Primary Energy Usage Research Articles

Optimizing renewable energy integration in new districts: Power-to-X strategies for improved efficiency and sustainability

To achieve optimal renewable energy self-sufficiency in new districts, it's crucial to efficiently manage surplus electricity or heat. One effective approach is ‘sector coupling,’ which increases self-consumption by redirecting excess energy via heat pumps (Power-to-Heat) or producing hydrogen (Power-to-Gas). Integrating electric vehicles and storage solutions (Power-to-Power) further enhances system flexibility. Moreover, the implementation of energy communities offers not just an uptick in self-consumption but also encourages consumers to embrace renewable energy technologies. This study evaluates the integration of renewable energy within urban districts through ‘sector coupling’ strategies, aiming to enhance self-sufficiency and consumption by managing surplus electricity and heat. Focusing on a renovated district in Southern Italy, it compares Power-to-X strategies—such as Power-to-Heat, Power-to-Gas, and Power-to-Power—in terms of their impact on primary energy usage, CO2 emissions, and financial costs. Dynamic simulations show these strategies can reduce CO2 emissions by 30 % and energy use by 20 % on average, offering valuable insights for urban energy planning and policy.

Multimodal Framework for Smart Building Occupancy Detection

Over the years, building appliances have become the major energy consumers to improve indoor air quality and occupants’ lifestyles. The primary energy usage in building sectors, particularly lighting, Heating, Ventilation, and Air conditioning (HVAC) equipment, is expected to double in the upcoming years due to inappropriate control operation activities. Recently, several researchers have provided an automated solution to turn HVAC and lighting on when the space is being occupied and off when the space becomes vacant. Previous studies indicate a lack of publicly accessible datasets for environmental sensing and suggest developing holistic models that detect buildings’ occupancy. Additionally, the reliability of their solutions tends to decrease as the occupancy grows in a building. Therefore, this study proposed a machine learning-based framework for smart building occupancy detection that considered the lighting parameter in addition to the HVAC parameter used in the existing studies. We employed a parametric classifier to ensure a strong correlation between the predicting parameters and the occupancy prediction model. This study uses a machine learning model that combines direct and environmental sensing techniques to obtain high-quality training data. The analysis of the experimental results shows high accuracy, precision, recall, and F1-score of the applied RF model (0.86, 0.99, 1.0, and 0.88 respectively) for occupancy prediction and substantial energy saving.

Virtual Prosumers and the Impact of Remote Solar Parks on Lithuania’s Buildings Decarbonization Efforts

Abstract To reduce the carbon footprint of buildings, the concept of virtual prosumers (consumers who both consume and produce) using remote solar energy parks represents a novel method in Europe. In 2019, Lithuania became the first country in Europe to introduce a digital platform that enables the buying or renting of parts of a remote solar park, making it the first such platform in the world to operate on a national scale. This study examines the effectiveness of this model in Lithuania, assessing the model’s success, public engagement, and success factors. The main study focus is on evaluating the impact of remote solar parks on the decarbonization of buildings, particularly through the prism of virtual prosumer participation. This study integrates both qualitative and quantitative data. The quantitative analysis includes a detailed case study, evaluating the amount of energy produced by two selected remote solar parks in Lithuania, as well as their impact on the carbon dioxide emissions and primary energy use of the two individual houses (a detached house and a unit within an apartment building) connected to these remote power plants. In Case Study A, the renewable primary energy usage was 22.19 kWh/m2 compared to a minimal 0.22 kWh/m2 of non-renewable energy (CO2 emissions 0.0 kgCO2/kWh). Case Study B showed 181.38 kWh/m2 of renewable energy versus 3.63 kWh/m2 of non-renewable energy (CO2 emissions 6.17 kgCO2/kWh). Concurrently, qualitative methods involve analysing the existing legal and economic frameworks in Lithuania and Europe, which either facilitate or impede the prosumer model, in addition to examining the necessary technological infrastructure. Key findings of this study highlight the potential of remote solar energy parks to significantly reduce the carbon emissions of buildings. This model is especially beneficial for structures where onsite solar energy solutions are impractical. It fosters greater inclusivity in adopting renewable energy, enabling a variety of stakeholders to participate in and benefit from clean energy production. However, the study identifies several major challenges, including regulatory restrictions, the need for infrastructure development, a shortage of developers, state contributions, public awareness, and the creation of a unified platform.

