Installation Location Research Articles

Tether Force Estimation Airborne Kite Using Machine Learning Methods

This paper explores the potential of Airborne Wind Energy Systems to revolutionize wind energy generation, demonstrating advancements over current methods. Through a series of controlled field experiments and the application of classical machine learning techniques, we achieved significant improvements in tether force estimation. Our XGBoost model, for example, demonstrated a notable reduction in error in predicting the tether force that can be extracted at a particular location, with a root mean square error of 52.3 Newtons and a mean absolute error of 32.1 Newtons, coupled with a R2 error, which measures the proportion of variance explained by the model, achieved an impressive value of 0.93. These findings not only validate the effectiveness of our proposed methods but also illustrate their potential to optimize the deployment of Airborne Wind Energy Systems, thereby maximizing energy output and contributing to a sustainable, low-carbon energy future. By analyzing key input features such as wind speed and kite dynamics, our model predicts optimal locations for Airborne Wind Energy System installation, offering a promising alternative to traditional wind turbines.

Creation of Wind Speed Maps and Determination of Wind Energy Potential with Geographic Information Systems: The Case of Kırklareli Province, Türkiye

The intensive use of fossil fuels for energy production harms the environment. The adoption of sustainable energy systems can reduce the damage. Wind energy is one of the most widely used renewable sources. The most important problem in establishing new wind power plants (WPPs) is estimating the wind energy potential (WEP) in potential installation locations where there are no measured data. Many geographic information system (GIS)-based studies have been conducted on this subject. In this study, based on the technical specifications of a wind turbine selected for the Kırklareli Province of Türkiye, wind speed maps at 125 m height were created using many station points with known locations and wind speeds and the WEP of Kırklareli was calculated. In addition, the WEP map of Kırklareli was created by first determining the areas where WPPs cannot be installed and creating the wind speed map. After removing exclusion areas where wind turbines cannot be installed, the wind speeds at 125 m ranged between 3.12 m/s and 8.51 m/s. The wind speed was found to be higher in the south of the province, and the total WEP in areas with wind speeds higher than 6 m/sec was 6628.21 MW.

Optimal Configuration Strategy of Soft Open Point in Flexible Distribution Network Considering Reactive Power Sources

The intelligent soft open point (SOP) has powerful power flow regulation capabilities in the distribution network. If applied to the distribution network, it can flexibly cope with the output uncertainty of unmanageable distributed energy sources. However, considering the investment, operation, and maintenance costs, as well as the assistance of reactive power equipment, the site selection and capacity determination of SOP have become an urgent problem to be solved. This article proposes the optimal configuration strategy of SOP in a flexible interconnected distribution network, taking into account the features of distributed generation and reactive power sources. Firstly, based on the unpredictability of DG output, this paper uses improved sensitivity analysis to determine the optimal SOP installation location. Subsequently, with the optimization objective of minimizing the annual cost of the distribution network, this paper considers the characteristics of DGs, CBs, and OLCTs and uses second-order cone programming to optimize and solve SOP capacity under constraints such as trends. Finally, in the enhanced IEEE 33-node distribution system model, the effects of different scenarios on node voltage, reactive power components, and SOP location and capacity are compared.

Advancements and Challenges in Direct Air Capture Technologies: Energy Intensity, Novel Methods, Economics, and Location Strategies

Direct air capture (DAC) technology is increasingly recognized as a key tool in the pursuit of climate neutrality, enabling the removal of carbon dioxide directly from the atmosphere. Despite its potential, DAC remains in the early stages of development, with most installations limited to pilot or demonstration units. The main barriers to its widespread implementation include high energy demands and significant capture costs. This literature review addresses the most critical research directions related to the development of this technology, focusing on its challenges and prospects for deployment. Particular attention is given to studies aimed at developing new, cost-effective, and efficient sorbents that could significantly reduce the energy intensity and costs of the process. Alternative technologies, such as electrochemical and membrane-based processes, show promise but require further research to overcome limitations, such as sensitivity to oxygen presence or insufficient membrane selectivity. The economic feasibility of DAC remains uncertain, with current estimates subject to significant uncertainty. Governmental and regulatory support will be crucial for the technology’s success. Furthermore, the location of DAC installations should consider factors such as energy availability, options for carbon dioxide storage or utilization, and climatic conditions, which significantly affect process efficiency. This review highlights the necessity for continued research to overcome existing barriers and fully harness the potential of DAC technology.

