Energy Equipment Research Articles

ENERGY AUDIT AT HEAT POWER STATIONS IN SERVICE

This article explains the necessity of complex energy audit as an alternative for another approaches to their technical and economical indicators improvement. By authors estimation, latest 20 years there weren’t nor new facility launches neither research on existing ones (at least open public). The article proves that using limited financial resources for facilities modernization, external complex examination (audit) is systematized, controlled and profitable way to prolong energy equipment use or to justify its’ replacement. While any regulation rules for HES energy audit services are absent, such activities’ reliability straightly depend on customers’ and executants’ mutual clarity. Further there are requirements for HES energy audit Customers and Executants defined as far as general methodology approaches and typical energy audit (chronological) order. Also the article suggests that success of Ukrainian HES modernization strongly depends on sectoral-level energy business clarity and demonopolization.

Make your home carbon-free. An open access planning tool to calculate energy-related carbon emissions in districts and dwellings

Reducing the carbon emissions of buildings and whole districts is one of the main objectives of sustainable development goals. Both policymakers and end-users need reliable information to take actions that lead to achieving those goals. For this, an innovative open access planning tool has been developed to assess the effect of energy consumption on the overall carbon emissions of districts, buildings, and house units. When it comes to the end-users, it would help them know the actual environmental impact of their homes and make environmentally and financially sound decisions before investing in new equipment. The tool is meant to be an online planning service for dwelling end-users and policymakers alike; thus responding to a still unresolved demand. For this, firstly, the study focuses on the obtention of a complete catalogue of open-source conversion factors, which convert the different energy sources to carbon dioxide emissions per unit of energy. Secondly, it presents two case studies to illustrate the use of the tool. The first case study explains how an end-user could estimate the energy savings that may result from changing his domestic energy habits, equipment, and sources. The second case study uses actual data from a district in Valencia (Spain) to show how renewable sources would affect the carbon footprint of an apartment block. Both study cases show greenhouse gas emissions savings by replacing the existing equipment with more efficient ones such as heat pumps or renewable energy-based power systems like photovoltaic panels. This study concludes that providing smart tools is pivotal to planning nearly Zero-Energy Districts (nZED).

The diaphragm coupling in energy equipment: A review

With the rapid development of high-speed rotating machinery, diaphragm couplings are widely used in energy equipment such as compressors, generators, drilling equipment, and turbine drives by virtue of their high sensitivity, oil resistance and corrosion resistance. However, the theoretical research of this product mainly focuses on the design of diaphragm profile, the combination form between diaphragms, the overall structural form of diaphragm coupling and the axial dynamic characteristics of diaphragm coupling. Therefore, this paper analyzes and summarizes the current research status of diaphragm couplings in the world, and puts forward the problems that need to be solved in the field of diaphragm coupling research, and proposes a new direction for the subsequent research.

Study on Cutting Performance of Micro Groove Tool in Turning AISI 304 and Surface Quality of the Workpiece

AISI 304 has high-tensile strength and excellent corrosion resistance, which is widely needed in the energy industry and equipment manufacturing industry. However, the tools for cutting AISI 304 are easy to wear and have short service life. In order to improve tool life, micro grooves are designed on the rake face of the tool for the machining of AISI 304. Through the single factor cutting experiment, it is found that under the same cutting parameters, the micro groove tool has less cutting depth resistance than the initial tool; the main cutting force and feed resistance are reduced by more than 15%. The shear energy is reduced by more than 13%; the surface roughness and the hardening degree of the workpieces are reduced. Through the durability test, it is found that the service life of the micro groove tool is 57% longer than that of the initial tool, and the abrasive wear, bonding wear, and oxidation wear of the tool are significantly less. Through cutting experiments and theoretical analysis, the cutting performance of the micro groove tool has been improved.

Comprehensive Planning of Laboratory Equipment Based on Genetic Algorithms.

