• Energy Research
• engineering and technology close
• 11. Sustainability close
• Transport Research close

Introduction. The article presents an analysis of researches on the operation of public transport vehicles with an electric drive. Electric buses have been tested in megacities, and despite the advantages, problems were identi- fied both in the selection of the charging type, technological features and with the availability and operation of the charging infrastructure. The operation process is associated with a number of technical restrictions, which in prac- tice make it difficult to select routes for the electric bus operation. The aim of the study is to develop an algorithm for selecting a rational regular urban route for the electric bus operation and to test it on the example of the route network of Tyumen.Materials and methods. A structural diagram of the factors influencing the selection of the route for the electric bus operation has been formed. As a result of processing expert assessments, the most significant factors were identified. The diagram of the interconnections of these factors is identified and limitations for the algorithm are for- mulated based on the theory of systems analysis. The algorithm for selecting the rational regular urban route for the electric bus operation has been developed. It enables creating the simulation model for selecting a rational regular urban route for the operation of an electric bus.Results. The diagram of factors influencing the selection of a rational regular urban route for the operation of an electric bus, taking into account their mutual relations, has been formed. The algorithm and simulation model for se- lecting a rational regular urban route for the operation of an electric bus has been developed. Several urban routes in Tyumen were assessed for the rationality of the introduction of electric buses.Discussion and conclusions. Evaluation of five regular urban routes in Tyumen using the developed algorithm and the simulation model revealed three rational routes, and also showed the inefficiency of the other two. It due to the discrepancy between the duration of the charging session and breaks in operation, as well as the insufficient charge level of the traction battery to ensure the required autonomous movement of the vehicle. In the course of the continuation of these studies, the developed algorithm will be supplemented with the stage of economic assess- ment of routes for the operation of electric buses.

Twenty-minute neighbourhoods highlight the importance of well-connected and mixed-used neighbourhoods and communities with proximate access to employment, essential services, public transport, and open spaces. Shorter distances together with re-prioritised public spaces encourage more active transport choices, resulting in public health benefits and reduced environmental pollution. Higher liveability brought about by mixed-use developments enables people to have equitable access to local facilities, amenities, and employment opportunities, promoting vibrancy, social cohesion, and intergenerational connections. The attributes of 20-minute neighbourhoods also combine to create places, that are acknowledged as friendly for all ages, address changing needs across the life course, and provide better support for the ageing population. Furthermore, there are indications that 20-minute neighbourhoods may be more resilient against many of the negative impacts of stringent public health protocols such as those implemented in periods of lockdown during the Covid-19 pandemic. In this article, we evaluate and compare planning policies and practices aimed at establishing 20-minute neighbourhoods in Melbourne (Australia) and Scotland (the UK). Using case studies, we discuss similarities and differences involved in using place-based approaches of 20-minute neighbourhoods to address 21st-century challenges in key areas of health and wellbeing, equity, environmental sustainability, and community resilience.

Route game is recognized as an effective method to alleviate Braess’ paradox, which generates a new traffic congestion since numerous vehicles obey the same guidance from the selfish route guidance (such as Google Maps). The conventional route games have symmetry since vehicles’ payoffs depend only on the selected route distribution but not who chose, which leads to the precise Nash equilibrium being able to be solved by constructing a special potential function. However, with the arrival of smart cities, the real-time of route schemes is more of a concerned of engineers than the absolute optimality in real traffic. It is not an easy task to re-construct the new potential functions of the route games due to the dynamic traffic conditions. In this paper, compared with the hard-solvable potential function-based precise method, a matched Q-learning algorithm is designed to generate the approximate Nash equilibrium of the classic route game for real-time traffic. An experimental study shows that the Nash equilibrium coefficients generated by the Q-learning-based approximate solving algorithm all converge to 1.00, and still have the required convergence in the different traffic parameters.

