Real Installation Research Articles

Comparison of the Energy Contributions of Different Types of Ground Heat Exchangers Related to Cost in a Working Ground Source Heat Pump System

Geothermal systems face adoption challenges due to their high initial investment cost. Accurate cost analyses and a more precise understanding of updated prices could assist geothermal industry projects in obtaining investment financing and better money management with the right equipment. As the cost of geothermal installations can vary widely depending on case and location, it seems essential to clarify the factors and parameters that determine the cost of the system. These include the type of loop system, the ground conditions, the type of heat pump, the system size, and the geographical location. The scope of this study is to compare the operation of various types of ground heat exchangers (GHEs) present in a Ground Source Heat Pump (GSHP) system installed in the coastal area of the Mediterranean climate zone of Cyprus. The highlight of this work is that it presents real installation cost data as well as recorded total energy contributed by the GHEs to the GSHP system of a HP cooling and heating capacities of 101 kW and 117 kW, respectively. The input contribution from the GHEs to the HP is 85,650 kWh (308,340 MJ) in summer and 25,880 kWh (93,168 MJ) in winter. It is shown that, among the three groups of GHEs investigated, the open-well GHE complex has the lowest cost per kWh ratio (0.32 EUR/kWh), followed by the vertical GHE complex (1.05 EUR/kWh), and lastly by the helical coil GHE (2.77 EUR/kWh). This clearly suggests that when underground water is available, the open-well GHE is much more favorable than other GHE types.

Implementation of economic and didactic opportunities of the educational university-based technology park in the training of engineers for the food industry

Introduction. With the advent of a new component in the system of continuous education – the children’s and youth leisure technology park (technopark) at engineering universities – the task arose to identify its niche in this system, to determine educational and mentoring opportunities. Research purposes are to determine the economic and didactic capabilities of university educational technology parks and to describe the principles of advanced education. Materials and methods. The research material was the activities of the technology park in the field of training personnel for the food industry. Systemic, personal, activity-based and axiological methodological approaches were used. Project-oriented learning and the research-based teaching method, collaboration technology, methods of collective and creative project activity, STEM education technologies, and collaborative learning were applied. Results. Leisure education in the technology park for schoolchildren with engineering inclinations is aimed at the students’ individual development in a creative team, project activities under the guidance of a mentor, demonstration of their scientific and technical achievements at international competitions, active search for their creative “I” and choice of direction for further professional development within the walls a specific university and an already chosen specialty. The technology park is also considered from the perspective of economic pedagogy. The “product” that the technology park offers is the skills of creative work, the ability to combine knowledge obtained from various fields of technical and technological sciences to generate new knowledge and create unique industries, i.e. as an intellectual “good” in the format of skills for its use and skills for ethical assessment of the results of future achievements (axiological aspect of training and education). STEM education technologies are optimally combined with the use of remote access laboratory installations for research, which makes it possible to conduct physical and chemical experiments in real time in real installations, remotely controlling the operation of the installation. This makes it possible to form a clear idea of natural phenomena and their role in technological processes. Conclusion. The creation of university-based technology parks is promising for the actively developing technology industry, it provides the opportunity to form a talented personnel reserve and develop environmental thinking.

A novel methodology for map-based model fitting: A case study with a Dual Source Heat Pump experimental dataset