Laboratory equipment planning is a very important task in modern enterprise management. Laboratory equipment planning by computer algorithm is a very complex NP-hard combinatorial optimization problem, so it is impossible to find an accurate algorithm in polynomial time. In this study, an improved genetic algorithm is used to solve and analyze the comprehensive planning of laboratory equipment. After analyzing the traditional heuristic algorithm and genetic algorithm to solve the simple laboratory equipment planning problem, the simple laboratory equipment planning is designed and implemented according to the principle of the heuristic algorithm. Finally, the algorithm is implemented in Python. A general equipment planning based on genetic algorithm with two selection operators is realized. Two constraints of test start and completion time are given. In the scenario of using multiple test equipment for a test project, the possible solutions of laboratory equipment planning under given constraints are analyzed. The efficiency coefficient is not necessarily a constant, it is related to the output characteristics of energy equipment. Three independent planning algorithms are used to solve the actual test requirements. One is the planning method based on manual test scheduling in the test cycle of experimental instruments, the other is the genetic algorithm for gene location crossover operator, and the third is the genetic algorithm for experimental part crossover operator. The planning solutions obtained by the three algorithms are compared from three aspects: the shortest time to complete the test, the calculation time of the algorithm, and the utilization of the test equipment.

Ultra-thin carbon fiber reinforced carbon nanotubes modified epoxy composites with superior mechanical and electrical properties for the aerospace field

The ultra-thinning of large tow carbon fiber (CF) is a trend to promote the industrialization of CF-reinforced polymer (CFRP) composite materials. However, pristine epoxy resins cannot meet the demands of high-performance composites. The effect of carbon nanotube (CNTs) reinforced epoxy resin on ultra-thin CFRP composites was explored. It was found that the epoxy resin matrix had the highest compressive strength, bending strength, bending modulus, and tensile strength when the CNTs content was 0.2 wt%. Most importantly, the transverse fiber bundle test tensile strength, interlaminar shear strength, and compressive strength of ultra-thin CF reinforced modified epoxy composites have been significantly improved. In addition, the composite exhibits excellent thermal conductivity, electrical, and electromagnetic interference shielding effectiveness. This work provided insights into preparing structural–functional integrated ultra-thin CFRP composites, which showed potential applications in the fields of aerospace, and energy equipment, among others.

Evaluating the Growth of Ceria-Modified N-Doped Carbon-Based Materials and Their Performance in the Oxygen Reduction Reaction.

Owning to their distinctive electronic structure, rare-earth-based catalysts exhibit good performance in the oxygen reduction reaction (ORR) and can replace commercial Pt/C. In this study, CeO2-modified N-doped C-based materials were synthesized using salt template and high-temperature calcination methods, and the synthesis conditions were optimized. The successful synthesis of CeO2–CN–800 was confirmed through a series of characterization methods and electrochemical tests. The test results show that the material has the peak onset potential of 0.90 V and the half-wave potential of 0.84 V, and has good durability and methanol resistance. The material demonstrates good ORR catalytic performance and can be used in Zn–air batteries. Moreover, it is an excellent catalyst for new energy equipment.

Integrated optimization of a regional integrated energy system with thermal energy storage considering both resilience and reliability

The regional integrated energy system (RIES) is widely adopted from the viewpoints of energy saving, emissions reduction and resilience enhancement. Especially, in case of external energy supply interruption caused by extreme events, a RIES can survive and ensure energy supply by multi-energy coupling and reserve capacity. Moreover, the resilience and reliability of a RIES can be further enhanced by employing energy storage equipment. In this study, an integrated optimization framework has been proposed for a RIES including thermal energy storage accounting for both resilience and reliability. Firstly, a rolling optimization model is developed to calculate the minimum capacity of backup thermal energy storage at each time. Following which, the day-ahead economic scheduling is carried out based on the constraint of backup energy. The Monte Carlo method based on the Markov process is used to simulate the system reliability. The reliability model can also reflect the increase of operation costs caused by backup thermal energy. As an illustrative example, a regional energy system located in Shanghai, China has been selected for analysis. According to the simulation results, the backup thermal energy storage improves both resilience and reliability of the RIES system, and ensures the load supply in case of external energy interruption or equipment failure. There are nine load-shedding periods with improved energy satisfaction rate under external energy interruptions in summer and five in winter. Furthermore, under 10,000 days of operation simulation, the supply interruptions due to equipment failure decrease from 47 to 15 in summer and 22 to 4 in winter.

