Station Site Research Articles

A novel multi-criteria framework for selecting optimal sites for electric vehicle charging stations from a sustainable perspective: evidence from India

A novel multi-criteria framework for selecting optimal sites for electric vehicle charging stations from a sustainable perspective: evidence from India

Mobile base station site as a virtual power plant for grid stability

Energy grids and markets are in transition. Increased use of renewable energy sources (RES) introduces new stability challenges for power grids. Despite the substantial electrical consumption of mobile networks, they are yet to harness their inherent flexibility for aiding in the stability of the power grid. A noticeable research gap exists concerning measuring full activation time for fast frequency reserve (FFR) product while using batteries from mobile network base stations. Our objective is to demonstrate that mobile operators could use their existing infrastructure to participate in the reserve market of a contemporary power grid. Furthermore, it seeks to determine if the full activation time can meet the requirements of an FFR product. The system consists of a live mobile base station site with a mobile connection to the site, local controller, an existing battery, and a power system that, in combination, can function as part of a power grid balancing system. Our main finding indicates that the rectifier reaction time within an installed base station site infrastructure ranges from 5 to 8 s, and the time when the base station is entirely off from the grid varies from 7 to 10 s. This finding is significant since the activation time is too long for the base station power system controller to be used for FFR. The required full activation time for FFR is less than 1.3 s. In conclusion, power system vendors should investigate improvements for their equipment and software products to enable fast reserve market entry for their existing customers and stay competitive.

Risk Evaluation of Urban Subway Site Selection: Balance, Attractiveness, and Financing Models

As a crucial form of public transportation, subways are becoming essential infrastructure that cities in China increasingly prioritize for development. However, there is a lack of effective risk assessment methods for subway station and line siting. To address this gap, this paper uses the subway system in Kunming, China, as a case study, establishing a subway site risk evaluation framework (SIRE-BAF) that integrates three dimensions: balance (B), attractiveness (A), and financing mode (F). An extended NP-RV model is proposed to assess the balance (or imbalance) characteristics of subway stations based on sub-dimensions of traffic supply, land use, and urban vitality. Findings indicate that (1) the balance (or imbalance) of subway stations is distinctly distributed along the line and simultaneously exhibits a spatial pattern radiating from the urban core to the periphery. (2) Stations with high urban vitality and minimal imbalance are highly attractive and tend to face “undersupply” during operation, whereas stations with lower attractiveness are more prone to “oversupply”. A higher level of BAF coupling coordination suggests a more suitable subway site selection and lower investment risk, while lower coupling coordination indicates increased risk. (3) Excessive reliance on the “subway + real estate” model, without considering urban vitality, may lead to high vacancy rates and reduced efficiency in subway service. This paper further assesses the site selection risks for the proposed Kunming subway. This study contributes to risk assessments of existing subway operations and maintenance in Chinese cities, enhances planning rationality and site selection for proposed subways, and holds potential applicability for other cities.

Optimizing renewable energy-based plug-in hybrid electric vehicle charging stations for sustainable transportation in India

India's burgeoning population necessitates innovative transportation solutions, with electric vehicles (EVs) emerging as a locally viable and urgent need. However, a significant obstacle lies in the improper deployment of charging stations, which strains the power distribution system. Recognizing the environmental benefits of Renewable Energy Sources (RES), high-priority buses are now equipped with Plug-in Hybrid Electric Vehicle (PHEV) charging stations, bolstering effective utilization. This study leverages meta-heuristic optimization techniques to propose an efficient allocation strategy for PHEV charging stations powered by RES. The core objective is to establish a cost-effective charging infrastructure while upholding the effective integrity of the network in distribution system. To address these challenges, the study employs meta-heuristic optimization algorithms and optimizes forecasting around sustainable energy systems to achieve desired output. Consequently, the research introduces a novel approach, conceptualizing the distribution of optimal charging stations as a multi-objective problem with added parameters. Furthermore, this study tackles the RES PHEV and charging station site challenge by introducing the innovative Walrus Optimization Algorithm (WaOA), which effectively overcomes issues related to slow convergence and local optima. Experimental findings demonstrate the superiority of the proposed model in terms of minimizing the cost function. This research offers a promising pathway toward sustainable transportation in India's evolving landscape.