Progress in Gallium Oxide Field-Effect Transistors for High-Power and RF Applications.

Power electronics are becoming increasingly more important, as electrical energy constitutes 40% of the total primary energy usage in the USA and is expected to grow rapidly with the emergence of electric vehicles, renewable energy generation, and energy storage. New materials that are better suited for high-power applications are needed as the Si material limit is reached. Beta-phase gallium oxide (β-Ga2O3) is a promising ultra-wide-bandgap (UWBG) semiconductor for high-power and RF electronics due to its bandgap of 4.9 eV, large theoretical breakdown electric field of 8 MV cm-1, and Baliga figure of merit of 3300, 3-10 times larger than that of SiC and GaN. Moreover, β-Ga2O3 is the only WBG material that can be grown from melt, making large, high-quality, dopable substrates at low costs feasible. Significant efforts in the high-quality epitaxial growth of β-Ga2O3 and β-(AlxGa1-x)2O3 heterostructures has led to high-performance devices for high-power and RF applications. In this report, we provide a comprehensive summary of the progress in β-Ga2O3 field-effect transistors (FETs) including a variety of transistor designs, channel materials, ohmic contact formations and improvements, gate dielectrics, and fabrication processes. Additionally, novel structures proposed through simulations and not yet realized in β-Ga2O3 are presented. Main issues such as defect characterization methods and relevant material preparation, thermal studies and management, and the lack of p-type doping with investigated alternatives are also discussed. Finally, major strategies and outlooks for commercial use will be outlined.

The experimental study of dehumidification and regeneration processes in a fin and tube liquid desiccant system

Significant focus has been placed on improving Indoor Air Quality (IAQ) due to the emergence of the large-scale severe acute respiratory syndrome (SARS) virus epidemic in the air conditioning system of buildings. There is also a need for an adequate air ventilation system that balances energy needs with air quality. This led to the discovery of liquid desiccants which have the ability to enhance air quality and lower primary energy usage as an alternative to the standard air dehumidification technology. Therefore, this study was conducted to investigate the dehumidification and regeneration processes in a Fin and tube liquid desiccant system. This involved flowing air horizontally while the ionic liquid flowed through the cooling or heating coil vertically downward to create a cross-flow fin and tube configuration. In the testing process, we obtained measurements of relative humidity and dry bulb temperature inlet and outlet from ducting by varying the input parameters. Moreover, the differential humidity ratio of the inlet and output process for the dehumidification and regeneration was observed to be essential for the dehumidifier performance indices. The experimental result showed that the system absorbed a humidity ratio of 5.5 g/kg during the dehumidification process and released 10.7 g/kg during regeneration.

Transient analysis of buildings with Trombe wall in a southern envelope and strengthening efficacy by adding phase change material

In a long-term analysis (1965–2020), primary energy usage (EU) grew by 48.7% and in China by 1226%. In this study, considering the cold climate in the China region, Eu in the residential sector was investigated. The building uses the Trombe wall on the south side to consume less heat energy to regulate the temperature. In the residential building, a schedule was applied to take into account heat gains of occupancy, lighting and equipment, and then the summer and winter temperatures were defined following people's presence. To improve the effectiveness of the Trombe wall, PCM was mounted in it. To study the natural convection, the momentum and energy equations for the indoor space were extended along with the area enclosed in the Trombe wall. The energy equation for all the walls was then discretized using finite difference methods to determine the thermal flux at boundaries. Energy analysis was performed for residential buildings, and the results showed that the Trombe wall had an acceptable performance in reducing EU by 26.5% in winter while increasing EU by 5.5% during the year. With the addition of PCM to the Trombe wall, the EU in all months decreased, and in one year, EU decreased by 18%.

