Thermal Energy Demand Research Articles

Optimisation of multi-period renewable energy systems with hydrogen and battery energy storage: A P-graph approach

Renewable energy systems play an important role in alleviating environmental pollution, and their characteristics, including low emissions and recyclability, are highly favourable. At present renewable energy can be costly and renewable energy systems have room for optimization, particularly systems which cater to remote and island areas. This paper develops a P-graph-based multi-period energy model, using hydrogen for energy storage to satisfy the fluctuating electrical and thermal energy demand of an island. Hydrogen can be generated from renewable energy sources during off-peak periods and can be used to serve as an energy carrier. An economic and carbon footprint analysis of the system is performed, which compares a pure renewable energy system, with hydrogen storage, and with battery storage. Within the same scenario, the results show that the renewable energy systems with hydrogen storage and battery storage are 21.5 % and 5.3 % cheaper than the renewable energy system without energy storage, with CO2eq emissions of 1,717 t/y and 1,680 t/y. These findings show that the inclusion of energy storage systems has great potential to reduce costs within renewable energy systems. Changes in the supply of biomass were investigated (which had the greatest impact in the study area), as well as changes in the cost of hydrogen storage. In addition to the optimal solution, near-optimal solutions were also suggested to provide well-rounded guidance for implementation.

BECCS opportunities in Brazil: Comparison of pre and post-combustion capture in a typical sugarcane mill

In order to make feasible the efforts that would limit the rise of Earth's temperature to no more than 2 °C, profound changes are required in the energy systems. In this sense, BECCS are considered instrumental to attain possible negative emissions. This draws attention to the sugarcane industry in Brazil, where it is possible to produce fuel ethanol at a relative low cost and a large amount of relatively cheap biomass is available. This paper is part of a research that aims to study the combined production of liquid fuels and electricity, using sustainable sources of biomass and maximizing carbon capture. Two cases related to an innovative technology were evaluated and in both the capture is based on amine technology: pre-combustion capture of CO2 from the fuel gas derived from biomass gasification, and post-combustion capture from gas turbine exhaust gases. Information from the scientific literature was used in modelling the systems, as well as estimating energy penalties and costs associated with capturing, transporting and storing CO2. The results indicate technical feasibility of both capture options, but difficulties in setting the full integration of the power unit (BIG-CC) with the sugarcane mill and the CCS system, due to the high demand for thermal energy as low-pressure steam. The estimated CO2 abatement cost is in the range 60–71 €/tCO2 for pre-combustion capture, and 52–63 €/tCO2 in the case of post-combustion. Feasibility results are impacted by the scale of CO2 capture (0.82–1.44 MtCO2/year), particularly in the pre-combustion case, and the relatively high cost of electricity generation.

Simulation of thermal comfort and energy demand in buildings of sub-Himalayan eastern India - Impact of climate change at mid (2050) and distant (2080) future

The global warming associated with climate change predicted by the Intergovernmental Panel on Climate Change (IPCC) is expected to deteriorate the indoor climate of free-running buildings. Features like proper orientation and wall thickness are important for the design of a building that is resilient to the impact of climate change. However, the implementation of these features is sometimes difficult, especially in a rugged hilly location. A whole building simulation was performed using DesignBuilder for an existing 3-storey free running multi-family concrete building located in the sub-Himalayan region of eastern India, for thermal comfort and energy demand during the present and the climate change scenarios of 2050 and 2080. The results show an increasing trend in the indoor operative temperature during the future climatic scenario, with the condition inside the top roof-exposed floor deteriorating the most. A decrease of 59.8% and 81.2% in the annual heating energy and an increase of 221.9% and 467.0% in the annual cooling energy were predicted for the future climate of 2050 and 2080 compared to the present. Parametric analysis performed considering orientation, wall U-value, infiltration rate and window-to-wall ratios revealed that the east/south-east facing orientation would perform the best with regard to overheating due to climate change. Further, the use of autoclaved aerated concrete (AAC) brick is recommended along with the decrease in air infiltration rate and window-to-wall ratio to improve the thermal performance of the indoor environment. In addition, we have also proposed a method to assess the under-cooling of an indoor environment.

