scholarly journals Development of electric road transport: simulation modelling

Baltic Region ◽  
2020 ◽  
pp. 118-139
Author(s):  
D. Yu. Katalevsky ◽  
T. R. Gareev
Keyword(s):  
Electric Vehicles ◽  
Regional Scale ◽  
Demand Forecasting ◽  
Simulation Modelling ◽  
Spatial Optimization ◽  
Transport Infrastructure ◽  
Technological Advancement ◽  
Electric Transport ◽  
Test Bed ◽  
Proposed Model

Electric transport is rapidly gaining popularity across the world. It is an example of technological advancement that has multiple consequences for regional economies, both in terms of the adaptation of production, transport and energy systems and their spatial optimization. The experience of leading economic regions, including countries of the Baltic Sea region, shows that electric transport can potentially substitute traditional transport technologies. Based on an authentic model of system dynamics, the authors propose a new approach to simulation modelling of the dissemination of electric vehicles in a given region. The proposed model allows the authors to take into account the key systemic feedback loops between the pool of electric vehicles and the charging infrastructure. In the absence of data required for the econometric methods of demand forecasting, the proposed model can be used for the identification of policies stimulating the consumer demand for electric vehicles in regions and facilitating the development of the electric transport infrastructure. The proposed model has been tested using real and simulated data for the Kaliningrad region, which due to its specific geographical location, is a convenient test-bed for developing simulation models of a regional scale. The proposed simulation model was built via the AnyLogic software. The authors explored the capacity of the model, its assumptions, further development and application. The proposed approach to demand forecasting can be further applied for building hybrid models that include elements of agent modelling and spatial optimization.

scholarly journals On the Issue of Regulatory Support for Passenger Electric Vehicles Operation

2020 ◽  
Vol 18 (1) ◽  
pp. 196-211
Author(s):  
M. A. Kudryashov ◽  
A. V. Prokopenkov ◽  
R. S. Ayriev
Keyword(s):  
Electric Vehicles ◽  
Environmentally Friendly ◽  
Economic Assessment ◽  
Intermediate Stage ◽  
Transport Infrastructure ◽  
Rolling Stock ◽  
Electric Transport ◽  
Electric Bus ◽  
Environmental Goals ◽  
Charging Stations

The article provides the results of an intermediate stage of research on development of a project to create infrastructure for operation of highly environmentally friendly electric vehicles. The transition to electric transport is one of the promising methods to solve the problem of emissions and achieve environmental goals. An electric bus is a relatively new type of rolling stock, requiring a balanced and objective justification for selection of certain possible options for technical, technological, economic and other aspects of organisation of its operation. To achieve the goal of developing a project to create infrastructure for operation of environmentally friendly electric vehicles, an initial analysis of legal acts, technical characteristics of electric buses and the parking and on route infrastructure approaches to organizing transportation by electric buses with various charging concepts was performed. The analysis of the concepts of charging electric bus batteries allowed to divide them into 5 classes and group into 3 groups according to charging speed. An analysis of the required infrastructure for operation of electric buses showed that conceptually there are 2 types of charging stations. The calculations and evaluation of various options for organizing operation of electric buses on a fixed route with various concepts of charging were performed. A necessary direction for further research is economic assessment of operation of electric buses with various charging concepts and the necessary transport infrastructure. The methods used include analysis, evaluation of previously performed analytical studies, legal acts and a synthesis of domestic and foreign experience.

scholarly journals Usage of the Pareto Fronts as a Tool to Select Data in the Forecasting Process—A Short-Term Electric Energy Demand Forecasting Case

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3204
Author(s):  
Michał Sabat ◽  
Dariusz Baczyński
Keyword(s):  
Energy Demand ◽  
Demand Forecasting ◽  
Electric Energy ◽  
Forecasting Model ◽  
Short Term ◽  
Complex Evaluation ◽  
Proposed Model ◽  
Energy Demand Forecasting ◽  
Pareto Fronts ◽  
Naive Approach

Transmission, distribution, and micro-grid system operators are struggling with the increasing number of renewables and the changing nature of energy demand. This necessitates the use of prognostic methods based on ever shorter time series. This study depicted an attempt to develop an appropriate method by introducing a novel forecasting model based on the idea to use the Pareto fronts as a tool to select data in the forecasting process. The proposed model was implemented to forecast short-term electric energy demand in Poland using historical hourly demand values from Polish TSO. The study rather intended on implementing the range of different approaches—scenarios of Pareto fronts usage than on a complex evaluation of the obtained results. However, performance of proposed models was compared with a few benchmark forecasting models, including naïve approach, SARIMAX, kNN, and regression. For two scenarios, it has outperformed all other models by minimum 7.7%.

Shared Autonomous Vehicle System Design for Battery Electric Vehicle (BEV) and Fuel Cell Electric Vehicle (FCEV)

2021 ◽  
Author(s):  
Ungki Lee ◽  
Sunghyun Jeon ◽  
Ikjin Lee
Keyword(s):  
Fuel Cell ◽  
System Design ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Proton Exchange ◽  
Battery Electric Vehicle ◽  
Test Bed ◽  
Alternative Fuel Vehicles ◽  
Total Cost ◽  
Fuel Cell Electric Vehicle

