starting from a limited existing capacity. This pioneering study explores supply sources and heat density demand cohorts to develop a model to understand district heating in a low-deployment region, using Ireland as a case study. We also conduct a sensitivity analysis considering different connection rates.Our research demonstrates that district heating is pivotal in achieving optimal decarbonisation pathways. Incorporating district heating reduces marginal CO2 emission prices by 13%–25%. Additionally, with feasible growth limits applied, total savings for the energy system are anticipated to reach €17.2 billion by 2050. This reduction of emissions in the building sector, facilitated by district heating, allows for greater emissions allowances in other sectors and reduces reliance on electricity while meeting climate targets. These insights highlight the need for spatial energy policies and deepen our understanding of integrating district heating within an energy system optimisation model.

Assessing the impact of seasonality on bioenergy production from energy crops in Germany, considering just‐in‐time philosophy

AbstractThe availability of biomass is strongly influenced by seasonality, which can affect the production of biofuels, biogas, and bio‐based products in the downstream bioenergy supply chain. Rapeseed, maize silage, sugar beet, wheat, and grass from grassland are the most popular energy crops; they play a significant role in the German bioenergy strategy and are being discussed extensively in the current gas shortage context. Most models in the literature assume yearly temporal resolution for these energy crops, which can negatively impact the accuracy of results. This problem is increasingly relevant under weather conditions that are varying increasingly due to climate change; in this study we therefore employ the extended bioenergy optimization model (BENOPTex) to explore the impact of seasonality on the optimal deployment of biomass from energy crops in bioenergy production in the German heat, power, and transport sectors, which typically show high dependency on fossil fuels. First, we increased the model's temporal resolution using available datasets and documents. Next, the varying availability factors were embedded in the optimization model, considering the no‐storage policy for energy crops in accordance with the just‐in‐time philosophy. Finally, the outcomes of the BENOPTex with annual resolution were contrasted with the results including the effects of seasonality, while considering various objective functions. We demonstrated a shift toward the consumption of woody biomass until 2045 due to its longer shelf life and improved storability. The energy demand stemming from summer leisure travel was also anticipated to exceed the bioenergy system's capacity. The insights provided here might be interesting for policymakers who design roadmaps for bioenergy development with a more resilient energy supply.

Strategic features of heat supply in different countries

Aim. To analyze the features of different models of heat supply in different countries in terms of identifying strategic actors and their role in the analyzed models.Objectives. To analyze heat supply models in Russia, Kazakhstan, USA and China, as well as strategic features in heat supply models of different countries; to identify strategically significant actors that play a leading role in the heat supply industry in different countries; to compare and reveal the features that can contribute to the growth of efficiency of strategizing the domestic heat supply industry.Methods. The research is carried out in accordance with the strategy theory and strategy methodology developed by academician V.L. Kvint in the aspect of analyzing the external environment, interest groups and assessing the influence of strategic actors in the industry.Results. In all the studied countries the state plays the role of regulator and controller, as the industry directly affects the economy of any country and the well-being of citizens. However, the level of regulation and influence of the state on the industry differs. The population as an actor shaping the strategic feature is identified only in the USA. This is due to the high decentralization of the industry and complicates strategizing, because in accordance with the methodology of V. L. Kvint, everyone who will subsequently implement the developed strategy should participate in the strategizing process. Each model has advantages and disadvantages. The US model of heat supply takes into account the opinion of the actors most fully, although it is the most decentralized and has the least population coverage. In contrast, China’s ultra-high centralization model achieves efficient growth and predictable planning in the heat sector. However, this model focuses on achieving quick results through the wholesale supply of heat to industrial enterprises and the use of cheap, unecological fuels such as coal.Conclusions. Most of the models analyzed tend to decentralize the heat supply system. For effective strategizing in the Russian industry it is necessary to increase the role of consumers and generating companies as strategic actors in the heat sector.