This paper presents a new methodology to adjust map-based models to experimental data and reports the main results of a comprehensive experimental campaign of a Dual Source Heat Pump (DSHP) prototype. The prototype tested incorporates variable speed components (compressor, circulation pumps, and fan). The novelty of this prototype lies in its ability to select two possible heat sources: air or ground. Thus, it can operate as a geothermal or aerothermal heat pump, as well as a chiller, thanks to the additional capacity to reverse the cycle. Thanks to this hybrid approach, several advantages can be obtained compared to conventional equipment, such as higher efficiency, the requirement of smaller borehole heat exchangers, or the absence of defrost cycles. In a prior study, polynomial models were developed to accurately characterize the DSHP’s performance (i.e., condenser and evaporator capacities and electrical energy consumption). These models were obtained considering the external variables to the unit as independent variables to facilitate their applicability using variables commonly measured in real installations. Due to the complexity of heat pump performance, which in current equipment can be influenced by up to 5 or 6 independent variables, the search for suitable polynomial models required the availability of a complete working map including more than 3000 working points. Thus, this previous work developed these models based only on simulation results. In this sense, this paper concludes the development of these models by focusing on two critical issues concerning empirical model development. The first aspect involves determining the minimum number and location of testing points needed to define the experimental sample for the model adjustment. The reported experimental data were obtained by analyzing the most suitable experimental design methodology to create the experimental matrices in each operating mode of the DSHP. The second aspect focuses on the final adjustment of models using experimental data. A novel fitting approach for empirical models is introduced in the last part of this study. The developed methodology enables the integration of simulation and experimental results for the final fitting of empirical models through a two-step adjustment. The first step involves analyzing and defining polynomial functionals from the complete working maps generated by simulation. Subsequently, in a second step, the polynomial models are refitted to a suitable experimental sample using the methodology presented in this work. The latter allows for the increase of the accuracy of the models and the minimization of experimental costs. This novel approach ensures a robust characterization of systems with many independent variables using a minimum amount of experimental data. Significant benefits can be obtained from its application, such as the reduction of experimental cost and an increase in the model’s accuracy through an effective combination of both experimental and simulated information. Furthermore, it can be considered of general applicability to other engineering problems where the characterization of physical systems influenced by a high number of independent variables is required.

Experimental study of an on-grid hybrid solar air conditioner with evaporative pre-cooling of condenser inlet air

This paper presents an experimental study of a split type solar air conditioning system with evaporative pre-cooling at the condenser. The main objective of this research is to evaluate the thermal and electrical performance of the system under hot summer conditions in a Mediterranean climate. Previous studies have separately shown the benefits of both condenser inlet air pre-cooling and photovoltaic solar cooling. The novelty of this work will be the study of the coupling of these two techniques in a real installation, where the viability of the system depends on the component-level design and the operating conditions, since weather variables such as ambient temperature, relative humidity and solar radiation significantly affect the thermal behaviour of the refrigeration cycle, the evaporative pre-cooling capacity and the performance of the photovoltaic panels. Experimental tests were carried out over a summer season to evaluate the behaviour of the system and to obtain performance correlations validated with experimental data. These correlations will allow the modelling of the system and will be used to carry out an economic and environmental feasibility study of the proposed hybrid solar air conditioning system. The results show that a 100mm-thick evaporative pad achieved an average evaporative cooling efficiency for all tests performed of ɛevap=67.4%, reducing the air inlet temperature to the condenser by around 6°C. This resulted in an 18.3% improvement in the EER of the air conditioner. In addition, the use of evaporative pre-cooling resulted in a significant 23% reduction in peak power consumption. The study also evaluated the impact of the air pressure drop caused by the evaporative pad when not in use, with results favouring its installation. The system achieved a solar contribution of more than 30% under different solar radiation conditions when using pre-cooling, compared to 25% with a standard condenser. In addition, the combination of photovoltaic contribution and evaporative pre-cooling reduced energy consumption by 43%.

Real-time number plate detection using AI and ML

The abstract presents a research study focusing on real-time license plate verification, a key feature of electronic systems that operate by rapidly identifying and removing identification numbers from vehicle registration in a dynamic global environment. The research leverages the combination of artificial intelligence (AI) and machine learning (ML) techniques, specifically the integration of region-based convolutional neural networks (RCNN) and advanced RCNN algorithms, to create a powerful and readily available system. In terms of methods, this research optimizes algorithm performance and deploys the system in a cloud-based environment to improve accessibility and scalability. Through careful design and optimization, the proposed system has achieved a consistent result in license recognition, as evident from the well-accounted evaluation of performance, including precision, recall, and computational efficiency. The results demonstrate the efficiency and usability of this system in a real installation and promise to revolutionize automatic vehicle identification. Finally, the integration of artificial intelligence and machine learning technology into real-time license plate recognition signifies changes in traffic management, assessment safety and smart city plans. Therefore, interdisciplinary collaboration and continuous innovation are crucial to shaping a sustainable and balanced future for intelligent transportation systems.

