Prediction of metabolic status of dairy cows in early lactation with on-farm cow data and machine learning algorithms

Metabolic status of dairy cows in early lactation can be evaluated using the concentrations of plasma β-hydroxybutyrate (BHB), free fatty acids (FFA), glucose, insulin, and insulin-like growth factor 1 (IGF-1). These plasma metabolites and metabolic hormones, however, are difficult to measure on farm. Instead, easily obtained on-farm cow data, such as milk production traits, have the potential to predict metabolic status. Here we aimed (1) to investigate whether metabolic status of individual cows in early lactation could be clustered based on their plasma values and (2) to evaluate machine learning algorithms to predict metabolic status using on-farm cow data. Through lactation wk 1 to 7, plasma metabolites and metabolic hormones of 334 cows were measured weekly and used to cluster each cow into 1 of 3 clusters per week. The cluster with the greatest plasma BHB and FFA and the lowest plasma glucose, insulin, and IGF-1 was defined as poor metabolic status; the cluster with the lowest plasma BHB and FFA and the greatest plasma glucose, insulin, and IGF-1 was defined as good metabolic status; and the intermediate cluster was defined as average metabolic status. Most dairy cows were classified as having average or good metabolic status, and a limited number of cows had poor metabolic status (10–50 cows per lactation week). On-farm cow data, including dry period length, parity, milk production traits, and body weight, were used to predict good or average metabolic status with 8 machine learning algorithms. Random Forest (error rate ranging from 12.4 to 22.6%) and Support Vector Machine (SVM; error rate ranging from 12.4 to 20.9%) were the top 2 best-performing algorithms to predict metabolic status using on-farm cow data. Random Forest had a higher sensitivity (range: 67.8–82.9% during wk 1 to 7) and negative predictive value (range: 89.5–93.8%) but lower specificity (range: 76.7–88.5%) and positive predictive value (range: 58.1–78.4%) than SVM. In Random Forest, milk yield, fat yield, protein percentage, and lactose yield had important roles in prediction, but their rank of importance differed across lactation weeks. In conclusion, dairy cows could be clustered for metabolic status based on plasma metabolites and metabolic hormones. Moreover, on-farm cow data can predict cows in good or average metabolic status, with Random Forest and SVM performing best of all algorithms.     

Performance investigation of the heat pump and power generation integration system

A novel heat pump and power generation integration system (HPPGIS) using solar energy as a low temperature heat source was presented in this study. This system could be operated in both an organic Rankine cycle power generation (ORC‐PG) mode and a reverse Carnot cycle heat pump (RCC‐HP) mode. Compared with a single heat pump and power generation system, this system improved the utilization efficiency of solar energy, thus showing potential for the generation of economic benefits. Contrastive analyses of different working fluids using ORC‐PG and RCC‐HP systems were conducted first, leading to the selection of R142b and R245fa as optimal fluids. Then, an experimental investigation of the system was carried out under different conditions. A heat pump and ORC system model was proposed and validated by comparing experimental and simulated values. The experimental results indicated that the HPPGIS had good feasibility and stability in both modes. In the ORC‐PG mode, HPPGIS had a power output of 1.29 kW and a thermal efficiency of 4.71% when the water inlet temperature of the evaporator was 90.03°C. In the RCC‐HP mode, HPPGIS had a COP of 3.16 and a heat capacity of 33.24 kW when the water outlet temperature of the condenser was 106.23°C.     

Process design and techno‐economic analysis of ethyl levulinate production from carbon dioxide and 1,4‐butanediol as an alternative biofuel and fuel additive

Carbon dioxide capture, utilization, and storage (CCUS) is one of the promising negative emission technologies (NET). Within various CCUS routes available, CO₂ conversion into fuels is one of the attractive options. Currently, most of CO₂ conversion into fuels requires hydrogen, which is expensive and consume large energy to produce. Hence, a different route of producing fuel from CO₂ by utilizing 1,4‐butanediol as the raw material is proposed and evaluated in this study. This alternative route comprises production of levulinic acid from the reaction between CO₂ and 1,4‐butanediol and production of ethyl levulinate, an alternative biofuel and biofuel additive, via an esterification reaction of levulinic acid with ethanol. The process is designed and simulated according to the available data and evaluated in terms of its technical features. Because of the unavailability of reaction data for synthesis of levulinic acid from 1,4‐butanediol and CO₂, several assumptions were taken, which may implicate the accuracy of the studied design. This technical evaluation is followed by cost estimations and sensitivity analysis. Because of the free CO₂, the profitability of the plant depends strongly on the prices of the other chemicals and the price difference between 1,4‐butanediol (raw material) and ethyl levulinate (product). Monte Carlo simulation indicates that the proposed plant will always be profitable if the ethyl levulinate is slightly more expensive than the 1,4‐butanediol, highlighting that the process of producing ethyl levulinate from CO₂ is economically profitable. Future research should be directed towards a catalytic system that can effectively convert CO₂ into levulinic acid, by‐products produced from the two reaction steps, and reduce the excess ethanol used in the second reaction.     