Settings of community engagement: beyond the Janus-faced post-political in ‘neoliberalised’ London

Drawing on an in-depth analysis of the politics of a large-scale urban development in London, as part of a wider comparative project, this paper reconsiders the post-political conclusions of an earlier round of research on large scale developments in Europe. Through a critical re-reading of Jacques Rancière’s analysis and attending to insights from wider accounts of urban politics from the majority urban world, including our own comparative research on Johannesburg and Shanghai, the paper considers the potential of political contestation and engagement. Concepts such as ‘insurgent citizens’, the ‘arts of citizenship’, and the multiple roles of the state, provide focus for a nuanced assessment of the achievements and potential of residents’ and wider community engagements in planning in the case of Old Oak, north-west London. First designated as an ‘Opportunity Area’ and then a Mayoral Development Corporation, substantial investment has been made by the Mayor of London in stimulating development around the site of a new High Speed Train station at Old Oak. Community mobilisation took the form of a network of existing organisations and residents across a large area, encompassing a diverse population and including large swathes of railway and industrial land, making connections were hard to forge. The ambition of the Mayoral Development Corporation created a range of different settings for progressing planning and development, from open engagements with communities over planning visions, to informal and restricted discussions of development applications, secretive master planning initiatives, and highly legalistic procedures of formal inspection. Disaggregating the unitary assessment of politics embedded in post-political analysis, the paper identifies the series of ‘settings’ in which different combinations of political openings, closures and opportunities for advancing concerns of community-based movements can be located. The analysis signposts scope for a more targeted political ambition, based on a community-based strategic assessment of the fragmentation of planning practice. Notably, the negotiations to determine planning gain between planners and developers were identified by the community groups as crucial to shaping development outcomes, with the growing demand to open these to public scrutiny.

Design and Implementation of a Smart Wireless Access Point for A Gas Station (SWAP-GS)

The gas distribution sector is a good fit for wireless communications, especially considering how often distribution facilities are located in distant areas. The underlying communications infrastructure needs to be extremely dependable, with a resilient system that links sensors and controls throughout a vast field area network, when working with accumulated and real-time data. The resulting detail assists managers in creating and modifying business processes, managing the station site fully, and increasing operational efficiency. A wireless gas station offers an architecture based on Wi-Fi standards for applications that track and collect data all the way down sto the sensor level. The goal of the research was to install a wireless infrastructure network at a service station. When used in a gas station, plant, enable users to access real-time information, exchange and share sensor readings from the access point, and develop a smart wireless access point system with higher secure encryption than the generic wireless network. The NodeMCU microcontroller, which broadcasts the real-time data to the clients, receives inputs from a temperature, pressure, and humidity sensor. This allows the system to do such activities. It was believed that the built wireless infrastructure will enhance the existing LAN infrastructures. A few basic prerequisites are taken into account. First and foremost, a microcontroller, a sensor unit, software design, and compliance with IEEE 802.11 standards were required.

Multi-Objective Optimization of Urban Gas Station Site Selection Under Territorial Spatial Planning Constraints

The traditional process for selecting urban gas station sites often emphasizes economic benefits and return on investment, frequently overlooking mandatory and guiding constraints established by territorial spatial planning regulations. This neglect can compromise the effective layout and future growth of cities, potentially affecting their long-term development. To address this issue, this study develops a systematic framework for urban gas station site selection that integrates both mandatory and guiding constraints. By conducting detailed analyses of feasible construction areas and fuel demand, the framework quantifies relevant indicators and establishes a comprehensive index system for site selection. A multi-objective optimization model employing genetic algorithms was utilized to maximize fuel demand coverage, minimize inter-station redundancy, and achieve optimal site coverage. This framework was applied to the central urban area of Lishui City, China, as a case study. The site selection schemes achieved a coverage rate exceeding 90%, an inter-station redundancy rate around 30%, and a demand coverage rate surpassing 90%, optimizing the key objectives. Compared to traditional methods that often ignore territorial spatial planning constraints, this framework effectively avoids conflicts with urban planning and regulatory requirements. It enhances infrastructure coordination, supports environmental sustainability, and exhibits strong adaptability to diverse urban contexts, thus offering valuable support for practical decision-making.