Design of Sinusoidal Leading Edge for Low-Speed Axial Fans Operating under Inflow Distortion

Axial fans may be equipped with passive flow control devices to enhance rotor efficiency or minimize noise emissions. In this regard, blade designs influenced by biomimicry, such as rotors with sinusoidal leading edges (LEs), have gained popularity in recent years. However, their design is predominantly driven by a trial-and-error approach, with limited systematic studies on the influence of rotor performance. Furthermore, their effectiveness is typically evaluated under controlled conditions that may significantly differ from operations in real installation layouts. In this work, a systematic review of the design process for sinusoidal LE axial fan rotors is provided, aiming to summarize previous design experiences. Then, a modified sinusoidal LE is designed and fitted to a 7.3 m low-speed axial fan for air-cooled condensers (ACCs). These fans operate at environmental conditions, providing a quasi-zero static pressure rise, often with inflow non-uniformities. A series of RANS computations were run to simulate the performance of the baseline fan and that of the sinusoidal leading edge, considering a real installation setup at Stellenbosh University, where the ACC is constrained between buildings and has a channel running on the ground below the fan inlet. The aim is to explore the nonbalanced inflow condition effects in both rotor geometries and to test the effect of the installation layout on fan performance. The results show that the modification to the rotor allows for a more even distribution of flow in the blade-to-blade passages with respect to the baseline geometry.

Scale Modular Test Platform for the Characterization of PD Measuring Systems Using HFCT Sensors.

Today, online partial discharge (PD) measurements are common practice to assess the condition status of dielectrics in high-voltage (HV) electrical grids. However, when online PD measurements are carried out in electrical facilities, several disadvantages must be considered. Among the most important are high levels of changing electrical noise and interferences, signal phase couplings (cross-talk phenomena), and the simultaneous presence of various defects and difficulties in localizing and identifying them. In the last few decades, various PD-measuring systems have been developed to deal with these inconveniences and try to achieve the adequate supervision of electrical installations. In the state of the art, one of the main problems that electrical companies and technology developers face is the difficulty in characterizing the measuring system's functionalities in laboratory setups or in real-world facilities, where simulated or real defects must be detected. This is mainly due to the complexity and costs that the laboratory setups entail and the fact that the facilities are permanently in service. Furthermore, in the latter scenario, owners cannot assign facilities to carry out the tests, which could cause irreversible damage. Additionally, with the aforementioned installations, a comparison of results over time in various locations is not possible, and noise conditions cannot be controlled to perform the characterizations in a correct way. To deal with the problems indicated, in this article, an affordable scale modular test platform that simulates an HV installation is presented, where real on-site PD measuring conditions are simulated and controlled. In this first development, the HV installation comprises a cable system connected at both ends to a gas-insulated substation (GIS). As the most common acquisition technique in online applications is based on the placement of high-frequency current transformer (HFCT) sensors in the grounding cables of facilities, the test platform is mainly adapted to carry out measurements with this type of sensor. The designed and developed test platform was validated to assess its features and the degree of convergence with a real installation, showing the convenience of its use for the appropriate and standardized characterization of PD-measuring systems.

Understanding Resonance in a Renewable Energy Power Plant

This paper investigates the effect of various causes of resonance found in a typical renewable energy power plant. The consequences of resonance are discussed, and a simplified single-phase equivalent model of a plant is mathematically described and modelled in MATLAB. Reactive element interaction that causes resonant frequencies is discussed. Results obtained from the simplified mathematical model are compared with a detailed DIgSILENT PowerFactory model of a real installation. It is concluded that using the mathematical equations for the harmonic impedance profiles could provide insight into the expected resonant frequencies in a plant and possible increase in harmonic current propagation.