ZIF-derived twisted wedge-shaped CoS2/NC nanoporous architectures pinned to graphene foam as negative electrode for lithium and sodium-ion batteries

• A novel wedge-shaped CoS 2 /NC@NPG nanoporous structure is developed. • The waved wrinkles on porous carbon framework facilitate ion transmission. • ZIF-L and N -doped porous graphene construct 3D conductive network. • The composite exhibits remarkable rate performance for LIBs/SIBs. To explore more efficient ways to deal with deteriorating environmental problems, lithium-ion and sodium-ion batteries are expected to serve as advanced energy storage equipment for green energy. Herein, ZIF-L derived CoS 2 with N‑doped porous carbon framework carried by three-dimensional (3D) N -doped porous graphene (CoS 2 /NC@NPG) is prepared by a facile method in deionized water, followed by carbonization and vulcanization. The composite delivers remarkable rate performance as negative electrode for lithium-ion batteries (527 mAh/g at 10 A/g) and sodium-ion batteries (386 mAh/g at 10 A/g). The excellent performance is mainly ascribed to the abundant wrinkles with active sites on the rough surface of twisted wedge-shaped carbon frame, which is related with excellent rate capability. The porous carbon framework derived from ZIF-L and NPG supporter provides fast ion channels and improved conductivity. The carbon coating where CoS 2 uniformly distributed in can accommodate the volume expansion during the cycling, thereby boosting the capacity storage and cyclic stability. This work would provide an efficient and concise approach for designing three-dimensional porous structure and self-supporting complex combining transition metal sulfides and carbon matrix for serving as advanced energy storage material.

Building resilience to handle disruptions in critical environmental and energy sectors: Implications for cleaner production in the oil and gas industry

Even before the outbreak of the COVID-19 pandemic, the oil and gas (O&G) industry had been facing disruptions in terms of an energy transition phase that include the focus on the use of renewable energy equipment , transport electrification , decarbonization, and waste elimination among others. However, the contraction in global travel and remote working habits owing to the pandemic really set off disruptions for the O&G industry. This research intends to identify and analyze the enablers for the O&G industry that can help it handle potential disruptions and hence become resilient. Several significant enablers have been identified through a systematic literature review using the PRISMA approach and Delphi method. The mutual inter-relationships among the enablers have been developed using the modified total interpretive structural modelling approach. Later, the matrice d'impacts crois es multiplication appliques an un classement analysis has been used to identify the enablers' clusters according to their dependence and driving powers. The modelling and analysis results suggest four paths for the O&G industry to handle disruptions effectively. This research aims to help academicians, managers, and researchers understand the essential enablers and paths to adopt on a priority basis so as to handle disruptions and build resilience in the O&G industry.

Binary Newton Calculation Method of Residual Stress Based on the Indentation Energy Difference Theory

Residual stress is a key parameter to evaluate the structural reliability of energy equipment. The indentation method has the characteristics of being nondestructive and easy to operate to calculate the residual stress of test materials, which has a broad application prospect in the field testing of energy equipment. However, because of the effect of preloading and data acquisition delay, the problem of indentation data fluctuation is prominent, and the indentation energy coefficient fitted by the traditional least square method is not consistent with the theoretical law, making it difficult to carry out stable calculations. In this paper, the Newton iteration formula of a binary nonlinear formula is derived based on the univariate Newton iteration formula, which is introduced into the data processing of residual stress, which increases the weight of the data in the stability stage and reduces the influence of the fluctuation data on the fitting results, so that the indentation energy coefficient is accurately calculated. Combined with the basic principle of indentation energy difference theory, the precise and efficient measurement of residual stress is realized.

Synthetic thermal convolutional‐memory network for the lithium‐ion battery behaviour diagnosis against noise interruptions

AbstractIn order to meet the two global challenges of energy shortage and environmental pollution, various countries have begun to advocate the application of new energy equipment such as electric vehicles. This has also promoted the development of energy storage equipment and energy storage systems. With their high performance, lithium‐ion batteries are used in a wide range of electrical equipment. But the safety of lithium‐ion batteries depends on effective behaviour diagnosis. In order to better realise behaviour diagnosis, this paper combined the long and short‐term memory network (LSTM) with the temporal convolution network (TCN) for the first time and established a synthetic thermal convolutional‐memory network (STCMN) for lithium‐ion battery behaviour diagnosis against noise interruptions. In addition, a TCN‐LSTM alliance network structure is designed. The TCN‐LSTM alliance network is an effective architecture applied not only to the temperature prediction of Li‐ion batteries but also to the thermal diagnosis part. And these two parts finally constitute the thermal convolutional‐memory network. The experimental results show the network designed in this paper was able to improve Li‐ion battery behaviour detection.

Affordable Artificial Intelligence-Assisted Machine Supervision System for the Small and Medium-Sized Manufacturers.