A small, old, and slightly rough mirror: Encountering traumatic experiences in Nanjing Museum of the Site of Lijixiang Comfort Stations

AbstractThis paper investigates how traumatic events are curated and narrated in the Nanjing Museum of the Site of Lijixiang Comfort Stations. Drawing on narrative therapy in museology, the paper offers a perspective for understanding and interpreting the narrative practice in public space. It follows the reconstruction of narrative structures through a variety of viewpoints, including spatial narratives, exhibition narratives, public engagement in response to traumatic memories, and the logical and emotional encounters in museums. Visitors' learning of traumatic experiences in the museum shows a kind of indissoluble connection, a type of empathetic mutual understanding, a kind of community engagement that contributed to the recovery, and a kind of responsibility to prevent such traumatic events from happening again.

АНАЛИЗ ВЛИЯНИЯ МЕТЕОРОЛОГИЧЕСКИХ УСЛОВИЙ НА ПРОДУКТИВНОСТЬ ЯРОВОЙ ПШЕНИЦЫ В 2023 ГОДУ НА ПРИМЕРЕ МЕТЕОРОЛОГИЧЕСКОЙ СТАНЦИИ ТАЙЫНША СЕВЕРО-КАЗАХСТАНСКОЙ ОБЛАСТИ

According to the results of the assessment about possible agricultural losses due to climate change, conducted as part of the preparation of the Seventh National Communication of the Republic of Kazakhstan on Climate Change, including for the North Kazakhstan region, where, according to the forecast, by 2050 a decrease in moisture supply during the growing season by 11...16 % and an increase in climate aridity by 10...15 % relative to current indicators are expected. As a result of such changes, this may lead to a decrease in the yield of spring wheat by 30...40 %. The aim of this study was to establish the relationship between the yield of Aviada spring wheat and meteorological conditions at the observation site of the Taiynsha meteorological station in the North Kazakhstan region for 2023. For this purpose, the actual meteorological parameters for the specified year were studied, such as temperature and precipitation, hydrothermal moisture coefficient (HTC), productive moisture reserves in the soil, sums of effective temperatures, as well as the growth and development characteristics of spring wheat of the Aviada variety during the vegetation period of 2023, its yield.It was found that insufficient precipitation during the critical phases of spring wheat development created stressful conditions during the grain ripening period, and, as a result, affected its yield.In addition, the shift of summer precipitation to August...September led to crop losses during and after harvesting. This article represents the results of the research internship that took place at Taiynsha meteorological station from May to August 2023.

A new fuzzy location-based approach for fire station site selection in Tehran

A new fuzzy location-based approach for fire station site selection in Tehran

Large aperture microphone array measurement at operating airport for sound source model creation of J-FRAIN

In 2022, authors conducted microphone array measurements at an operating airport to create sound source models for commercial aircraft based on the noise prediction framework J-FRAIN. A similar measurement was also performed by our colleagues in 2019, but it was a trial to establish the concept of the framework and was done using a microphone array in which the number of microphones was reduced to about half. In order to improve the accuracy of the sound source models, the microphone array with a 30-meter diameter consisting of 195 microphones mounted on the ground was used in 2022. Recording-based simultaneous noise measurement using sound level meters was also performed around the airport to validate prediction results in terms of time histories of 1/3 octave band sound pressure levels. This paper describes an overview of the microphone array measurements conducted in 2022 and a case study of noise prediction around the airport using sound source models created from the data of microphone array measurements conducted in 2022. Predicted results are compared with 1/3 octave band data measured using sound level meters mounted at a height of 4 m above the ground at sites of noise monitoring stations around the airport.