The growing number of electric vehicles in recent years is observable in almost all countries. The country’s energy transition should accompany this rise in electromobility if it is currently generated from non-renewable sources. Only electric vehicles powered by renewable energy sources can be considered zero-emission. Therefore, it is essential to conduct interdisciplinary research on the feasibility of combining energy recovery/generation structures and testing the energy consumption of electric vehicles under real driving conditions. This work presents a comprehensive approach for evaluating the energy consumption of a modern public building–electric vehicle system within a specific location. The original methodology developed includes surveys that demonstrate the required mobility range to be provided to occupants of the building under consideration. In the next step, an energy balance was performed for a novel near-zero energy building equipped with a 199.8 kWp photovoltaic installation, the energy from which can be used to charge an electric vehicle. The analysis considered the variation in vehicle energy consumption by season (winter/summer), the actual charging profile of the vehicle, and the parking periods required to achieve the target range for the user.

Purpose. In modern conditions of energy consumption growth and a rapid increase in energy prices the actual problem is the development and implementation of energy efficiency programs and resource-saving conversion in to a source to provide the needs of industry and municipal power. The paper aims to solve the urgent problem of energy saving and efficient use of fuel-energy ones and heat supply system optimization on the basis of Uman National University of Horticulture (UNUH). Methodology. The work investigated the process of heating and hot water supply in the course of 2007-2015 years. Implementation of current problems of energy saving is grounded on the scientific-practical and efficient assurance of fuel and energy usage. At the same time energy-saving technologies are viewed as a priority direction of the energy sector development, reduction of man-induced impact on the environment and as a way of improving the competitiveness of the national economy. Findings. Statistical data acquisition and analyzing of gas flow and outside air temperature for nine years was carried out. On the basis of this analysis, the problem was identified and specific targets for its solutions were set. Originality. Scientific novelty lies in solving the problem of energy saving and efficient use of fuel resources in Ukraine through the use of a systematic approach, the methodology development of efficient use of different fuels and optimization of local heating operation, applying contemporary automation and control systems. Firstly it was in detail analyzed and conducted the comprehensive assessment of various factors influence on energy conservation. It takes into account the human factor, professionalism and responsibility of the operators of boilers and their superiors, as well as the relevant control services. Practical value. For UNUH campus hybrid use of solid fuel and gas boilers was carried out. Decentralization of the university heating system has been conducted through the restoration of 350 individual heating systems in residential buildings, remote departments and campus dormitories. The conclusions propose the list of activities upon the real economy of fuel and energy resources, and measures to overcome the economic and political crisis in the country.

Efficient parking tends to be challenging in most large cities in China. Drivers often spend substantial amounts of time looking for parking lots while driving at low speeds, thereby resulting in interference with road traffic. This paper focuses on efficiently allocating parking spaces to the demanders. A double-objective model is proposed that considers both the utilizing rate and the walking distance. First, managers want to utilize parking resources fully. Therefore, they tend to prioritize the efficient distribution of parking spaces in response to parking demands. However, demanders typically choose parking spaces according to convenience. The second objective is the acceptable walking distance from the parking space to the destination. The particle swarm optimization (PSO) algorithm is used to solve this model. We collected parking demand and supply data in a central business district (CBD) of Harbin in China and evaluated the feasibility of the model. The results demonstrate that the proposed model increases the occupying rates of parking lots in residential zones while decreasing the walking distance. The shared use of parking spaces maximizes the utility and alleviates the shortage of parking spaces in downtown.

Medium and heavy-duty battery electric trucks (BETs) may play a key role in mitigating greenhouse gas (GHG) emissions from road freight transport. However, technological challenges such as limited range and cargo carrying capacity as well as the required charging time need to be efficiently addressed before the large-scale adoption of BETs. In this study, we apply a geospatial data analysis approach by using a battery electric vehicle potential (BEVPO) model with the datasets of road freight transport surveys for analyzing the potential of large-scale BET adoption in Finland and Switzerland for trucks with gross vehicle weight (GVW) of over 3.5 t. Our results show that trucks with payload capacities up to 30 t have the most potential for electrification by relying on the currently available battery and plug-in charging technology, with 93% (55% tkm) and 89% (84% tkm) trip coverage in Finland and Switzerland, respectively. Electric road systems (ERSs) would be essential for covering 51% trips (41% tkm) of heavy-duty trucks heavier than 30 t in Finland. Furthermore, range-extender technology could improve the trip electrification potential by 3–10 percentage points (4–12 percentage points of tkm).