Optimizing 100%‐renewable grids through shifting residential water‐heater load

A low‐carbon electricity supply for Australia was simulated, and the installed capacity of the electrical grid was optimized by shifting the electricity demand of residential electric water heaters (EWHs). The load‐shifting potential of Australia was estimated for each hour of the simulation period using a nationwide aggregate EWH load model on a 90 × 110 raster grid. The electricity demand of water heaters was shifted from periods of low renewable resource and high demand to periods of high renewable resource and low demand, enabling us to effectively reduce the installed capacity requirements of a 100%‐renewable electricity grid. It was found that by shifting the EWH load by just 1 hour, the electricity demand of Australia could be met using purely renewable electricity at an installed capacity of 145 GW with a capacity factor of 30%, an electricity spillage of 20%, and a generation cost of 15.2 ¢/kWh. A breakdown of the primary energy sources used in our scenario is as follows: 43% wind, 29% concentrated solar thermal power, and 20% utility photovoltaic. Sensitivity analysis suggested that further reduction in installed capacity is possible by increasing the load‐shifting duration as well as the volume and insulation level of the EWH tank.     

Experimental and numerical analysis of seasonal solar‐energy storage in buildings

This paper presents seasonal‐energy storage of solar energy for the heating of buildings. We distinguish several types of seasonal storage, such as latent, sensible, and chemical storage, among which the thermochemical storage is used and analysed in this research. In the first part, a laboratory heat‐storage tank, which was made in the laboratory for heating, sanitary, and solar technology and air conditioning from the Faculty of Mechanical Engineering, University of Ljubljana, Slovenia, was presented. The experimental model was tested for charging and discharging mode. Two types of numerical models for sorption thermal‐energy storage exist, which are microscale and macroscale (integral). For microscale analysis, the analysis system (ANSYS) model can be used to simulate the behaviour in the adsorption reactor. On macroscale or integral scale, TRaNsient SYStem (TRNSYS) model was used to perform the operation of the storages on the yearly basis. In the second part the simulation of the underfloor heating system operation with a built‐in storage tank was carried out for two locations, Ljubljana and Portoro?. Furthermore, the comparison between a thermochemical and sensible‐heat storage was performed with TRNSYS and Excel software. In this comparison, the focus was on the surface parameters of the SCs and volume of the thermal‐storage tank for the coverage of the energy demand for selected building. With this analysis, we would like to show the advantage of the thermochemical storage system, to provide greater coverage of the energy demand for the operation of the building, compared with the seasonal sensible‐heat storage (SSHS). Such a heat‐storage technology could, in the future, be a key contributor to the more environmentally friendly and more sustainable way of delivering energy needs for buildings.     

Experimental investigation on the effect of MgO and TiO2 nanoparticles in stepped solar still

This work aims at augmenting the amount of potable water using MgO and TiO₂ in stepped solar still. Experiments were carried out for the climatic conditions of Chennai, India, with two different concentrations of nanofluids inside a stepped basin under three different cases. Results show that there is an improvement in yield of fresh water from stepped solar still by 33.18% and 41.05% using 0.1% and 0.2% volume concentration of TiO₂ nanofluid, respectively, whereas the freshwater yield from stepped still with MgO nanofluids improved by 51.7% and 61.89%. Furthermore, the economic analysis revealed that the cost of potable water from the modified solar still reduced from 0.029 to 0.016 $/kg. Similarly, the useful annual energy, yearly cost per kilogram, and annual cost per kilowatt hour are significantly profitable with the use of MgO nanofluid in the stepped basin and found as 512.46 kWh, 0.025 $/kg, and 0.026 $/kWh, respectively. It is also found that the cost of potable water from the modified still significantly increases as the amount of fresh water produced is decreased with increased fabrication cost of the solar still.     

