Sustainability and carbon neutrality in UK's district heating: A review and analysis

The UK is currently approaching a critical point in the fight against climate change. To achieve carbon neutral by 2050, it is crucial that the way in which buildings are heated are reviewed to determine the most suitable solution. The UK government has acknowledged that district heating (also referred to as heat networks) forms an important part of their plan for future sustainability in heating homes as well as improving energy costs. At present, there are five generations of district heating with distinctive improvements between each. However, research shows a lack of progression with only minor improvements to efficiencies and carbon emissions in the past two decades. Therefore, this paper aimed to review the key technologies and design principles of the low-impact network which shall be implemented into future networks to ensure sustainability and carbon neutral. Furthermore, data were utilised from UK government's ‘Heat Network Project Pipeline’ documents which cover a wide range of projects supported through the development stage by the UK Heat Network Delivery Unit. A statistical analysis was also undertaken to identify popular heat source technologies currently being implemented into the UK networks. Information such as technologies, size and costs were analysed to establish the intercorrelations, which may influence the type of technologies being selected. The results show that 56% of total networks contained Combined Heat and Power (CHP) as a primary heat source, of which over 40% were gas fired CHP, displaying the current dominance of the technology. Overall, it is evident in the UK that, the new networks have been improved from previous generations with a high concentration of renewable energy technologies and heat recovery methods being used. However, there is still a high reliance on natural gas, which does not fulfil the characteristics of a low-impact heating network

An Experimental Case Study for the Course of ‘Testing Technology and Data Processing’

‘Testing Technology and Data Processing (TTDP)’ is one of the core courses for the undergraduates in mechanical engineering subject. This paper designs an experimental case to improve the students’ abilities in signal acquisition, preprocessing, feature extraction, and artificial intelligence (AI)-based pattern recognition. The case study is based on an internet of things (IoT) node that integrating with accelerometer, microphone, and magnetic sensors. The order tracking algorithm and a double-layer bidirectional long short-term memory (DBiLSTM) model are used to process the multi-sensor data for condition monitoring and fault diagnosis of a motor. The students’ feedback demonstrates that the designed case improves their interests to this course, and also improves their abilities in engineering practice

Consumer-feeder relationship identification method for low-voltage distribution station area considering feature fusion of voltage variation and spatial distribution

Consumer-feeder relationship is an important basis for the fault location, outage management, load adjustment and power quality management in low-voltage distribution station area (LVDSA). The current identification method of the consumer-feeder relationship based on electrical characteristics analysis is single and lack of reliability. Besides, the consumers of different feeders which locate near the bus at the low voltage side of distribution transformer have high voltage variation similarity, which makes it difficult to distinguish reliably. The spatial distribution of consumers can directly reflects the feeder trend. Therefore, a consumer-feeder relationship identification method for LVDSA considering feature fusion of voltage variation and spatial distribution is proposed in this paper. Firstly, the electrical characteristics based on voltage variation and spatial distribution characteristics based on geographical location are analyzed, and the correlation between the characteristics above and consumer-feeder relationship is explained. Secondly, a semi-supervised spectral clustering (SSC) algorithm based on the feature of voltage variation and spatial distribution is proposed to identify the consumer-feeder relationship. Finally, the proposed method is tested with the real data of LVDSAs in China. The results indicate that the feature fusion of voltage variation and spatial distribution can effectively improve the identification accuracy of consumer-feeder relationship

Theoretical line loss calculation method for low-voltage distribution network via matrix completion and ReliefF-CNN

Line loss is directly responsible for the management profitability of the grid company. The traditional method of calculating the theoretical line loss for Low Voltage Distribution Networks (LVDN) necessitates more electrical parameters. which cannot be obtained easily. Besides, due to the backward communication conditions of LVDN, the problem of smart meter data missing is significant, which poses a challenge to an exact theoretical line loss calculation. In an attempt to solve the issues above, a theoretical line loss computation approach via matrix completion and ReliefF-convolutional neural network (CNN) for LVDN is proposed. Firstly, a feature weighting algorithm based on ReliefF is presented to analyze the relevance of the electrical parameters, which can be obtained easily. Secondly, a theoretical line loss calculation method is proposed for CNN-based. In the view of the data missing problem, a matrix completion method based on singular value thresholding (SVT) is introduced to obtain the high-precision data, in order to enhance the calculation accuracy of the theoretical line loss calculation. Finally, the proposed method is tested on the data sample of 789 LVDNs. The results show that comparing with CNN, back-propagation and other methods, the mean absolute percentage error (MAPE) of the presented method can reduce by more than 90%. When data missing, the MAPE of the proposed method can reduce by more than 95% compared with the method without considering the data completion