Novel Neural Network Optimized by Electrostatic Discharge Algorithm for Modification of Buildings Energy Performance

Proper analysis of building energy performance requires selecting appropriate models for handling complicated calculations. Machine learning has recently emerged as a promising effective solution for solving this problem. The present study proposes a novel integrative machine learning model for predicting two energy parameters of residential buildings, namely annual thermal energy demand (DThE) and annual weighted average discomfort degree-hours (HDD). The model is a feed-forward neural network (FFNN) that is optimized via the electrostatic discharge algorithm (ESDA) for analyzing the building characteristics and finding their optimal contribution to the DThE and HDD. According to the results, the proposed algorithm is an effective double-target model that can predict the required parameters with superior accuracy. Moreover, to further verify the efficiency of the ESDA, this algorithm was compared with three similar optimization techniques, namely atom search optimization (ASO), future search algorithm (FSA), and satin bowerbird optimization (SBO). Considering the Pearson correlation indices 0.995 and 0.997 (for the DThE and HDD, respectively) obtained for the ESDA-FFNN versus 0.992 and 0.938 for ASO-FFNN, 0.926 and 0.895 for FSA-FFNN, and 0.994 and 0.995 for SBO-FFNN, the ESDA provided higher accuracy of training. Subsequently, by collecting the weights and biases of the optimized FFNN, two formulas were developed for easier computation of the DThE and HDD in new cases. It is posited that building engineers and energy experts could consider the use of ESDA-FFNN along with the proposed new formulas for investigating the energy performance in residential buildings.

Feasibility of Solar Thermal and Photovoltaic Integrated With Building Facade, a Case Study in Thimphu

Based on energy simulations, the annual energy demand of the DHI office is estimated to be 3,739 kWh. The total energy includes heating, lighting, and equipment energy requirements. The thermal energy demand of the office is 2,240 kWh and the combined lighting and equipment energy is 1,499 kWh. A radiation analysis of the front of the office is carried out to determine which facade received the most solar radiation. The annual global solar radiation received on building facade are 2.6 kWh/m^2, 2.4 kWh/m^2 and 2.3 kWh/m^2 on south, west and east facing facade respectively. Accordingly, the radiation results concluded that the south-facing facade is the most promising facade, followed by the west-facing facade and the east-facing facade. The proposed STC system, designed to maintain hot water temperature of 55°C, and simulations indicate that it would generate 2,440 kilowatt-hours of heating energy per year. This thermal energy would be sufficient to meet the space heating energy needs of the DHI office. Finally, the possibility of installing photovoltaic (PV) panels on the west-facing facade area 26 m^2 was simulated, suggesting the potential of 2,016 kWh of energy, which could replace the total lighting loads of 1,499 kWh currently received from grid supply.

Evaluation of technical and economic potential of waste heat distribution networks in industrial sites

This paper presents a methodology for the evaluation of waste heat distribution networks in industrial sites. In the context of ultra-efficient industrial sites, implementing these networks shows significant energy cost and emission reduction potential through cooperation between companies. To this end, a mathematical methodology for waste heat distribution network simulation was developed. In this approach, a differential equation relating radial heat losses and internal temperature was derived to include temperature changes inside the pipe system. Furthermore, relevant parameters such as diameter, insulation thickness, and temperature at source and sink were used to determine the distribution network’s technical and economic feasibility . Using time discrete, characteristic thermal energy supply and demand data in the analysis framework, the technical and economic assessment of waste heat distribution networks was carried out via the use case of an industrial park. In this use case, the economic and ecological advantages were quantified and shown.

Thermal management of a mono-crystalline PV/T system using gold plasmonic nanofluid based optical filter

Solar energy can fulfill most of the world's electrical and thermal energy demands. The utilization of nanofluids in solar Photovoltaic/Thermal (PV/T) systems, to enhance the overall system performance using passive and active methods, have been studied explicitly in the last few years. More recently, nanofluid-based optical filters are integrated in decoupled fashion with Photovoltaic (PV) systems for the effective utilization of solar spectrum i.e. below and beyond the band-gap of PV cells. For the work presented here, we compared thermal performance of Au nanofluid-based optical filter (at 0.0002 wt%)over base fluid water on a 50 W mono-crystalline PV module under real outdoor conditions. The study results showed that in comparison to DI water, Au lowers the average surface temperature of the PV module, and hence better overall system efficiency compared to water as an optical filter. The overall efficiency of PV/T system was observed about 42%, 37% and 14% with Au nanofluid optical filter, de-ionized water filter, and bare PV module, respectively. This study revealed that the overall efficiency of the PV module with Au nanofluid as the optical filter can be enhanced.