Application of the Conjugate Gradient Method for Predicting Unknown Heat Flux in 2D Plat under Effect of Insulation

When an anomaly is discovered during a thermal inspection of industrial equipment, the diagnosis of finding the heat source is made more difficult by the presence of heat insulation. The use of the Conjugate Gradient Method (CGM) to solve the unknown heat flux in Inverse Heat Conduction Problem (IHCP) under insulation condition has been discussed. This method is used to predict a heat flux by utilizing temperature data at any points of measurement. The study deals with the structure of 2D thin plate at steady state. A copper plate with a thickness of 1 mm is used as specimen. White glass wool is used to thermally insulate the plate on the back surface. An electrical heater is plate mounted and operated by varying the DC voltage. A datalogger with thermocouple sensors records plate temperature changes. Software for solving the IHCP based on the CGM was developed. Initially, the software was implemented using synthetic data obtained from the forward heat conduction equations with a known heat flux. Simulated measurement data are assumed to have high accuracy (± 0.1 ºC). Determination of heat flux with the CGM gives very satisfactory results with a low error below 0.12%. The CGM was then applied using experimental data. With a measurement error of ± 0.5 ºC, the computational stopping criterion can still be met satisfactorily. In real installations, equipment is sometimes partially or completely isolated. In the experiment, this phenomenon is simulated by varying the isolation area as follows: 0%, 25%, 50% and 100%. The results of the flux calculation are correlated with the real flux supplied by the electrical heater. Each type of insulation area has a similar curve. By obtaining the correlation equation, the equivalent heat flux from calculation to real and vice versa can be carried out.

Design and implementation of the safety system of a solar-driven smart micro-grid comprising hydrogen production for electricity & cooling co-generation

This article presents a comprehensive description of the safety system of a real installation that comprises PV panels, lithium-ion batteries, an electrolyzer, H2 storage, a fuel cell, and a barium chloride/ammonia thermochemical prototype for heat recovery and cooling production. Such a system allows for the increase of the overall efficiency of the H2 chain by exploiting the waste heat and transforming it into a cooling effect, particularly useful in tropical regions like French Polynesia.The study provides a great deal of detail regarding practical aspects of the system implementation and a consistent reference to the relevant standards and regulations applicable to the subject matter. More specifically, the study covers the ATEX classification of the site, the safety features of each component, the electrical power distribution, the main safety instrumented system, fire safety and the force ventilation system. The study also includes safety assessment and a section on lessons learned that could serve as guidance for future installations. In addition, an extensive amount of technical data is readily available to the reader in repository (P&ID, electrical diagrams, etc.).

Rationalization of Electrical Energy Consumption in Households through the Use of Cheap IoT Module with Cloud Data Storage

This article explores mechanisms to enhance the efficient utilization of renewable energy sources (RES), with a particular emphasis on photovoltaic installations. One such strategy involves implementing a customized electricity rate system for individual consumers. This paper discusses the potential economic and environmental benefits of transitioning from a flat-rate tariff to a time-of-day tariff. This modification can lead to increased energy consumption during off-peak hours, aligning with occasional periods of photovoltaic installations’ overproduction, which might require their temporary shutdowns. The energy that could be produced by RES is supplied by conventional power plants (mostly coal-fueled). Not only does this have negative effects on the environment, but it also increases energy costs. In order to make an informed decision regarding the change of tariff, the consumer must be aware of its potential benefits and drawbacks. The article introduces an IoT-based, cost-effective system with cloud data storage for monitoring residential electricity consumption, offering various features, including an assessment of the financial viability of switching tariffs. This system has been operational for more than six months in real installation, encouraging homeowners to transition from a flat rate tariff to time-of-day tariff and optimize their use of electrical appliances. The article presents the potential benefits of this action, encompassing both financial aspects for users of the installation and environmental protection issues.