With the rapid concurrent advance of artificial intelligence (AI) and Internet of Things (IoT) technology, manufacturing environments are being upgraded or equipped with a smart and connected infrastructure that empowers workers and supervisors to optimize manufacturing workflow and processes for improved energy efficiency, equipment reliability, quality, safety, and productivity. This challenges capital cost and complexity for many small and medium-sized manufacturers (SMMs) who heavily rely on people to supervise manufacturing processes and facilities. This research aims to create an affordable, scalable, accessible, and portable (ASAP) solution to automate the supervision of manufacturing processes. The proposed approach seeks to reduce the cost and complexity of smart manufacturing deployment for SMMs through the deployment of consumer-grade electronics and a novel AI development methodology. The proposed system, AI-assisted Machine Supervision (AIMS), provides SMMs with two major subsystems: direct machine monitoring (DMM) and human-machine interaction monitoring (HIM). The AIMS system was evaluated and validated with a case study in 3D printing through the affordable AI accelerator solution of the vision processing unit (VPU).

Electrification of Rural Remote Areas Using Renewable Energy Sources: Literature Review

The current stage of development of autonomous energy systems is characterized by a rapid increase in renewable energy sources’ installed capacity. Such growth is observed both in centralized and isolated energy systems. Renewable energy sources show high efficiency in the electrification of rural remote settlements around the world. The power of such power complexes varies from several kilowatts to tens of megawatts. When solving the problems of rural remote settlements electrification, the main issues of optimizing the composition of equipment and the structure of the energy systems play an extremely important role. Moreover, depending on the specifications of the problem being solved, criteria for evaluating efficiency are used, which are different. For example, the following are used as objective functions: minimization of the levelized cost of energy and fossil fuel consumption; maximizing the standard of people living and reliability indicators; the payback period of the project and other indicators. Various combinations of objective functions and the solution to the multi-criteria optimization problem are possible. Moreover, an important stage in the development of renewable energy in remote rural areas is the availability of new mechanisms to support an environmentally friendly generation. These mechanisms can be used in solving problems of optimizing the structure and composition of energy equipment in remote power systems. The main purpose of this article is to demonstrate the world practices of optimal design of isolated energy systems. The review includes both the main questions that arise when solving such problems, and specific problems that require a more detailed analysis of the object of study.

Energy and economical optimal of Nzeb design under different climate conditions of Türkiye

Numerous studies are being carried out in the literature to reduce the energy consumption of buildings under the concept of zero energy buildings. However, there is no neither widely accepted NZEB definition nor a specific design standard to achieve NZEB. This study proposes a complete design methodology from preliminary stage up until construction to achieve NZEB. In the proposed methodology, unlike the other methods, design process has been split into 2 stages. Prior to reaching zero energy balance by renewables, Pareto front solutions related to building envelope parameters were found at the first stage. Subsequently, renewable energy systems, including PV array and wind turbines, were integrated into building energy model and pareto optimal solutions have been obtained for NZEB. NSGA-II genetic optimization algorithm has been implemented with developed code, to couple optimization algorithm and energy analysis software (Energyplus), in Matlab environment. Diverse climatic conditions of Türkiye have been used since it allows simulating heating and cooling dominated building loads along with the balanced loads. Outcomes of the study showed that NZEB designs that have excess energy of up to 23 kWh/m2, 9 kWh/m2 and 3 kWh/m2 was achieved for hot semi-arid climate, Mediterranean climate and cold semi-arid climate, respectively. It was also revealed that although the share of renewable energy equipment in the initial investment cost, which corresponds to an average of 19% of overall initial cost, is not too high, the influence of renewable systems on both achieving the net energy balance and reducing LCC is very significant. Besides, the payback period of integrating renewables for NZEB is around 3.5 years if the proposed methodology is followed.

Horner syndrome after thyroid-related surgery: a review

Horner syndrome (HS) is caused by damage to the cervical sympathetic nerve. HS is a rare complication after thyroidectomy. The main manifestations of HS include miosis and ptosis of the eyelids, which seriously affect esthetics and quality of life. At present, there is a lack of research on HS after thyroidectomy, and its etiology is not completely clear. This review aimed to evaluate how to reduce the incidence of HS and promote the recovery from HS as well as to provide a reference for the protection of cervical sympathetic nerves during surgery. HS caused by thyroid surgery is not particularly common, but it is still worthy of our attention. After searching with "Horner Syndrome," "Thyroid" as keywords, a total of 22 related cases were screened in PubMed. The results showed that open surgery, endoscopy, microwave ablation, and other surgical methods may have HS after operation. In addition, the statistics of 1213 thyroid surgeries in our hospital showed that the incidence of HS after endoscopic surgery (0.39%) was slightly higher than that after open surgery (0.29%). Further, this review analyzed potential causes of HS after thyroidectomy, so as to provide a theoretical basis for reducing its incidence. Preventing HS during thyroidectomy is a difficult problem. The close and highly variable anatomical relationship between the thyroid and cervical sympathetic nerves increases the risk of sympathetic nerve damage during thyroidectomy. Surgery and the use of energy equipment are also closely related to the occurrence of HS.