Arundo donax L. as sustainable building material

Arundo donax L. (ADL), also known as giant reed or Mediterranean cane, is a riparian herbaceous species characterized by long and robust stems. Classified as an invasive species because of its high capacity to grow, this natural material has been used for centuries in several sectors: handicrafts, agriculture and, mostly important, in buildings. Even if this species is easily found in the most of Mediterranean landscapes and is characterized by a large employment, most of its physical and mechanical properties are still unknown. In this context, the paper focuses on the identification of the ADL properties as plant and the assessment of the benefits to use Arundo donax in the field of constructions, especially in terms of environmental impact, through a careful analysis of existing architectures. Moreover, a simulation for the determination of the thermal performance and energy demand of a building that use Arundo donax as insulating material is proposed, also comparing the results to traditional insulating products.

The matching model of thermal energy supply and demand in power generation park with new energy and municipal solid waste

The matching model of thermal energy supply and demand in power generation park with new energy and municipal solid waste

Comparison Study and Assessment of Thermal Performance and Energy Self-sufficiency of Nearly Zero Energy Building (nZEB) in Two Different Climates

The paper presents a comparative study of a nearly zero-energy office building with respect to two different cities located in two different climate zones: a humid continental climate with dry winter, represented by the city of Seoul and a hot semi-arid climate, represented by the city of Benguerir. Obviously, climate is one of the most influential factors affecting indoor thermal comfort, energy demand and energy self-sufficiency of nZEBs. In this study, we first assess the impact of regional climate on the thermal performance, and we explore the influence of the local natural energy sources on the Solar BIPV and PV outputs in the two different cities: Benguerir and Seoul, respectively. And then, we explore the overall energy self-sufficiency of the nZEB for the respective climates. The differences in thermal need and energy self-sufficiency responses were statistically significant. With respect to Benguerir, the thermal energy needs for cooling amount to 71.5 kWh/m²/year, with almost no heating thermal needs and the Energy Balance (EB) reaches 0.88. On the other side, these metrics are around 52.56 kWh/m²/year for the total thermal needs with a share of 43% for heating thermal needs and a yearly EB equals to 0.6 for the nZEB in Seoul. Finally, it is important to mention that the BIPV output share out of the total solar energy output amounts to 57% and 61% for the cities of Seoul and Benguerir, respectively, which highlight the important role of BIPV in reaching advanced levels of energy self-sufficiency.

The matching model of thermal energy supply and demand in power generation park with new energy and municipal solid waste

The matching model of thermal energy supply and demand in power generation park with new energy and municipal solid waste

An Optimized Machine Learning Approach for Forecasting Thermal Energy Demand of Buildings

Recent developments in indirect predictive methods have yielded promising solutions for energy consumption modeling. The present study proposes and evaluates a novel integrated methodology for estimating the annual thermal energy demand (DAN), which is considered as an indicator of the heating and cooling loads of buildings. A multilayer perceptron (MLP) neural network is optimally trained by symbiotic organism search (SOS), which is among the strongest metaheuristic algorithms. Three benchmark algorithms, namely, political optimizer (PO), harmony search algorithm (HSA), and backtracking search algorithm (BSA) are likewise applied and compared with the SOS. The results indicate that (i) utilizing the properties of the building within an artificial intelligence framework gives a suitable prediction for the DAN indicator, (ii) with nearly 1% error and 99% correlation, the suggested MLP-SOS is capable of accurately learning and reproducing the nonlinear DAN pattern, and (iii) this model outperforms other models such as MLP-PO, MLP-HSA and MLP-BSA. The discovered solution is finally expressed in an explicit mathematical format for practical uses in the future.

Development of a realistic scenario for the thermal energy demand of residential buildings in Bavaria till 2050

To achieve the climate protection goals, enormous efforts must be undertaken in all sectors: households, industry, commerce, and transport. Following a straightforward approach, the political objectives foresee, that in the building sector a massive reduction of energy use for the heat supply is accomplished. However, previous investigations have shown that this reduction of energy consumption is not feasible. Older buildings exhibit especially high energy demand and emissions. Yet, due to the low refurbishment rate, no substantial change of the heat demand can be expected within the next decades. By fully renovating the entire residential building stock, approximately 70 % of the final energy demand and related CO2 emissions could be saved, still not enough to reach the political goals. Therefore, renovation or renewal of buildings and of the use of renewable energy sources have to be implemented jointly for achieving the desired savings.The methods used to estimate the characteristics of Bavaria’s residential building stock as well as its heating energy demand and related CO2 emissions for the year 2050 are presented. Alternative goals are given which base upon the achievable final energy saving for a realistic renovation scenario accompanied by further reduction of CO2 emissions by using renewable energies.