Two-layer optimization model of distribution network line loss considering the uncertainty of new energy access

The integration of a distributed generator (DG) into the distribution network alters the topology structure and power flow distribution, subsequently causing changes in network loss. Moreover, existing distribution network optimization methods face high computational complexity, low efficiency, and susceptibility to local optima. This article proposes a scenario generation method using a generative adversarial network (GAN) to handle the uncertainty associated with DGs and constructs a two-layer optimization model for the distribution network. The upper layer model determines the installation location and capacity of distributed power and energy storage systems with the lowest economic cost. The lower layer model establishes an optimization model, including wind, solar, and storage, with active power network loss and voltage deviation as objective functions. Both layers are solved using the Improved Whale Optimization algorithm (IWOA). Then, the IEEE-33 node distribution system was taken as a simulation example to verify the effectiveness and superiority of the proposed model and algorithm.

Low-Frequency AC Multiport Asynchronous Grid Connection System to Optimize Generation Costs and Mitigate Bottlenecks

Renewable energy sources continue to increase due to the energy transition; thus, the generation output of conventional power sources is decreasing. The installation of renewable energy sources can lead to the concentration of these sources depending on geographical characteristics, which may cause bottlenecks between the renewable energy generation sites and load centers, and such bottlenecks can result in power shortages in load centers and may cause issues that limit the integration of renewable energy. Thus, this paper proposes the application of an LFAC multiport asynchronous grid connection system to solve these problems, where the frequency conversion device uses a variable frequency transformer (VFT). In addition, the installation location of the proposed LFAC multiport asynchronous grid connection system is selected using a grid partitioning technique, and the optimal power flow is performed to minimize the generation costs. The grid partitioning was conducted using the IEEE 39 bus system, and the feasibility of the proposed LFAC multiport asynchronous grid connection system was verified through simulation tests of the generation and load demands in the grid. In addition, the VFT control and optimal power flow control performances were confirmed through MATLAB/Simulink.

Selection of photovoltaic panels for floating systems: an analysis based on Entropy, CRITIC and TOPSIS

ABSTRACT In the context of sustainable energy use, multiple criteria are involved in the decision to select the best energy generation projects, as well as its installation location. However, despite the widespread use of decision-making techniques, there is a noticeable gap due to the lack of a systematic process for selecting the best projects for energy transition. This paper evaluates alternatives of photovoltaic panels for energy generation in floating systems and proposes a procedure to select the best project using a multiple-criteria decision analysis. The Entropy method was used to determine the weight of eight criteria, including cost, number of cells, efficiency, area, panel weight, and power characteristics, and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was used to make the selection. A sensitivity analysis was conducted considering different weighing methods. Among the 20 photovoltaic panels analysed, the method proved to be effective in determining the most successful one for installation in floating systems. The chosen panel maintained the best performance in all scenarios tested. This paper provides a systematic approach for selecting the most suitable photovoltaic panel for floating energy systems, contributing to researchers to refine decision-making methodologies and practitioners to optimise project implementation in sustainable energy initiatives.

Assessment of the viability of photovoltaic system implementation on the New Media Tower of Universitas Multimedia Nusantara using PVSyst software: A feasibility study.