Internet of Things (IoT) in Buildings: A Learning Factory

Advances towards smart ecosystems showcase Internet of Things (IoT) as a transversal strategy to improve energy efficiency in buildings, enhance their comfort and environmental conditions, and increase knowledge about building behavior, its relationships with users and the interconnections among themselves and the environmental and ecological context. EU estimates that 75% of the building stock is inefficient and more than 40 years old. Although many buildings have some type of system for regulating the indoor temperature, only a small subset provides integrated heating, ventilation, and air conditioning (HVAC) systems. Within that subset, only a small percentage includes smart sensors, and only a slight portion of that percentage integrates those sensors into IoT ecosystems. This work pursues two objectives. The first is to understand the built environment as a set of interconnected systems constituting a complex framework in which IoT ecosystems are key enabling technologies for improving energy efficiency and indoor air quality (IAQ) by filling the gap between theoretical simulations and real measurements. The second is to understand IoT ecosystems as cost-effective solutions for acquiring data through connected sensors, analyzing information in real time, and building knowledge to make data-driven decisions. The dataset is publicly available for third-party use to assist the scientific community in its research studies. This paper details the functional scheme of the IoT ecosystem following a three-level methodology for (1) identifying buildings (with regard to their use patterns, thermal variation, geographical orientation, etc.) to analyze their performance; (2) selecting representative spaces (according to their location, orientation, use, size, occupancy, etc.) to monitor their behavior; and (3) deploying and configuring an infrastructure with +200 geolocated wireless sensors in +100 representative spaces, collecting a dataset of +10,000 measurements every hour. The results obtained through real installations with IoT as a learning factory include several learned lessons about building complexity, energy consumption, costs, savings, IAQ and health improvement. A proof of concept of building performance prediction based on neural networks (applied to CO2 and temperature) is proposed. This first learning shows that IAQ measurements meet recommended levels around 90% of the time and that an IoT-managed HVAC system can achieve energy-consumption savings of between 10 and 15%. In summary, in a real context involving economic restrictions, complexity, high energy costs, social vulnerability, and climate change, IoT-based strategies, as proposed in this work, offer a modular and interoperable approach, moving towards smart communities (buildings, cities, regions, etc.) by improving energy efficiency and environmental quality (indoor and outdoor) at low cost, with quick implementation, and low impact on users. Great challenges remain for growth and interconnection in IoT use, especially challenges posed by climate change and sustainability.

Experimental investigation of hotspot phenomenon in PV arrays under mismatch conditions

The global installed capacity of photovoltaic (PV) plants is increasing exponentially since the beginning of the 21st century. And as the early installations have started nearing their end-of-life, presently, PV waste management has started raising concerns amongst environmental researchers. The cumulative PV waste generation is estimated to reach 8 million tonnes by 2030, however, interestingly, this humungous volume may be reduced by 79% if early failures could be averted. And one of the major contributors to the early failure of the PV modules is the hotspot generation under partial shading and other mismatch conditions. Various innovative array configurations have been proposed in the past to minimize power loss under partial shading conditions, however, the performance of those from the perspective of hotspot formation and PV reliability is neglected. In the present work, the efficacy of the hotspot prevention mechanism is investigated, both in an experimental setup and in real installations. The results revealed that the extant mechanism is ineffective in preventing the occurrence of hotspots in total cross-tied (TCT) array configuration, which is hailed as the best performing one in the literature, when studied from the perspective of mismatch power loss only.

Methods for product sound design: a correlation between annoyance and sound quality of noise emitted by household appliance

The sound quality analysis, used as a tool for the product design, has been defined and described in the literature and the characteristics describing the type of sound have been identified. However it is often not known how the subjective assessments and the human factor are taken into account in the procedure governing the studies of sound quality. Today making a product as quiet as possible is one of the most captivating challenge for the industrial sector, especially if it is for a household appliance. This case study show how the consumer perception of product sound quality is a fundamental variable to define the sound character. The classification of sound quality is based on the correlation between an objective measurement and the subjective judgment result. Psychoacoustic metrics like Loudness, Sharpness and Roughness, and the combinations of them into more sophisticated models, like annoyance, pleasantness and powerfulness are commonly used for analysis and prediction of product sound quality. However, some problems arise when the sounds are analyzed by different consumers. It is assumed that the reason for this is the human not ability to understand the difference between noise and annoyance and to focus consciously or unconsciously on the sound emitted by the appliance. For this reason the aim of this work is to validate a method to calculate a sound quality index applicable to the sounds produced by five kitchen hoods in a real installation condition.