Performance evaluation and spectrum-based analysis of a wall-mounted photovoltaic system for zero-energy building

The concept of zero-energy building (ZEB) has attracted global attention in recent years as it involves offsetting the primary energy usage of a building on an annual base by the energy generated from renewable resources. The performance of wall-mounted photovoltaics (PV) for building applications has great potential for ZEB. In this study, we compared wall-mounted and common roof-mounted PV systems using a combination of experimental and theoretical studies. The wall-mounted PV system exhibited an unusual performance behavior depending on the season. Winter is a suitable season for energy production from the wall-mounted PV system because of the low solar altitude and resulting lower incident angle of the sun. However, the performance ratio (PR) had twin peaks throughout the day that could not be explained by the classical model that uses irradiance and temperature variation. In summer, there was less irradiance on the vertical wall and the PR had triple peaks that were also hard to explain using the conventional model. We established a detailed output power model of the wall-mounted PV using spectrum variation on a vertical plane. Our approach is the development of spectrum model that can be applied to all-climate and computed the performance variation according to the sun’s orientation and incident angle. Our model quantitatively explains unique seasonal and daily efficiency variations for the wall-mounted PV system (twin peaks in winter and triple peaks in summer). Our validated model can be utilized to map a suitable location for a wall-mounted PV system.

Estimation of waste heat and its recovery potential from energy-intensive industries

The recovery and reuse of waste heat offers a significant opportunity for any country to reduce its overall primary energy usage. Reuse of waste heat improves the ambient air quality by reducing both industrial pollution and greenhouse gas emissions from industries. This paper presents an estimation of thermal waste heat potential in five energy-intensive industrial sectors (i.e., iron and steel, chemical and petrochemical, paper and pulp, cement, and glass), based on data available in the extant literature and government reports. The findings show that both the chemical and petrochemical industries have the highest theoretical waste heat to power generation capacity for the selected industries. In addition, six individual plant data were collected for case study to determine their waste heat potentials. These estimates were further used to identify the power generation potential using the organic Rankine cycle based on economic advantages, whereby the iron and steel industries were found to have the maximum power generation potential of 66.5 TWh using its waste heat.

Life Cycle Assessment of bioenergy production from mountainous grasslands invaded by lupine (Lupinus polyphyllus Lindl.)

Mountainous grasslands are typically important habitats both for fauna and flora but increasingly suffer from invasions by neophytes (i.e. Lupinus polyphyllus Lindl.) in most German low mountain areas, which eventually threatens species richness. Regular defoliation is required to eliminate the invasion, however, at present options to handle the harvested biomass are limited. Integrated generation of solid fuel and biogas from biomass (IFBB) and anaerobic digestion (AD) are two possible options to utilise the biomass and convert it into energy. There is substantial environmental impact associated with the energy and resource usage during conversion of the biomass into fuel and during usage of fuels and co-products obtained. This study examines IFBB and AD to identify the best option in terms of environmental impacts and primary energy usage, also looking at alternatives for process parameters along the life cycle that would reduce environmental impacts. It was found that IFBB was a better option compared to AD, as it had higher environmental and primary energy savings across all grassland sites. Higher energy conversion efficiency of IFBB resulted in higher greenhouse gas (GHG) and energy savings, even though the energy usage for the processing steps were higher compared to AD. Biomass yield was positively related to the savings, providing better GHG and energy savings for grasslands containing invasive species. There were no savings in terms of acidification (AP) and eutrophication potential (EP) for both IFBB and AD, however AP and EP was lower using IFBB compared to AD. Hence, biomass originating from mountainous grasslands with lupine invasion could be effectively utilised with IFBB, as this option had lower environmental impacts and higher energy savings compared to AD. Biomass from non-invaded grasslands could also be converted effectively using IFBB, hence IFBB could be used to utilise the harvested biomass in the situation where the invasion is eliminated.