The urgency of addressing climate change, exacerbated by greenhouse gas emissions, necessitates sustainable solutions, including green building practices and renewable energy adoption. This study focuses on the feasibility of implementing solar photovoltaic systems at Universitas Multimedia Nusantara (UMN), particularly in Building C, known as the New Media Tower, which is designed with green building principles. Solar energy, an increasingly prominent renewable source, presents a viable solution to reduce carbon footprints. Before installation, thorough simulations using software like PVSyst are essential to predict energy output and evaluate system efficiency. Several studies have explored PV system feasibility using simulations, highlighting the importance of software selection for accurate assessments. Building C offers potential locations for PV installation, with the rooftop being a primary consideration due to its expansive area and minimal shading. The rooftop PV system simulation shows an annual energy production of 202 MWh, close to the target of 209.64 MWh, while the parking area system only generates 64.5 MWh/year. Technical evaluations reveal that only the rooftop PV system meets electricity generation targets, highlighting its superiority over the parking area system. Financial analysis demonstrates the rooftop system's viability, with a payback period of 8.2 years and a return on investment (ROI) of 115.8%. Although the upfront investment is substantial, the long-term benefits justify implementation. Overall, this study underscores the technical and financial feasibility of rooftop photovoltaic systems on Building C at UMN, offering valuable insights for sustainable energy initiatives in academic institutions.

Defining the Best Strain Gauge Placement through Numerical Simulations of the Mechanical Behavior of the Modified-WOL Specimen

In structural steels, cracks are an inevitable occurrence, demanding an examination of their ability to resist crack propagation under expected loads and various environmental conditions. The process of experimentally determining fracture toughness comes at a significant expense, involving the use of multiple specimens and extended testing periods, which hinders the swift acquisition of crucial parameters. An alternative approach entails the execution of a constant displacement test using the Modified-WOL specimen, which is equipped with an instrumented bolt for self loading. The primary objective of this method is to provide the Threshold Stress Intensity Factor for Environment-Assisted Cracking, utilizing only a single specimen. The incorporation of electronic instrumentation is essential for obtaining reliable, real-time data. Despite its importance, a consensus is lacking in the literature regarding the best location for sensor installation on the Modified-WOL specimen, potentially influencing its mechanical response. This study aims to explore the mechanical behavior of the three components constituting the Modified-WOL specimen test in accordance with the guidelines outlined by ISO 7539-6. Employing the Finite Element Method with two- and three-dimensional models, this investigation utilizes the Augmented Lagrangian method for formulating the contact regions. Additionally, quarter-point singular elements are employed to accurately represent stress singularity behavior at the crack tip. The numerical computation of fracture parameter (KI) is conducted using the Displacement Correlation Technique. Comparative analyses are then carried out between the numerical and the analytical values of KI determined based on the ISO 7539-6 standard. The findings demonstrate alignment with empirical literature values, ultimately contributing to the identification of the best location for strain gauge installation among the highlighted regions of considerable interest.

Analysis of the Impact of Photovoltaic Generation on the Level of Energy Losses in a Low-Voltage Network

Due to the dynamic development of energy generation in photovoltaic installations, a reliable assessment of their impact on the level of energy losses in distribution networks is needed. For energy companies managing network resources, this issue has a very tangible practical aspect. Therefore, ongoing analyses of the level of electricity losses based on actual measurement data of prosumers are needed. In the paper, the influence of energy introduced by prosumer photovoltaic installations on energy losses in a low-voltage radial line is investigated. The issue is examined from three perspectives: 1. Focused on energy supplied into the low-voltage grid from photovoltaic installations; 2. the installations’ locations; and 3. the product of energy and distance from the power source. Comparative assessments are made of the examined aspects for 87 possible locations of prosumer installations in the tested low-voltage network. An analysis of energy losses is carried out both for the entire analysed network and separately for the line and the transformer. The changes in energy losses are influenced by both the power and the location of the photovoltaic installations. Based on the research findings, functions defining relative changes in energy losses in the low-voltage network are determined.

Borehole Optical Fibre Distributed Temperature Sensing vs. Manual Temperature Logging for Geothermal Condition Assessment: Results of the OptiSGE Project.