Sustainability accounting for the construction and operation of a plant‐scale solar‐biogas heating system based on emergy analysis

Domestic heating systems have long been playing a significant role in China's energy structure. The sustainability of a hybrid solar‐biogas heating system (SBHS) under various feedstock fermentation scenarios was evaluated using emergy analysis. Representative emergy indices such as transformities, emergy yield ratio (EYR), environmental loading ratio (ELR), emergy sustainability index (ESI), ratio of waste treatment (%W), feedback yield ratio (FYR), and emission mitigation intensity (EMI; g/10¹⁰ sej) were selected to evaluate the sustainability performance of different feedstock scenarios including cow dung (CD), swine manure (SM), and poultry manure (PM). The results showed that PM fermentation scenario had greater market competitiveness, lower environmental pressure, better sustainability, and self‐organizing ability than the other two options. However, both the emergy efficiency and the CO₂ emissions mitigation intensity of PM scenario were worse than that of the SM and CD. Moreover, compared with other biogas systems and traditional agricultural systems, the hybrid SBHS was proved to be a promising mode for the treatment of rural manure waste with favorable economic benefits and environmental sustainability.     

Heat transfer analysis of receiver for large aperture parabolic trough solar collector

Parabolic trough solar collector (PTSC) is one of the most proven technologies for large‐scale solar thermal power generation. Currently, the cost of power generation from PTSC is expensive as compared with conventional power generation. The capital/power generation cost can be reduced by increasing aperture sizes of the collector. However, increase in aperture of the collector leads to higher heat flux on the absorber surface and results in higher thermal gradient. Hence, the analysis of heat distribution from the absorber to heat transfer fluid (HTF) and within the absorber is essential to identify the possibilities of failure of the receiver. In this article, extensive heat transfer analysis (HTA) of the receiver is performed for various aperture diameter of a PTSC using commercially available computational fluid dynamics (CFD) software ANSYS Fluent 19.0. The numerical simulations of the receiver are performed to analyze the temperature distribution around the circumference of the absorber tube as well as along the length of tube, the rate of heat transfer from the absorber tube to the HTF, and heat losses from the receiver for various geometric and operating conditions such as collector aperture diameter, mass flow rate, heat loss coefficient (HLC), HTF, and its inlet temperature. It is observed that temperature gradient around the circumference of the absorber and heat losses from the receiver increases with collector aperture. The temperature gradient around the circumference of the absorber tube wall at 2 m length from the inlet are observed as 11, 37, 48, 74, and 129 K, respectively, for 2.5‐, 5‐, 5.77‐, 7.5‐, and 10‐m aperture diameter of PTSC at mass flow rate of 1.25 kg/s and inlet temperature of 300 K for therminol oil as HTF. To minimize the thermal gradient around the absorber circumference, HTFs with better heat transfer characteristics are explored such as molten salt, liquid sodium, and NaK78. Liquid sodium offers a significant reduction in temperature gradient as compared of other HTFs for all the aperture sizes of the collector. It is found that the temperature gradient around the circumference of the absorber tube wall at a length of 2 m is reduced to 4, 8, 10, 13, and 18 K, respectively, for the above‐mentioned mass flow rate with liquid sodium as HTF. The analyses are also performed for different HTF inlet temperature in order to study the behavior of the receiver. Based on the HTA, it is desired to have larger aperture parabolic trough collector to generate higher temperature from the solar field and reduce the capital cost. To achieve higher temperature and better performance of the receiver, HTF with good thermophysical properties may be preferable to minimize the heat losses and thermal gradient around the circumference of the absorber tube.     

Hybrid solar parabolic dish power plant and high‐temperature phase change material energy storage system

In this study, a conventional steam power plant with two regenerative boilers is considered, and one of its boilers is replaced with parabolic solar dish collectors and storing the produced thermal energy by the phase change material (PCM) in a storage tank. The results show the necessity of the existence of an auxiliary fired‐gas boiler to provide constant load during the whole 24 hours. The performance of the proposed hybridized system is evaluated through energy and exergy analyses. It was demonstrated that substituting solar collectors with one of the boilers marginally lowers the energy efficiency but increases the exergy efficiency of the whole power plant up to 41.76%. Moreover, it is found out that this hybridization decreases the total irreversibility of the power plant in comparison with the base case, from 51.1 to 47.2 MW. The parametric analysis states that raising the mass flow rate of the heat transfer fluid in the solar collectors not only enhances the system performance but also increases the volume of the PCM tank.