Characterizing Egyptian National Seismic Network station sites using genetic optimization for microtremor data inversion

Characterizing Egyptian National Seismic Network station sites using genetic optimization for microtremor data inversion

Particle swarm optimization based on data driven for EV charging station siting

Charging stations are an important support facility for electric vehicles (EVs). Nowadays, the EV industry is developing rapidly, however, the imperfect construction of charging stations or the unreasonable choice of location has seriously reduced the desire of people to buy EVs and led to the problem of difficult charging of EVs in many areas. At present, the research field of EV charging station siting suffers from the inability to quickly and accurately calculate the optimal solution for charging station siting. In this regard, a particle swarm optimization based on deep neural networks modified boundaries (DNNMBPSO) is proposed for solving the problem. DNNMBPSO reduces the convergence value of the objective function by applying deep learning to modify the boundary of the particle swarm optimization. DNNMBPSO is an algorithm that combines heuristic and data driven. In this study, DNNMBPSO is applied for siting study in a system having 50 alternative points, 500 alternative points, and 1000 alternative points and a case of siting of electric vehicle charging stations in Nanning, Guangxi, China. The convergence value of the DNNMBPSO-based objective function is found to be at least 5.5 %, 1.7 %, 8.23 % and 14.7 %, lower compared to genetic algorithms, African vulture optimization algorithm, particle swarm optimization, and grey wolf optimization algorithms, respectively. Traditional heuristic optimization algorithms cannot find optimal solutions in large-scale systems, while DNNMBPSO shows feasibility in large-scale systems.

Fabrication of Active Z-Scheme Sr2MgSi2O7: Eu2+, Dy3+/COF Photocatalyst for Round-the-Clock Efficient Removal of Total Cr.

Photoreduction is recognized as a desirable treatment method for hexavalent chromium (Cr(VI)). However, it has been limited by the intermittent solar flux and limited light absorption. In this work, a novel Z-scheme photocatalyst combining a covalent organic framework (COF) with Eu2+, Dy3+ co-doped Sr2MgSi2O7 (Sr2MgSi2O7:Eu2+, Dy3+) is synthesized, which shows the high spectral conversion efficiency and works efficiently in both light irradiation and dark for Cr(VI) reduction. Sr2MgSi2O7:Eu2+, Dy3+ serves as both an electron transfer station and active sites for COF molecule activation, thus resulting in 100% photoreduction of Cr(VI) (50 mL, 10 mg/L) with high light stability and over 1 h dark activity. Moreover, the XPS and FT-IR analyses reveal the existence of functional groups (Si-OH on Sr2MgSi2O7:Eu2+, Dy3+, and -NH- on COFTP-TTA) on the composited catalyst as active sites to adsorb the resultant Cr(III) species, demonstrating a synergistic effect for total Cr removal. This work provides an alternative method for the design of a round-the-clock photocatalyst for Cr(VI) reduction, allowing a versatile solid surface activation for establishing a more energy efficient and robust photocatalysis process for Cr pollution cleaning.

Local earthquake monitoring with a low-cost seismic network: a case study in Nepal

Seismic monitoring matters both for research and for populations living in areas of seismic hazard; however, it comes with a cost that is not fully affordable for developing countries. Compared to classical approaches with very quiet sites and high-quality instrumentation, it is therefore worth investigating low-cost seismic networks and how well they perform at detecting and characterizing seismicity. We analyze 1 year of seismic data from an educational seismology network in Nepal, create our own earthquake catalog, and compare it to the publicly available national observatory catalog. We find that despite the noisier seismic station sites, the overall results are comparable and all the main features relevant for seismicity are found. We present quantitative analyses of locations, magnitudes and their frequency distribution in our catalog, as well as differences with the observatory catalog. Differences between the two catalogs primarily stem from the respective network geometries and their coverage, as well as daytime noise level differences. We conclude that if properly planned and installed, low-cost seismic networks are a viable, feasible and significant complement to monitor seismic activity.Graphical

Response of actinidia deliciosa plants to abiotic stress in the Russian subtropical zone