Geothermal energy is a crucial component contributing to the development of local thermal energy systems as a carbon-neutral and reliable energy source. Insights into its availability derive from knowledge of geology, hydrogeology and the thermal regime of the subsurface. This expertise helps to locate and monitor geothermal installations as well as observe diverse aspects of natural and man-made thermal effects. Temperature measurements were performed in hydrogeological boreholes in south-western Poland using two methods, i.e., manual temperature logging and optical fibre distributed temperature sensing (OF DTS). It was assumed the water column in each borehole was under thermodynamic equilibrium with the local geothermal gradient of the subsurface, meaning rocks and aquifers. Most of the acquired results show typical patterns, with the upper part of the log depending on altitude, weather and climate as well as on seasonal temperature changes. For deeper parts, the temperature normally increases depending on the local geothermal gradient. The temperature logs for some boreholes located in urban agglomerations showed anthropogenic influence caused by the presence of infrastructure, the urban heat island effect, post-mining activities, etc. The presented research methods are suitable for applications connected with studies crucial to selecting the locations of geothermal installations and to optimize their technical parameters. The observations also help to identify zones of intensified groundwater flow, groundwater inrush into wells, fractured and fissured zones and many others.

Optimal expansion planning of a self-healing distribution system considering resiliency investment alternatives

This paper proposes a three-stage optimization framework for the expansion planning of a self-healing distribution system that determines the optimal characteristics of distributed generation, energy storage systems, electric vehicle charging stations, and sectionalizing switches for the planning horizon. The main contribution of this model is that the proposed model considers the resilient investment alternatives in the expansion planning exercise to reduce the system's vulnerability against external shocks. The mobile energy storage system commitment in contingent conditions is another contribution of this paper. In the first stage, the optimal location, capacity, and time of installation of the electricity facilities are calculated. Then, the optimal allocation of sectionalizing switches is performed in the second stage. The third stage consists of three levels. In the first and second levels, the optimal normal and contingent operational scheduling are determined, respectively. The system is sectionalized into multi-microgrid systems in contingent conditions. Finally, the resilient investment alternatives for the designed system are evaluated. The proposed model utilizes a self-healing index and resilient expansion planning index to assess the impacts of resilient investment alternatives on the operational scheduling conditions. The proposed model was evaluated using the IEEE 123-bus system. The proposed method reduced the estimated average value of the worst-case energy not supplied by 50.52 % for the 5th year of the planning horizon concerning the no-resiliency investment case. Further, the proposed resilience investment method increased the self-healing index by about 9.32 % concerning the no-resiliency investment case.

Impact of a natural rubber-based scratcher as an environmental enrichment on the scratching behavior, cortisol level, and semen quality of stable male goats.

Goats are valuable livestock because they can generate meat and milk for human consumption. Goat husbandry is becoming more intensive due to the growing demand for goat products, which may impact animal welfare and natural behavior. This study aimed to investigate the impact of natural rubber (para rubber)-based scratchers as an environmental enrichment on scratching behavior, cortisol levels, and semen quality in stable bucks (male goats/goats). Nine male goats were used in this study. Scratching behavior and cortisol levels were used as welfare indicators, whereas semen quality was evaluated as an indicator of reproductive potential. These indicators were analyzed before and after scratcher installation. After installing the scratchers, the goats showed a significant increase in scratching behavior and a notable decrease in cortisol levels (p < 0.001). Notably, the goats exhibited a marked preference for scratching against the scratcher (p < 0.001) compared to the stable. They significantly preferred using their heads for scratching (p < 0.001) instead of other body parts. In addition, goats preferred to scratch on the softest rubber scratchers at specific installation locations (p < 0.001). Although there was a slight improvement in semen quality, there was no statistically significant difference (p > 0.05). A natural rubber-based scratcher can increase scratching behavior and reduce cortisol levels, indicating its potential to improve the welfare of farm goats. Selecting an appropriate hardness and preferred location is essential to ensure that the scratcher effectively encourages animals to use it.