A methodology for analyzing renewable energy opportunities for desalination and its application to Aruba

There are numerous possible technology combinations for providing desalination using renewable energy sources. This paper presents a model that captures facets ranging from hourly availability of the renewable energy sources to economic parameters such as inflation and discount rate without relying on third-party software. The proposed approach considers different combinations of reverse osmosis and multi-stage-flash distillation driven by wind, solar PV and solar thermal with reference systems driven from the electric grid or natural gas. The levelized cost of water and the primary energy usage are presented as the main indicators for the performance of the different system architectures. Aruba is chosen as an example to show an application of the model. The project duration and the efficiency of desalination technologies is used to demonstrate the model capability for sensitivity analyses. The authors provide all used equations in the supplemental material to this paper.

Economic performance of multi-energy supply system in a zero-carbon house

Due to the improvement of people's living standards, uptake of multi-functional household appliances, electricity consumption accounts for a rising ratio in the proportion of primary energy usage. Currently, electricity accounts for more than 50% of primary energy usage and city gas is about 21% of total. The aim of this research focus on improving the efficiency of household energy usage and optimizing the economy of residential energy systems. This paper classified the detail electricity consumption and generation for a Japan typical household with Hybrid Fuel cell and Photovoltaic System (HFPS) based on the history monitored data. Then a simulation model of the Hybrid Heat pump and Photovoltaic System (HHPS) was designed under the same user load for analyzing the energy consumption. Finally, the economy of the two systems is compared and optimized by considering the carbon tax, equipment price and energy price fluctuation. In general, by comparing the environmental and economic performances of both two systems, the results showed that HFPS has a better environmental performance than HHPS, but HHPS presented an economic advantage over HFPS. In addition, with the change of equipment price and the development trend of energy price in the future, the economic performance of HFPS is gradually improved, which is better than HHPS and has more development prospects. The results of this work provide policy guidance for the future Japanese government's promotion of residential fuel cell systems, while choosing the optimal path between user energy characteristics and power contract scheme.

Virtual testbed for model predictive control development in district cooling systems

Recently, with increasing cooling demands, district cooling has assumed an important role as it is more efficient than stand-alone cooling systems. District cooling reduces the environmental impact and promotes the use of renewable sources. Earlier studies to optimise the production plants of district cooling systems were focused primarily on plants with compressor chillers and thermal energy storage devices. Although absorption chillers are crucial for integrating renewable sources into these systems, very few studies have considered them from the cooling perspective. In this regard, this paper presents the progress and results of the implementation of a virtual testbed based on a digital twin of a district cooling production plant with both compressor and absorption chillers. The aim of this study, carried out within the framework of INDIGO, a European Union-funded project, was (i) to develop a reliable model that can be used in a model predictive controller and (ii) to simulate the plant using this controller. The production plant components, which included absorption and compressor chillers, as well as cooling towers, were built using the equation-based Modelica programming language, and were calibrated using information from the manufacturer, together with real operation data. The remainder of the plant was modelled in Python. To integrate the Modelica models into the Python environment, a combination of machine learning techniques and state-space representation models was used. With these techniques, models with a high computational speed were obtained, which were suitable for real-time applications. These models were then used to build a model predictive control for the production plant to minimise the primary energy usage. The improvements in the control and the resultant energy savings achieved were compared with a baseline case working on a standard cascade control. Energy savings up to 50% were obtained in the simulation-based experiments.

Analysis of low temperature lift heat pump application in a district heating system for flue gas condenser efficiency improvement

District heating (DH) is widely used in heating buildings in Europe, while Latvia takes the 2nd place among European countries by percentage of citizens served by district heating (Euroheat & Power, 2016). In Riga, DH heat is produced by several plants – gas and biomass – that are connected in one network. Exhaust gas temperature from DH plants reach 130 °C and is decreased by flue gas condenser by utilizing the wasted heat from the flue gas. The aim of this research is to evaluate the theoretical feasibility of using low-temperature lift heat pumps in the DH system for flue gas condenser efficiency improvement. The study examines connection scheme when a heat pump is installed on heating network’s return line before flue gas condenser, so the heat pump can utilize the return line of the DH network as the heat source and forward line as the sink. Six scenarios were evaluated with two different heat pumps. All calculations have been done by using developed for this purpose TRNSYS model and based on real data from Riga biomass heating plant for 2016 and 2017 years. The results show that theoretically heat pump with low-temperature lift can be applied in the district heating systems for flue gas condenser efficiency improvement. It allows decreasing primary energy usage and CO2 emissions, at the same time being cost-effective.