Quantifying the Financial and Climate Impacts of Greenhouse Gas Abatement Pathways in Residential Space Heating

New York State (NYS) has set strict greenhouse gas (GHG) emission reduction targets across all sectors of its economy, including the heating sector. This study examines the financial value and environmental impacts of the residential space heating sector in NYS under different GHG abatement options by comparing the existing natural gas heating pathway with three potential GHG abatement pathways: renewable natural gas (RNG), hydrogen blended into RNG, and air-source heat pumps (ASHPs). These pathways are analyzed via a comparative net present value (NPV) framework from 2022 to 2042 with the emission reduction represented as a revenue stream that serves as a function of the social cost of GHGs. The investment timing of each of these pathways is also accounted for to reflect the pathways’ varying deployment timelines. The ASHP pathway with a 10% financial discount rate and a 2% social cost of the GHG discount rate achieves the lowest NPV. The RNG pathway achieves the highest NPV. A sensitivity analysis determines the impact of key factors on the NPV results. This study aims to inform policymakers, homeowners, and stakeholders of the potential benefits and costs of each of the four pathways to aid them in their decision-making process.

Dynamic simulation and experimental validation of a 35 MW heat pump based on a transcritical CO2 cycle

Replacing the baseload providers on the energy market with decarbonized renewable solutions increases frequency dynamics on the grid. In order to handle the concomitant risks and chances linked with this change of paradigm between energy producers and consumers, complex dynamic models are required to optimize energy management strategies. Industrial transcritical carbon dioxide (CO2) heat pumps, such as the one developed by MAN Energy Solutions Schweiz AG (MAN ES), offer a proven solution for the decarbonization of the district heating sector. Furthermore, they are associated with pathways to increase the usage of this solution for sector coupling applications. This work presents a detailed Modelica model of the high-temperature CO2 heat pump, focusing on the thermodynamic states of the refrigerant during load variations of the system. In a consecutive step, the model is validated against testbed data of a heat pump from MAN ES with over 35 MW heat supply and a lift from 40 to 100 K. The model results match the testbed data with an accuracy of over 95 % and demonstrate a full coverage of the performance map minimum to maximum speed, providing water-side supply temperatures of 50–109 °C. Realistic dynamics in fast load balancing operation are demonstrated where power consumption was varied by 80 % compared to maximum power within 30 s. Models of this kind are essential for an accurate prediction how decarbonized energy networks react by linking electricity and heat supply together. These predictions are ultimately useful to upgrade or optimize complex control strategies.

Modeling of the influence of local heat sources on a light gas stratification formation and erosion in a large-scale experimental facility using eddy resolving numerical approach

The main objective of this work is to evaluate the results of application of Implicit Large Eddy Simulation (ILES) turbulence modeling approach to simulate the complex hydrogen safety problem. The paper presents the results of numerical simulation of the OECD/NEA HYMERES (HYdrogen Mitigation Experiments for Reactor Safety) HP2 series tests in the PANDA facility, aimed at studying the thermal effect of passive autocatalytic recombiner (PAR) operation on mixing the containment atmosphere, using CABARET-SC1 code. The code is based on the eddy resolving CABARET technique, which allows implicit modeling of the subgrid turbulence scales without using tuning parameters (ILES approximation). The natural convection flow inside the PAR model was calculated explicitly using a simplified model of the heating section and the housing. Good agreement of calculated transient with experimental data was obtained, which indicates the effectiveness of such approach.

Comparative modeling of cost-optimal energy system flexibility for Swedish and Austrian regions

This study develops a reproducible method for estimating the cost-efficient flexibility potential of a local or regional energy system. Future scenarios that achieve ambitious climate targets and estimate the cost-efficient flexibility potential of demonstration sites were defined. Flexible potentials for energy system assessment are upscaled from the demonstration sites in Eskilstuna (Sweden) and Lower Austria (Austria). As heat pumps (HPs) and district heating (DH) are critical for future heat demand, these sites are representative types of DH networks in terms of size and integration with the electricity grid. In both regions a TIMES model is used for energy system optimization, while for upscaling, Eskilstuna uses the building-stock model ECCABS, whereas Lower Austria uses a mixed integer linear programming optimization model, and the BALMOREL power system model. According to the modeling, HPs will dominate Eskilstuna’s heating sector by 2040. In Lower Austria, DH becomes more prevalent, in combination with wood biomass and HPs. These findings are explained by the postulated technological-economic parameters, energy prices, and CO2 prices. We conclude that future electricity prices will determine future heating systems: either a high share of centralized HPs (if electricity prices are low) or a high share of combined heat-and-power (if electricity prices are high). Large-scale energy storage and biomass can be essential solutions as may deliver increased cost-effectiveness, if available and under certain conditions.