Correlation analysis between urban environment features and crime occurrence based on explainable artificial intelligence techniques

ABSTRACT Crime and urban environments are considered to be closely related. However, there exists no clear understanding of this phenomenon. Therefore, this study analyzes the relationship between various urban environmental variables and crime occurrences and provides insights into the optimal placement of crime prevention facilities by developing a crime prediction map based on a paradigm of the Daegu city. To achieve this, we used 373,387 crime reports from Daegu as dependent variables and 370,000 random points. Independent variables included information such as the point of interest, land use, land cover, floating population, and card sales. The developed crime prediction map created using the model was used to evaluate the adequacy of CCTV installation locations and identify areas requiring new CCTV installations. The performances of various machine-learning models were compared and the XGBoost model (accuracy of 89.7 % and precision of 89.8 %) was selected. Key variables influencing crime report data were identified using the SHAP(SHapley Additive explanation) method. To analyze the spatial explanatory power of the relationship between crime and urban environmental variables, various buffer distances were tested, and a 20 m buffer distance was derived. The results of this study are expected to provide valuable data for crime prevention policies.

Air quality improvement at urban bus stops: Optimal air purification placement using CFD

Nitrogen dioxide (NO2) levels are often elevated near roadways due to vehicle emissions, while sulfur dioxide (SO2) is predominantly found near petrochemical complexes as a result of industrial activities such as oil refining and chemical manufacturing. Considering the detrimental effects of these emissions on the environment and human health, the optimal placement of air purification systems at two bus stops in Ulsan, a heavily industrialized city in South Korea, was investigated in this study to reduce NO2 and SO2 concentrations. Computational fluid dynamics (CFD) simulations were performed to identify strategic installation locations, resulting in a significant reduction in pollutant levels. The largest impact was noted for the Deokha Market bus stop, whereby the added health risk (AR) decreased by 1.93 % and the exposure reduction effectiveness (ERE), a measure of air purification system efficiency, increased by 13.8 %. Similarly, at the Hyomun Intersection bus stop, placing the system near the sidewalk led to a significant reduction in AR by 1.60 % and an increase in ERE by 11.63 %. Additionally, air purification systems at Ulsan bus stops are expected to reduce NO2 levels by 9.1 ppb, decreasing mortality risk by 1.44 %, saving 7 lives annually, and yielding an economic benefit of 33.06 million USD.

Self-reported public fast charging infrastructure demand: What do existing and potential electric vehicle adopters want and where?

Electric vehicles (EVs) promise emissions reduction, but adoption rates must increase to meet 2030 targets. Since public fast charging infrastructure (PFCI) is considered important to increase EV uptake, this research aims to assess its demand across existing and potential EV adopters in Ireland. Online mapping tools were used to capture 1635 self-reported locations where users prefer PFCI, along with other related preferences from 545 respondents. The results were analysed using a mixed-method approach including exploratory factor analysis (EFA), Geographic Information System (GIS), two-step cluster analysis, and qualitative analysis. The results indicate that expanding PFCI is critical for increasing EV uptake, with 81.4% of potential EV adopters showing a significant impact on uptake. Major deterrents identified include insufficient availability of public fast chargers followed by high charging costs. The qualitative analysis highlights existing EV users’ demand for improved end-user experiences, such as unified payment systems. Most preferred locations for PFCI installation include travel routes, followed by shopping centres/ supermarkets. Results also indicate that a reliable second-hand market would be key to increasing EV uptake. The findings from this study can serve policymakers in effectively rolling out PFCI, while the methodology employed can be replicated in other comparable study areas.