The elemental uphill diffusion with micropores reduction during HIP treatment for a solution-treated nickel-based superalloy

Micropores and elemental segregation are detrimental to the high-temperature properties of nickel-based single-crystal (SX) superalloys and hot isostatic pressing (HIP) treatment has been considered as an appropriate method to reduce micropores and elemental segregation. In this study, the effect of a two-step HIP treatment on the solution-treated nickel-based SX superalloy was investigated. An elemental uphill diffusion with the micropores reduction was discovered during HIP treatment and caused the elemental segregation of Al, Cr and Ta at the dendritic scale. It indicates that the HIP treatment is not always beneficial for alloy homogenization. The results show that the first-step HIP treatment could promote the uphill diffusion and cause the elemental segregation with the significant micropores reduction. The second-step HIP treatment could decrease the elemental segregation with further micropores reduction. During subsequent heat treatments, the elemental segregation caused by HIP treatment could be basically eliminated with a slight increase of micropores. During HIP treatment, the micropores reduction and elemental segregation were correlated with the HIP temperature and pressure. This study will provide the supports for controlling micropores and homogenization of nickel-based SX superalloys

Development and Adsorption Characterization of Metal Affinity-Immobilized Magnetic Liposome

A metal affinity-immobilized magnetic liposome (MA-IML) was prepared in this research, which was with lipid and Ni2+ content of 143.25 μg/mg and 32 μmol/mg, respectively. The antihypertensive peptides Ile-Pro-Pro (IPP) and Val-Pro-Pro (VPP) could be adsorbed onto MA-IML under specific conditions, and the adsorption kinetics was explored. The pseudo-second-order kinetics (R2 value>0.98) was more suitable to describe the adsorption process of IPP and VPP than the intraparticle diffusion model and pseudo-first-order kinetic model. The results indicated that MA-IML could be used as an adsorbent for screening antihypertensive peptides from natural products

In Situ Investigation of the Phase Transition at the Surface of Thermoelectric PbTe with van der Waals Control

The structure of thermoelectric materials largely determines the thermoelectric characteristics. Hence, a better understanding of the details of the structural transformation process/conditions can open doors for new applications. In this study, the structural transformation of PbTe (a typical thermoelectric material) is studied at the atomic scale, and both nucleation and growth are analyzed. We found that the phase transition mainly occurs at the surface of the material, and it is mainly determined by the surface energy and the degree of freedom the atoms have. After exposure to an electron beam and high temperature, high-density crystal-nuclei appear on the surface, which continue to grow into large particles. The particle formation is consistent with the known oriented-attachment growth mode. In addition, the geometric structure changes during the transformation process. The growth of nanoparticles is largely determined by the van der Waals force, due to which adjacent particles gradually move closer. During this movement, as the relative position of the particles changes, the direction of the interaction force changes too, which causes the particles to rotate by a certain angle

Chronic Heat Stress Induces Oxidative Stress and Induces Inflammatory Injury in Broiler Spleen via TLRs/MyD88/NF-κB Signaling Pathway in Broilers

The spleen is the largest peripheral immune organ of the organism, accounting for 25% of the total lymphoid tissue of the body. During HS, the spleen is damaged due to the elevated environment, which seriously affects life performance and broilers’ health. This study aimed to investigate the mechanism of chronic HS damage to broiler spleen tissues. The broilers were typically raised until they reached 21 days of age, after which they were arbitrarily allocated into two groups: an HS group and a cntrol group. The HS group was subjected to a temperature of 35 °C for 10 h each day, starting at 21 days of age. At 35 and 42 days of age, spleen and serum samples were obtained from the broilers. The results showed that after HS, a significant decrease in productive performance was observed at 42 days of age (p p p p p < 0.01). HS also led to a significant increase in cytokines IL-6, TNF-α, and INF-γ and a significant decrease in IL-4 in the spleen. The histopathologic results showed that the spleen’s red-white medulla was poorly demarcated. The cells were sparsely arranged after HS. After HS, the expression of TLRs, MYD88, and NF-κB genes increased significantly. The expression of HSP70 increased significantly, suggesting that HS may induces an inflammatory response in broiler spleens through this signaling pathway, which may cause pathological damage to broiler spleens, leading to a decrease in immune function and progressively aggravating HS-induced damage with the prolongation of HS