Experimental Evaluation of a Solar Low-Concentration Photovoltaic/Thermal System Combined with a Phase-Change Material Cooling Technique

The high operating temperatures of photovoltaic (PV) panels negatively affect both electrical efficiency and material degradation rate. Combining both a water-cooling-based photovoltaic/thermal (PV/T) system and a phase-change material (PCM) with/without low concentration (LC) represents a promising solution for boosting the overall energy conversion efficiency of the PV system. This approach needs to be evaluated in harsh weather where the PCM should have a high melting temperature. Therefore, this study experimentally investigates the performance of three PV cooling systems, namely PV-PCM, PV/T-PCM, and LCPV/T-PCM, compared to a reference PV without cooling, under the weather conditions of Riyadh. The results show that the PV/T-PCM attained the highest daily average electrical and overall efficiencies of 14.24% (5% increase) and 42.7%, respectively, compared to 13.56% electrical efficiency of the reference panel. The electrical efficiency of the PV-PCM was 13.64% due to inefficient natural cooling in the afternoon. The LCPV/T-PCM recorded the best performance during the two hours around noon, with an average increase in electrical power and efficiency of 11.06% and a maximum overall efficiency of 70%. Finally, the LCPV/T-PCM system can be only effectively used to support the higher demand for electricity and thermal energy around noon; otherwise, a new design configuration with low concentration is needed to establish a higher electrical efficiency in most hours of sunlight.

Wet Flue Gas Desulphurization (FGD) Wastewater Treatment Using Membrane Distillation

The use of waste incineration with energy recovery is a matured waste-to-energy (WtE) technology. Waste incineration can reduce the volume and mass of municipal solid waste significantly. However, the generation of high volumes of polluting flue gases is one of the major drawbacks of this technology. Acidic gases are constituents in the flue gas stream which are deemed detrimental to the environment. The wet flue gas desulphurization (FGD) method is widely employed to clean acidic gases from flue gas streams, due to its high efficiency. A major setback of the wet FGD technology is the production of wastewater, which must be treated before reuse or release into the environment. Treating the wastewater from the wet FGD presents challenges owing to the high level of contamination of heavy metals and other constituents. Membrane distillation (MD) offers several advantages in this regard, owing to the capture of low-grade heat to drive the process. In this study the wet FGD method is adopted for use in a proposed waste incineration plant located in Ghana. Through a mass and energy flow analysis it was found that MD was well matched to treat the 20 m3/h of wastewater generated during operation. Thermal performance of the MD system was assessed together with two parametric studies. The thermal efficiency, gained output ratio, and specific energy consumption for the optimized MD system simulated was found to be 64.9%, 2.34 and 966 kWh/m3, respectively, with a total thermal energy demand of 978.6 kW.

Integration of anaerobic digestion with heat Pump: Machine learning-based technical and environmental assessment

Anaerobic digestion (AD)-based biogas production mitigates the environmental footprint of organic wastes (e.g., food waste and sewage sludge) and facilitates a circular economy. The work proposed an integrated system where the thermal energy demand of an AD is supplied using an air source heat pump (ASHP). The proposed system is compared to a baseline system, where the thermal energy is supplied by a natural gas-based heating system. Several machine learning models are developed for predicting biogas production, among which the Gaussian Process Regression (GPR) showed a superior performance (R2 = 0.84 and RMSE = 0.0755 L gVS−1 day−1). The GPR model further informed a thermodynamic model of the ASHP, which revealed the maximum biogas yield to be approximately 0.585 L.gVS−1.day−1 at an optimal temperature of 55 °C (thermophilic). Subsequently, life cycle assessment showed that ASHP-based AD heating systems achieved 28.1 % (thermophilic) and 36.8 % (mesophilic) carbon abatement than the baseline system.