The article presents a general description of the culture of Actinidia deliciosa, grown in the humid subtropics of Russia. The work was carried out since 2017 at the site of the Adler experimental station of the branch of the Federal Research Center of the N.I. Vavilov All-Russian Institute of Plant Genetic Resources and in the laboratory of plant physiology and biochemistry of the Subtropical Scientific Center of the Russian Academy of Sciences, Sochi. Physiological and biochemical indicators were determined that reflect the resistance of actinidia plants planted in 1988 to environmental stress factors to identify the most adapted varieties to the conditions of the humid subtropics of the Krasnodar Territory. The soil is alluvial meadow with low humus. The varieties studied were late ripening Hayward; Ellison, Abbott and Bruno – early; Monty – medium; Tomuri (pollinator of kiwi female varieties). The indicator organ is physiologically mature actinidia leaves, which were selected from May to September against the backdrop of a natural increase in air temperature. Water deficit was in 2022–2023 is 29.62–36.46%, the minimum is for the Ellison and Monty varieties (29.62–30.21), the maximum is Abbott (36.46%). The dry matter content is 25.47–35.53%, the water content of leaf blades is 46.09-62.66%. The Monti, Hayward and Tomuri varieties are the most resistant to the weather and climatic conditions of the Russian subtropical zone.

Electric vehicle charging station siting planning model considering distribution grids

Electric vehicle charging station siting planning model considering distribution grids

Optimal Urban EV Charging Station Site Selection and Capacity Determination Considering Comprehensive Benefits of Vehicle-Station-Grid

Optimal Urban EV Charging Station Site Selection and Capacity Determination Considering Comprehensive Benefits of Vehicle-Station-Grid

Quantifying Aspect‐Dependent Snowpack Response to High‐Elevation Wildfire in the Southern Rocky Mountains

AbstractIncreasing wildfire frequency and severity in high‐elevation seasonal snow zones presents a considerable water resource management challenge across the western United States (U.S.). Wildfires can affect snowpack accumulation and melt patterns, altering the quantity and timing of runoff. While prior research has shown that wildfire generally increases snow melt rates and advances snow disappearance dates, uncertainties remain regarding variations across complex terrain and the energy balance between burned and unburned areas. Utilizing paired in situ data sources within the 2020 Cameron Peak burn area on the Front Range of Colorado, U.S., during the 2021–2022 winter, we found no significant difference in peak snow water equivalent (SWE) magnitude between burned and unburned areas. However, the burned south aspect reached peak SWE 22 days earlier than burned north. During the ablation period, burned south melt rates were 71% faster than unburned south melt rates, whereas burned north melt rates were 94% faster than unburned north aspects. Snow disappeared 7–11 days earlier in burned areas than unburned areas. Net energy differences at the burned and unburned weather station sites were seasonally variable, the burned area snowpack lost more net energy during the winter, but gained more net energy during the spring. Increased incoming shortwave radiation at the burned site was 6x more impactful in altering the net shortwave radiation balance than the decline in surface albedo. These findings emphasize the need for post‐wildfire water resource planning that accounts for aspect‐dependent differences in energy and mass balance to accurately predict snowpack storage and runoff timing.

Soybean response to high‐speed planting in Mississippi

AbstractMississippi soybean [Glycine max (L.) Mer.] producers are under pressure to plant as much land as possible within narrow planting windows. The 5‐year average planting progress is 45% of the total at the end of the optimal soybean planting window. New metering and seed delivery technology claims faster planting without sacrificing singulation, stand, or yield, but these tools need to be validated before recommendation. This study aimed to quantify soybean response to planting speeds using a precision planter (John Deere MaxEmerge 2 row units retrofitted with Ag Leader SureSpeed and SureForce) and a mechanical planter (John Deere 1700 ground‐driven mechanical planter equipped with eSet meters) for a total of 7 site‐years across Mississippi. In 2022, both planters were evaluated at four actual ground speeds of 7.9, 10.8, 13.5, and 16.4 km h−1 in a 2 × 4 factorial design. The experimental design was modified in 2023, where the mechanical planter served as the current farmer practice check at 9.7 km h−1and the precision planter speeds were 9.7, 14.5, and 17.7 km h−1 at research station sites and 9.7 and 14.5 km h−1 at an on‐farm site. Across sites, increased planting speed generally increased plant spacing, in‐row spacing variability, and decreased plant population. However, increased speed did not affect soybean yield. The precision planter at 17.7 km h−1 was no different from the mechanical planter in terms of soybean plant population, spacing, and yield in 2023. Results suggest soybean producers can plant soybean at 17.7 km h−1 without compromising yield.