Case Study of Thermal Diagnostics of Single-Family House in Temperate Climate

Reduction of the primary energy consumption is a crucial challenge for the building sector due to economic and environmental issues. Substantial savings could be achieved within the household. In this paper, we investigate the energy performance of a single-family house located in the temperate climate. The assessment is based on the comprehensive thermal diagnostic of the building performed on-site and via computational analyses. The on-site measurements included diagnostics of the building envelope, heat source, heating and domestic hot water system, ventilation system, and indoor environmental quality. Analyses confirmed that the studied building, which was built in 2008, meets the legislation requirements for the primary energy usage at that time and nowadays. However, results show discrepancies between energy performance obtained through on-site measurements and computational methods following regulations. Partially, discrepancies are a result of differences on normative values and how the building is operated in practice. It is also showed how important the role in the assessment of energy consumption through measurements is played by the measurement period.

Understanding the performance gap: a machine learning approach on residential buildings in Turin, Italy

Buildings account for the highest share of primary energy usage and greenhouse gas emission in the E.U. and U.S. [1], and most of this energy is used for space and water heating. Being able to gain a broader understanding of the gap between predicted and in situ measured thermal performance of buildings may, in a lot of cases, help reducing the energy consumption and, therefore, alleviating our pressure on the environment [2]. The aim of this research is to further investigate this performance gap and to evaluate the possibility of using machine learning algorithms to effectively predict the energy demand of buildings. For this purpose, a group of residential buildings in the city of Turin, Italy, is taken as case study: an estimation of their yearly heating demand is made using different machine learning algorithms, and their results are evaluated and discussed. The research showed that the use of machine learning resulted in a performance gap in line, if not lower, with the current literature. The reasons for this outcome, as well as possible future research directions are finally discussed.

Development of a topology analysis tool for fifth-generation district heating and cooling networks

Fifth generation district heating and cooling networks are characterized by supply temperatures in the ambient range of 15–25 °C, which not only reduces heat loss but also allows for integrating various kinds of low-temperature waste heat sources. The ability of these networks to absorb waste heat that is normally unrecoverable makes them an attractive solution for the future energy supply of urban areas. To enhance the adoption of these networks, this paper describes the development of a software tool to analyze the feasibility of fifth-generation of district heating and cooling systems in both new and existing districts. The research attempts to answer the question: ”Which buildings should be connected to a low-temperature hydraulic network given both the incremental benefits and costs relative to the scenario of decentralized (dedicated) heating and cooling systems for each building?” Therefore, all possible network layouts of the buildings are considered where the heating and cooling demands of each building are met by the fifth-generation of district heating and cooling network. For the heating and cooling load characterization of the buildings, reduced-order models are used while renewable energy and waste heat sources are included in the network. The focus of the research lies in the development of a hydraulic model for flexible use in the urban energy modeling and the optimization of the fifth-generation of district heating and cooling network topology for a given urban district. Simulation results quantify the performance of the fifth-generation of district heating and cooling network based on various output metrics, including primary energy usage, carbon dioxide emissions, and network implementation cost.