Robust Estimation of Crowd Density Using Vision Transformers

Estimating and predicting crowd density at large events or during disasters is of paramount importance for enhancing emergency management systems. This includes planning effective evacuation routes, optimizing rescue operations, and ensuring efficient deployment of emergency services. Traditionally, surveillance systems that rely on cameras have been employed to monitor crowd movements. However, accurately estimating crowd density using such systems presents several challenges. These challenges stem primarily from the interaction between large crowds and the limitations of two-dimensional cameras in capturing the full scope of three-dimensional spaces. Optical distortions, environmental factors, and variations in camera angles further complicate the task, making accurate estimations difficult to achieve. To address these challenges, this paper introduces a robust method for calculating crowd density that leverages advanced vision transformers. By combining the output of these transformers with a two-stage neural network, the method effectively mitigates the limitations of traditional approaches. One of the key advantages of the proposed system is its robustness, which allows it to perform well across different camera specifications, installation locations, and image aspect ratios. The method applies and evaluates various deep learning techniques, introducing improvements to existing network structures that are better suited for the problem at hand. Extensive experimental verification demonstrates that the proposed method consistently produces accurate crowd density estimates, even in diverse and complex crowd environments. This robust performance underscores its potential for improving emergency management and crowd control in real-world situations.

Multi-modal response control with multiple suspension-type tuned vibration absorbers

Due to complicated excitations, engineering structures are often subjected to multi-modal responses. Considering the feasibility in practical installation on slender structures, multiple Suspension-type Tuned Vibration Absorbers (S-TVAs) are investigated for multi-modal response control. Firstly, parametric optimization of a single S-TVA for single-modal response control is investigated analytically. The issues regarding to the optimal tuning, static and dynamic performances, and installation location are addressed. Subsequently, an optimal design method for multi-modal response control with multiple S-TVAs is presented. Two aspects on the optimization strategy are discussed. Consequently, the optimization should be performed with an inverse modal order sequence. And, the modal information should be updated considering the S-TVA optimized in the previous step. Finally, the effectiveness of the presented optimal design method is validated through practical wind-induced response control on a slender chimney. The most unfavorable response can be suppressed up to 59.7 %, which is 47.8 % better than traditional single-modal control approach. Moreover, it is interesting to find that the practical overall control performance may not be achieved with more controlled modes intuitively. It is recommended to select from several practical cases determined by the presented optimal design method. Practical installation and feasibility are highly required to be considered in practice.

Direct energy deposition for smart micro reactor

ABSTRACT Nuclear microreactors (MRs) have attracted significant attention for their versatility in installation locations, especially with the growing demand for sustainable green energy in large data processing facilities. However, ensuring their safe operation necessitates frequent inspections, which can be challenging for practical efficient management. This study proposes a novel approach using direct energy deposition to incorporate an optical fiber sensor into MR components, enabling real-time monitoring with artificial intelligence. The embedded optical fiber generates real-time data that allows for AI-driven in-vivo thermal deformation analysis. Our smart MR component can detect structural anomalies, identify abnormal operations, and assess operational conditions through augmented reality interfaces and AI technology.

Development and Experimental Study of Supercritical Flow Payload for Extravehicular Mounting on TZ-6.

This paper provides a detailed description of the development and experimental results of the supercritical flow experiment payload carried on the TZ-6 cargo spacecraft, as well as a systematic verification of the out-of-cabin deployment experiment. The technical and engineering indicators of the payload deployment experiment are analyzed, and the functional modules of the payload are shown. The paper provides a detailed description of the design, installation location, size, weight, temperature, illumination, pressure, radiation, control, command reception, telemetry data, downlink data, and experimental procedures for the out-of-cabin payload in the extreme conditions of space. The paper presents the annular liquid surface state and temperature oscillation signals obtained from the space experiment and conducts ground matching experiments to verify the results, providing scientific references for the design and condition setting of space experiments and comparisons for the experimental results to obtain the flow field structure under supercritical conditions. The paper provides a specific summary and discussion of the space fluid science experiment project, providing useful references for future long-term in-orbit scientific research using cargo spacecraft.