INVESTIGATION OF TEMPERATURE FIELDS DURING LOCAL INDUCTION HEATING OF THE CASING STRING IN THE WELL

One of the important tasks in geophysical studies of operating wells is the detection of behind the casing flows. The traditional complex of geophysical methods (thermometry, flow metering, composition methods, and others) does not always make it possible to detect the movement of fluid behind the well casing. To solve this problem, it is promising to use the method of active thermometry.Research technology using this method involves recording the temperature in the well during induction heating of a small section of metal casing. As a result of heat exchange between the heated section of the column and the liquid flow, a thermal disturbance is created in the annular flow channel. In the presence of behind the casing flow, heat will be carried away from the induction heating region in the direction of liquid movement and will be redistributed in the column above or below the heating interval. By recording the temperature of the casing during induction heating and after turning off the inductor, it is possible to establish the fact of cross-flow and quantify its flow rate.This paper studies the influence of the direction and flow rate of behind the casing flow on the unsteady temperature field in a metal casing during its local induction heating. The problem is solved numerically in the Ansys Fluent software package. The temperature field in the fluid in the wellbore is calculated taking into account free convection.The model temperature distributions obtained for different behind the casing flow configurations (direction, flow rate) can be used for quantitative interpretation, to determine the flow rate in the behind the casing flow channel by comparing actual and model temperature curves. To assess the intensity of behind-the-casing movement, time measurements at a “point” in the induction heating interval are also informative. The direction of flow is determined by the nature of the temperature distribution in depth above and below the induction heating section.

Coordinated scheduling of integrated electricity, heat, and hydrogen systems considering energy storage in heat and hydrogen pipelines

The increasing interdependency of electricity, heat, and hydrogen sectors in recent years provides a growing incentive to make use of the possible synergies obtained when coordinating these energy sectors from the perspective of an integrated energy system (IES). However, coordinated scheduling frameworks remain poorly developed for integrated electricity, heat, and hydrogen systems, and the energy storage potentials in heat and hydrogen pipelines have not been quantitatively analyzed. The present work addresses these issues by separately analyzing the energy storage value provided by district heat systems (DHSs) and hydrogen transmission systems (HTSs). These storage potentials are applied to develop an operation model that considers the delay characteristics of heat pipelines and hydrogen pipeline storage. Then, we develop a coordinated scheduling model for a power–heat–hydrogen IES. The analysis is facilitated by quantifying the value of energy storage in heat pipelines and hydrogen pipelines in terms of operation costs. Finally, a case study is conducted to verify the necessity of accounting for the dynamic energy storage potentials of the DHS and HTS during IES optimization. Numerical results verify the economic value of comprehensive consideration of heat and hydrogen pipeline storage, which results in higher operational flexibility of IES with lower operating cost and reduced wind power curtailment.

Optimal hydrogen infrastructure planning for heat decarbonisation

Energy decarbonisation is essential to achieve Net-Zero emissions goal by 2050. Consequently, investments in alternative low-carbon pathways and energy carriers for the heat sector are required. In this study, we propose an optimisation framework for the transition of heat sector in Great Britain focusing on hydrogen infrastructure decisions. A spatially-explicit mixed-integer linear programming (MILP) evolution model is developed to minimise the total system’s cost considering investment and operational decisions. The optimisation framework incorporates both long-term planning horizon of 5-year steps from 2035 to 2050 and typical days with hourly resolution. Aiming to alleviate the computational effort of such multiscale model, two hierarchical solution approaches are suggested that result in computational time reduction. From the optimisation results, it is shown that the installation of gas reforming hydrogen production technologies with CCS and biomass gasification with CCS can provide a cost-effective strategy achieving decarbonisation goal. What-if analysis is conducted to demonstrate further insights for future hydrogen infrastructure investments. Results indicate that, as cost is highly dependent on natural gas price, Water Electrolysis capacity increases significantly when gas price rises. Moreover, the introduction of carbon tax policy can lead to lower CO2 net emissions.