Three considerations for modeling natural gas system methane emissions in life cycle assessment

Natural gas is a fossil fuel accounting for about 30% of US primary energy consumption. Climate change is one of the primary environmental issues associated with natural gas use: natural gas combustion releases carbon dioxide. A less emphasized issue is that natural gas is mostly methane, a potent greenhouse gas (GHG). The climate impact of natural gas use is thus sensitive to the amount of methane that escapes from the natural gas system unburned. We call attention to three considerations for modeling natural gas-related methane emissions in life cycle assessment (LCA). First, natural gas system methane leakage is inconsistently characterized and likely systematically underestimated by commonly used life cycle inventory (LCI) databases. Second, studies are often imprecise in assumptions about process boundaries. This matters because not all natural gas uses rely on the same infrastructure and induce the same methane leakage. Third, there is not yet a stable estimate for the global warming potential (GWP) of methane. Newer estimates tend to be larger, which further exacerbates the underestimation of GHG impacts from natural gas systems. Data uncertainty is common in LCA, but natural gas-related methane emissions deserve special attention due to their influence on a decision-relevant parameter (GHG intensity) in product systems across the economy.

DUE-A: Data-driven Urban Energy Analytics for understanding relationships between building energy use and urban systems

Abstract Cities account for over 75% of all primary energy usage in the world with buildings making up the bulk of this usage. It is well acknowledged that the building energy usage is greatly impacted by urban context and thus understanding the relationships between building energy use and surrounding urban systems is critical for more energy efficient and holistic planning. This paper proposes a Data-driven Urban Energy Analytics (DUE-A) workflow to investigate and quantify the relationships between building energy usage and the spatial proximity of other urban systems. A case study of 530 buildings in a mid-size city in the Unites States is conducted to validate the performance of the workflow and demonstrate the statistical significance of relationships between building energy use and spatial proximity of other systems. Results show that spatial proximity of other buildings, roads and trees can have both positive and negative impacts on the mean, variability and distribution of building energy usage, and indicate that more holistic planning and design of cities could unlock urban energy efficiency and low-carbon municipal pathways.

Survey on the Operation of the District Energy Supply System in Japan According to Secular Change

Japan aimed for independent energy provision of large-scale energy consumers and energy efficient supply, so it actively introduced the District Energy System (DES) in the 1970s. A total of 133 sites (2 sites are unclear) are currently in operation, with 23 DESs established since 2000, and 110 sites consisting of superannuated facilities that are more than 20 years old. The purpose of this study is to compare and analyze the operational status of the DESs according to secular change, by identifying the supply area, the primary energy usage, and the utilization of renewable energy. As of 2003, 164 sites were in operation, and as of 2015, there were 133 sites. About 83% of the 133 sites were obsolete, being – more than 20 years old. About 87% areas showed lowered ratios of input primary energy in 2015 compared to that in 2003. The rate of operation of the main DES energy production system, cogeneration, has declined significantly, and the number of areas that use a current system rather than operate in cogeneration, has increased. This may have been due to the reduction of end use demand by the aging of the cities and the deterioration of the facilities. Therefore, it is necessary to suggest a new direction for the DES in preparation for the aging of their localities.

Developing a framework for assessing the impact of geothermal development phases on ecosystem services

The 2014 Indonesian National Energy Policy has set a target to provide national primary energy usage reached 2.500 kWh per capita in the year 2025 and reached 7.000 kWh in the year 2050. The National Energy Policy state that the development of energy should consider the balance of energy economic values, energy supply security, and the conservation of the environment. This has led to the prioritization of renewable energy sources. Geothermal energy a renewable energy source that produces low carbon emissions and is widely available in Indonesia due to the country’s location in the “volcanic arc”. The development of geothermal energy faces several problems related to its potential locations in Indonesia. The potential sites for geothermal energy are mostly located in the volcanic landscapes that have a high hazard risk and are often designated protected areas. Local community low knowledge of geothermal use also a challenge for geothermal development where sometimes strong local culture stand in the way. Each phase of geothermal energy development (exploration, construction, operation and maintenance, and decommissioning) will have an impact on the landscape and everyone living in it. Meanwhile, natural and other human-induced drivers will keep landscapes and environments changing. This conference paper addresses the development of an integrated assessment to spatially measure the impact of geothermal energy development phases on ecosystem services. Listing the effects on the ecosystem services induced by each geothermal development phases and estimating the spatial impact using Geographic Information System (GIS) will result in an overview on where and how much each geothermal development phase affects the ecosystem and how this information could be included to improve national spatial planning.