Development and Application of Smart Home Energy Management System Based on Wireless Network Technology

In order to solve the problem of integration of home energy management system and wireless network technology, the author proposes the development and application of a smart home energy management system based on wireless network technology. Divide the NB-IoT into different simulation levels, simulate the physical layer of the NB-IoT, and according to the household energy conservation rules, calculate the household energy distribution parameters, convert the intelligent control signal into a signal constellation point, calculate the deviation value of the control command corresponding to the energy equipment, build an intelligent control simulation algorithm, and finally complete the simulation of the intelligent control system. Experimental results show the following: The simulation method in the intelligent home language input terminal control system is based on the Internet of Things, the average time of simulating the test point of energy equipment is about 4.9 s, the required simulation time is long, and in the intelligent control system of the mobile road tunnel lighting vehicle, the simulation time required by the designed simulation method is about 6.8 s, and the simulation time is the longest. The average time of the method proposed by the author to simulate the energy distribution instruction is about 3.3 s. Conclusion. The application prospect of a smart home energy management system based on wireless network technology is very broad.

Modelling and mitigating lifetime impact of building demand responsive control of heating, ventilation and air-conditioning systems

This paper presents a modelling methodology to characterize heating, ventilation and air-conditioning (HVAC) equipment lifetime impact of load controls and an aging-aware demand responsive control strategy for single-stage HVAC systems to strike a balance between the electric utility and HVAC life-cycle costs. To assess the control performance and evaluate potential trade-offs between energy consumption, utility cost and equipment lifetime impact, whole-month simulation tests for a single-zone office building have been conducted for the proposed aging-aware control strategy along with two benchmarking strategies – energy minimizing and utility cost minimizing controllers. Test results show that the aging-aware demand response strategy could result in reductions of HVAC equipment aging effect by 18.8% to 39.1% compared to the utility-priority controller. The total building operation cost, with the electricity utility and HVAC life-cycle costs combined, could be reduced by up to 13.2% compared to the utility minimizing strategy and by up to 16.1% compared to the energy minimization baseline.

Converting data into knowledge with RCA methodology improved for inverters fault analysis

In the last years, the knowledge management methodology increased the perspective and deeply analysis in the energy evaluation, with great emphasis in the training of the maintenance teams and early detection of failure modes; these inefficiencies detection is associated to patterns recognition with expert systems. Several energy brands, utilities, universities, and design companies investigated about this problem with limits in the integration between maintenance team knowledge and the degradation of the energy equipment. Therefore, our findings are a new approach of the root cause analysis (RCA) improved with the knowledge management perspective, associated to the failure mode analysis for 164 inverters in photo-voltaic solar plant by using twenty-one failures modes; by incorporate the graph theory called Erdös–Rényi graphs with a quantitative methodology and qualitative evaluation with the knowledge management method in the root cause analysis; the dataset evaluated has 120,561 signals associated to 3,014,025 patterns, during the period from 2018 to 2021 in a PV solar plant. In this new root cause analysis method, the knowledge management is analyzed as a complement for the solution for sudden failure modes and early degradation.

Research on Regional Energy Visualization Based on Knowledge Graph

The equipment information in the regional energy system is difficult to retrieve and the amount of data is too large to realize intelligent application. In order to solve the problem, this paper proposes a regional energy visualization research method based on knowledge graph. Firstly, the collected regional energy information is classified. Secondly, the framework is defined for the unstructured data, which is difficult to be recognized by computer, and the hidden Markov model is used for word segmentation and labeling. Finally, the regional energy equipment information data are processed to construct the knowledge graph, the regional energy map structure information is represented by the ternary group graph structure, and the regional energy retrieval system is designed. The system can efficiently process and retrieve a large amount of natural language information in regional energy and realize the intelligence of regional energy equipment. It provides a strong guarantee for the efficient and stable operation of regional energy-related equipment and has a wide range of practical application and research value.