Measurement of carbon emissions and responsibility sharing for the industrial sector in Zhejiang, China

Carbon reduction is imperative for achieving carbon peaking and neutrality. Accordingly, it is important to determine which industrial sectors have more responsibility in this matter. Based on data from Zhejiang's input-output tables, this study applies the Input-Output method to measure and compare the carbon emissions of 42 industrial sectors in Zhejiang Province from 2002 to 2017, and then assesses the carbon emission attributes of each industrial sector, and ultimately determines the responsibility for carbon emission reduction from the perspectives of the producers and consumers. The results of the study show that direct carbon emissions and whole-process carbon emissions in Zhejiang increased continuously from 2002 to 2017, with carbon emission intensity first decreasing and then increasing. However, carbon emission intensity was much lower in 2017 than in 2002. Over time, the attributes of carbon emissions by sector changed little. Particularly, high-carbon sectors covered most of the energy supply sectors, low-carbon sectors were mostly tertiary-related, and pseudo-low-carbon sectors were mainly found in the productive services sector. In terms of carbon emission reduction responsibilities, there are large differences in emission reduction responsibilities between sectors, with the electricity and heat sectors bearing the largest responsibilities based on their production, consumption and total carbon emission reductions. The conclusions of this study can provide some data support for the further development of carbon peak and carbon neutral plans.

INVESTIGATING THE IMPACT OF INFORMATION FEEDBACK ON RESIDENTS’ ENERGY-SAVING BEHAVIOR IN THE HEATING SECTOR

Global fossil energy consumption is a significant source of carbon dioxide emissions and a major cause of global climate change. Heat consumption in the residential sector is an important part of this consumption. Based on reinforcement theory, this study analyzed the influence mechanism of information feedback on the residents’ energy-saving behaviors and applied the survey data from 1248 households in three Western European countries to analyze the impact of heat consumption information feedback on four typical heat-saving behaviors of residents. Finally, it applied the probit model to measure the quantitative effect of information feedback on the heat-saving behavior. Four heat-saving behaviors were considered: “improving house insulation”, “setting the thermostat to 20°C or below”, “turning the heat down at night” and “closing the windows when the heating is running”. The empirical results showed that heat consumption information feedback has a significant impact on residents’ heat-saving behavior. After adding the controlling variables, such as demographic variables, willingness to pay for greenness, environmental concern and environmental belief, the estimated results changed slightly, but the estimates of the study are still significant. According to the estimates, residents who can obtain the heat consumption information feedback timely were 9.3%, 5.2%, 5.9% and 4.3% more likely than residents who can’t obtain the heat consumption information feedback timely to adopt the heat-saving behaviors of “improving house insulation”, “setting the thermostat to 20°C or below”, “turning the heat down at night” and “closing the windows when the heating is running”.

Why germanys energiewende may fail to meet its goals: insights from power system simulation with natural generation

In order to achieve the Paris climate targets, the German government has developed phased plans and anchored these in an amendment to the Renewable Energy Sources Act (EEG). This not only defines expansion targets for renewable energy producers, but also the additional amounts of energy that must be available in the electricity grid in future if it is to supply the mobility and building heating sectors, which are currently still powered by fossil fuels. While the lack of grid transport capacities is recognized and discussed in the public debate, another known and critical hurdle is rarely presented here. This is the temporal distribution of power from renewable energies and its effects on the processes involved in controlling the grid balance. By analyzing a target scenario specified in the EEG for 2030 and another for 2040+, which a German economic research institute recommends to policymakers, the aim is to investigate whether their targets can be achieved under the conditions of the natural fluctuations occurring in Germany and the quantities of renewable energy that can be harvested with a reasonable use of resources. The focus is on simulating future generation curves using historical data in such a way that they show the typical weather-driven behaviour to be expected in Germany. Unavoidable Surplus generation is used as efficiently as possible with electricity and hydrogen storage systems. Both scenarios fall considerably short of their targets. CO2-free coverage of the demand specified for the long-term future is only possible with a quantity of generators that is at the limit of what is feasible. The reason for this is that the current plans are obviously based on an unrealistic picture of the temporal distribution of renewable energy output. Achieving the transformation goals in Germany could be much more complex than politicians currently believe and may require a change in strategy sooner or later.