Faulty feeder detection for single phase-to-ground faults in distribution networks based on patch-to-patch CNN and feeder-to-feeder LSTM

Faulty feeder detection has always been recognized as an essential issue in guaranteeing the stable and reliable operation of distribution networks. Existing methods fail to fully exploit the spatial correlation and temporal dependencies in the zero-sequence currents, which are exhibited as waveforms on the spatial domain and are displayed as time-series data on the time domain. In this paper, a novel detection method based on a hybrid model of convolutional neural network (CNN) and long short-term memory (LSTM) neural network is proposed, and the spatial–temporal information can be comprehensively explored. Deep spatial features are extracted by using CNN, and they are further processed by using LSTM network. Besides, to maintain the temporal dependencies of the extracted spatial features, the current waveforms are recognized on the patch scale by the proposed patch-to-patch CNN (PToP CNN). Moreover, a feeder-to-feeder LSTM (FToF LSTM) network is established to learn and compare spatial–temporal correlations between feeders. The joint PToP-CNN and FToF-LSTM can achieve collaborative superiority on mining the fault features in the zero-sequence currents. To verify the prospects in real installations, the hybrid model is implemented in an embedded device, called NVIDIA Jetson AGX Xavier, and the real-time detection demonstrates the efficiency of the proposed method.

Analysis of the Water Loss Volume in a Real Installation

Analysis of the Water Loss Volume in a Real Installation

Automatic maintenance with robotics of the induction melting plant in a cold crucible

The performance of works within the framework of technological operations of the closed nuclear fuel cycle of an industrial power complex is inevitably associated with the effects of an external factors that have a significant impact on the technological process. Thus, human participation should be minimized, mechanical and electromechanical systems should be included in the process, in particular, means of robotics. When creating a deserted technology, the issue of automation of the process comes to the fore, including with the use of robotic systems that solve transport, service, inspection tasks, including tasks directly related to the technological process. Special requirements are also imposed on the materials used. The processing of the vitrification of high-level waste is being considered in this work. Such a glazing site by the IMCC method was created by specialists of JSC «VNIINM». In this work, the analysis of the current technical process of the work of this site is carried out, proposals for optimizing the performance of individual operations are issued, recommendations for retrofitting the site are given. Based on the test results of the demonstration stand, proposals were formulated for the automation of the glazing section, taking into account the environmental factors that take place on a real installation, and taking into account the results obtained as a result of the mock-up tests.

Development and Initial testing of a Virtual Laboratory for the Build-up and Testing of Microgrid Management Algorithms

In a bid of facilitating the increasing penetration of intermittent and random renewable energies, microgrids along with their management algorithms are becoming crucial assets. To prove their effectiveness, these algorithms need to be tested in real environments and/or laboratories, which can be very difficult in many cases, especially at the initial development stages. To solve this issue, this article proposes the use of a laboratory digital twin, i.e., a virtual laboratory with a behaviour that is similar to that of real installations, aimed at facilitating the development, testing and debugging of microgrids management algorithms. The proposed solution is demonstrated to be safe and complete when it comes to test these algorithms.

First bifacial PV modules early 1983

A pioneer experience with the production and first commercialization of bifacial PV modules was developed by ISOFOTON, a Spanish academic spin-off established in 1981. Bifacial modules based on n-PERT cell technology were produced until 1989. 59 modules from that time were recovered from real installations after about 20 years of outdoor exposure. After cleaning and testing, 56 of these modules were connected to the grid at an IES-UPM terrace in Madrid on the 5th May 2021, constituting a 3.79 kW PV generator (nominal power of the frontal side), which is now in routine operation. The good health of these modules translates into yearly Performance Ratios of 88% (referred to the frontal side irradiation) and 81% (referred to the frontal plus rear irradiation). The comparison of the design and features of old and modern bifacial modules allows the evolution of PV technology throughout the last three decades to be appreciated.

Stability Analysis of PFC Converters Under Different Source Impedances and Its Consequences on Zero-Crossing Distortion

In the presence of multiple power converters in a power system the total current may exhibit zero-crossing distortion in the form of recurrent damped oscillations with high magnitude. These oscillations are synchronized with the power system frequency. This paper presents a comprehensive analysis of the input current of single-phase ac-dc converters fitted with power factor correction (PFC) controllers. Emphasis is given on the impacts of the source impedance, and on how the number of converters connected to a common coupling point (PCC) impacts the PFC controller’s performance. A system model is developed followed by simulation and measurements in a real installation with electronic ballasts used to drive fluorescent lighting tubes. Results show that the recurrent damped oscillations originating from PFC controllers are close to the harmonic range and with a very low level of cancellation between devices. The magnitude therefore increases proportionally with the number of devices. As the source impedance increases, instability may occur. Possible explanations for these observations are discussed.