Thermal performance improvement of thermal energy storage systems by employing a contrastive experiment

The thermal storage system is widely used to reduce the mismatch between thermal energy supply and demand in time and space, and its thermal performance is a critical factor in the system's thermal efficiency. The thermal performance of the Sensible Thermal Energy Storage Unit (STESU), the Latent Thermal Energy Storage Unit (LTESU), and the LTESU integrated with Copper Foam Fin (CFF) were compared through comparative experiments. The experimental results showed that the thermal changing rate of STESU was higher than that of other units, and there was no apparent thermal stratification. However, LTESU had the lowest thermal changing rate with apparent thermal stratification. During the thermal charging process, the solid-liquid interface on the LTESU cross-section formed an inverted-triangle shape. The lower part of the PCM could not change its phase as a dead zone and failed to participate in the thermal charging and discharging. Even so, the thermal efficiency of LTESU was 18.7% higher than that of STESU. Integrating with CFF could increase the thermal charging capacity, the thermal discharging capacity and the thermal efficiency by 51.1%, 55.9% and 10.8%, respectively.

Highly thermally conductive composite phase-change materials doped with two-dimensional heterogeneous nanohybrids for photo/electro-thermal energy storage

Phase-change thermal storage technology can solve the problem of mismatch between supply and demand of thermal energy. In this study, a meso-erythritol/two-dimensional heterogeneous nanohybrids/expanded graphite (mE/2DHN/EG) composite phase-change material (PCM) was prepared using hydrothermal and molding methods. The experimental results show that the mE/2DHN/EG composite PCM has excellent thermal, photo-thermal conversion, and electro-thermal conversion properties. The thermal conductivity of mE/2DHN/EG is as high as 12.36 W m−1 K−1, which is 17.31 times that of pure mE. In addition, the photo-thermal conversion efficiency of mE/2DHN/EG can reach 75.72 % under the action of 2DHN and can convert a low driving voltage (2.08 V) into medium-high temperature heat (>130 °C) with an efficiency of 70.07 %. This study provides a cost-effective way to manage the photo/electro-thermal response of PCMs.

Decarbonization of the heating sector from a system point of view: the case study of the Lombardy Region.

This work aims at defining the optimal technological mix which minimizes the total cost of the energy system in 2030 in the Lombardy region, in northern Italy. The goal is reached through a bottom-up model built on a linear optimization problem considering different technical and economic inputs and constraints. Civil sector is one of the sectors to focus on for the decarbonization process. Different areas, types of buildings and thermal systems are included in the model to consider the peculiarities of the available solutions in each context. The overall technological mix is constraint by a CO2 emission limit. For the civil sector the more the emission is constrained, the higher is the penetrations of electric heat pumps, coupled with envelope retrofit, (10% of the total thermal energy demand) and of district heating (18%), while natural gas boilers decrease (66%). Biomass boilers reach a maximum penetration of 29% in mountain areas. District heating is relevant in areas with available sources (max 29%). Natural gas boilers coupled with air conditioners have an important role and they reach a maximum penetration of 89% in certain areas. Electric heat pumps are quite homogeneous through the areas for residential buildings.

Process analysis for the simultaneous production of aromatics and syngas from shale gas and CO2

The production of benzene, toluene, and xylene (BTX) from shale-derived CH4, C2H6, and C3H8 is considered a promising alternative to their fossil-based counterparts. Herein, we evaluate a production technology for aromatics and hydrogen with non-oxidative and CO2 co-feeding reactions to predict the economics and environmental impact of each process. The optimal process for producing aromatics and hydrogen varies depending on the presence or absence of CO2, and we experimentally confirm the difference in the reaction systems. The operating conditions of both processes are optimized using an experiment-based surrogate model in terms of thermal energy demand and profit of products, which account for the highest portion of BTX production cost. Particularly, the CO2 emissions and economic feasibility of the proposed BTX production processes are compared with those of an ethane cracking center using shale gas and the naphtha reforming/Cyclar process to produce BTX. In the CO2 co-feeding case, the CO2 reduction effect is proven compared to other processes, and the economics was improved by the sale of H2 and CO compared to the non-oxidative BTX production. Furthermore, the BTX production cost reflecting the carbon price is comparable to that of commercial processes; as the carbon price increases, the economics has the potential to outperform existing processes. These findings present a platform for economic evaluation based on CO2 emissions as well as the economic benefits of processes that reduce CO2 emissions for energy-efficient conversion of shale gas into high value-added products.