Carbon neutrality in the Finnish energy sector: prospects for a fossil‐fuel phase out

AbstractThe Finnish government has set a target of reaching carbon neutrality by 2035 and renewable energy is playing an increasingly important role in the Finnish energy sector. Bioenergy from forest biomass is currently the most utilized renewable energy resource. European Union regulations are imposing limitations on the use of forest biomass for environmental reasons, however, and the energy sector is having to look for alternative renewable energy options to reach carbon neutrality. This paper reviews the latest changes in the energy industry in Finland and evaluates prospective renewable energy development and fossil fuel replacement in the future Finnish energy system. The study shows that only a combination of all available renewable energy forms can enable the carbon neutrality target to be achieved by 2035. There is a good possibility that Finland can replace fossil fuels fully in the energy sector; wind energy will increase its share of electricity production, and biomass will continue to play a crucial role in the heating sector. Industry and the transport sector, however, face greater challenges and should be studied in more detail.

Battery energy storage utilization in optimization of heat production in district heating sector

Battery energy storage utilization in optimization of heat production in district heating sector

Unveiling the Spatial Distribution of Heat Demand in North-West-Europe Compiled with National Heat Consumption Data

Space and water heating for residential and commercial buildings amount to a third of the European Union’s total final energy consumption. Approximately 75% of the primary energy is still produced by burning fossil fuels, leading to high greenhouse gas emissions in the heating sector. Therefore, policymakers increasingly strive to trigger investments in sustainable and low-emission heating systems. This study forms part of the “Roll-out of Deep Geothermal Energy in North-West-Europe”-project and aims at quantifying the spatial heat demand distribution in the Interreg North-West-Europe region. An open-source geographic information system and selected Python packages for advanced geospatial processing, analysis, and visualization are utilized to constrain the maps. These were combined, streamlined, and optimized within the open-source Python package PyHeatDemand. Based on national and regional heat demand input data, three maps are developed to better constrain heat demand at a high spatial resolution of 100 m × 100 m (=1 ha) for the residential and commercial sectors, and for both together (in total). The developed methodology can not only be applied to transnational heat demand mapping but also on various scales ranging from city district level to states and countries. In addition, the workflow is highly flexible working with raster data, vector data, and tabular data. The results reveal a total heat demand of the Interreg North-West-Europe region of around 1700 TWh. The spatial distribution of the heat demand follows specific patterns, where heat demand peaks are usually in metropolitan regions like for the city of Paris (1400 MWh/ha), the city of Brussels (1300 MWh/ha), the London metropolitan area (520 MWh/ha), and the Rhine-Ruhr region (500 MWh/ha). The developed maps are compared with two international projects, Hotmaps and Heat Roadmap Europe’s Pan European Thermal Atlas. The average total heat demand difference from values obtained in this study to Hotmaps and Heat Roadmap Europe is 24 MWh/ha and 84 MWh/ha, respectively. Assuming the implementation of real consumption data, an enhancement in spatial predictability is expected. The heat demand maps are therefore predestined to provide a conceptual first overview for decision-makers and market investors. The developed methods will further allow for anticipated mandatory municipal heat demand analyses.

Large scale integration of wind power – influence of geographical allocation

This paper investigates the influence of geographical allocation of wind power generation in Northern Europe, assuming large scale integration of wind power. The work applies a linear cost optimization model of the heat and power sector with a 1-hour time resolution. The model minimizes the sum of running costs to meet the heat and power demand and the wind power and transmission investment costs. Wind data are taken from modelled wind speed data from the Swedish Meteorological and Hydrological Institute. The Nordic countries and Germany were divided into regions and the 200 sites with the highest yearly output were chosen to represent the region. The model gives the most favourable distribution of wind power between the regions. In addition, the paper provides an assessment of the effect of geographical distribution of wind power with respect to influence on the aggregated wind power production (only considering the wind power generation itself). The modelling results show that the largest investments in wind power are made in the windy region of Southern Norway. However, depending on the cost of transmission allocating wind power near large load centers in Germany may also be favourable. As for the assessment of distribution of wind power, the wind data gives that if the 400 best sites in Europe were used, this would result in a capacity factor of 38.5% and a lowest output of 2.5 % of rated power (applying 2009 wind data).