Abstract Shared autonomous vehicles (SAVs) encompassing autonomous driving technology and car-sharing service are expected to become an essential part of transportation system in the near future. Although many studies related to SAV system design and optimization have been conducted, most of them are focused on shared autonomous battery electric vehicle (SABEV) systems, which employ battery electric vehicles (BEVs) as SAVs. As fuel cell electric vehicles (FCEVs) emerge as alternative fuel vehicles along with BEVs, the need for research on shared autonomous fuel cell electric vehicle (SAFCEV) systems employing FCEVs as SAVs is increasing. Therefore, this study newly presents a design framework of SAFCEV system by developing an SAFCEV design model based on a proton-exchange membrane fuel cell (PEMFC) model. The test bed for SAV system design is Seoul, and optimization is conducted for SABEV and SAFCEV systems to minimize the total cost while satisfying the customer wait time constraint, and the optimization results of both systems are compared. From the results, it is verified that the SAFCEV system is feasible and the total cost of the SAFCEV system is even lower compared to the SABEV system. In addition, several observations on various operating environments of SABEV and SAFCEV systems are obtained from parametric studies.

scholarly journals Photovoltaic Actuated Induction Motor for Driving Electric Vehicle

2019 ◽  
Vol 8 (6S3) ◽  
pp. 1612-1614
Keyword(s):  
Induction Motor ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Power Electronic ◽  
System Efficiency ◽  
Voltage Ripple ◽  
Proposed Model ◽  
Reducing Costs ◽  
Reducing Stress ◽  
Efficiency And Reliability

The paper depicts about the photovoltaic actuated induction motor for driving electric vehicle, helps in improving the efficiency of electric vehicles, the advance “power electronic interface” is used. System efficiency and reliability are improved by this proposed idea, and current or voltage ripple can be effectively reduced. Using this proposed model reduces the component’s dimensions (active and passive), thus reducing costs and this technology reducing stress on switching devices. The designing and analysis of proposed model is done by using MATLAB / Simulink.

Electricity demand forecasting using fuzzy hybrid intelligence-based seasonal models

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mehdi Khashei ◽  
Fatemeh Chahkoutahi
Keyword(s):  
Electricity Markets ◽  
Demand Forecasting ◽  
Load Forecasting ◽  
Multilayer Perceptrons ◽  
Modeling Tools ◽  
Content Type ◽  
Proposed Model ◽  
Hybrid Intelligence ◽  
Electricity Load ◽  
Electricity Load Forecasting

Purpose The purpose of this paper is to propose an extensiveness intelligent hybrid model to short-term load electricity forecast that can simultaneously model the seasonal complicated nonlinear uncertain patterns in the data. For this purpose, a fuzzy seasonal version of the multilayer perceptrons (MLP) is developed. Design/methodology/approach In this paper, an extended fuzzy seasonal version of classic MLP is proposed using basic concepts of seasonal modeling and fuzzy logic. The fundamental goal behind the proposed model is to improve the modeling comprehensiveness of traditional MLP in such a way that they can simultaneously model seasonal and fuzzy patterns and structures, in addition to the regular nonseasonal and crisp patterns and structures. Findings Eventually, the effectiveness and predictive capability of the proposed model are examined and compared with its components and some other models. Empirical results of the electricity load forecasting indicate that the proposed model can achieve more accurate and also lower risk rather than classic MLP and some other fuzzy/nonfuzzy, seasonal nonseasonal, statistical/intelligent models. Originality/value One of the most appropriate modeling tools and widely used techniques for electricity load forecasting is artificial neural networks (ANNs). The popularity of such models comes from their unique advantages such as nonlinearity, universally, generality, self-adaptively and so on. However, despite all benefits of these methods, owing to the specific features of electricity markets and also simultaneously existing different patterns and structures in the electrical data sets, they are insufficient to achieve decided forecasts, lonely. The major weaknesses of ANNs for achieving more accurate, low-risk results are seasonality and uncertainty. In this paper, the ability of the modeling seasonal and uncertain patterns has been added to other unique capabilities of traditional MLP in complex nonlinear patterns modeling.

An Integrated Methodology for Evaluation of Electric Vehicles Under Sustainable Automotive Environment

2019 ◽  
pp. 41-62 ◽  
Author(s):  
Tapas Kumar Biswas ◽  
Željko Stević ◽  
Prasenjit Chatterjee ◽  
Morteza Yazdani
Keyword(s):  
Electric Vehicles ◽  
Sustainability Assessment ◽  
Model Performance ◽  
Compromise Solution ◽  
Holistic Model ◽  
Proposed Model ◽  
Criteria Importance ◽  
Assessment Problems ◽  
Selection Of

In this chapter, a holistic model based on a newly developed combined compromise solution (CoCoSo) and criteria importance through intercriteria correlation (CRITIC) method for selection of battery-operated electric vehicles (BEVs) has been propounded. A sensitivity analysis has been performed to verify the robustness of the proposed model. Performance of the proposed model has also been compared with some of the popular MCDM methods. It is observed that the model has the competency of precisely ranking the BEV alternatives for the considered case study and can be applied to other sustainability assessment problems.

A Hybrid Heuristic for QoS Aware Matching of User's Job and Virtual Machines in Cloud Environment

2018 ◽  
Vol 11 (2) ◽  
pp. 88-109
Author(s):  
Devki Nandan Jha ◽  
Deo Prakash Vidyarthi
Keyword(s):  
Virtual Machines ◽  
Service Providers ◽  
Cloud Provider ◽  
Technological Advancement ◽  
Cloud Platform ◽  
Analytical Hierarchical Process ◽  
Hybrid Heuristic ◽  
Proposed Model

Cloud computing is a technological advancement that provides services in the form of utility on a pay-per-use basis. As the cloud market is expanding, numerous service providers are joining the cloud platform with their services. This creates an indecision amongst the users to choose an appropriate service provider especially when the cloud provider provisions diverse type of virtual machines. The problem becomes more challenging when the user has different jobs requiring specific quality of service. To address the aforementioned problem, this article applies a hybrid heuristic using College Admission Problem and Analytical Hierarchical Process for stable matching of the users' job with the cloud's virtual machines. The case study depicts the effectiveness of the proposed model.

scholarly journals Coordinated Dispatch of Integrated Energy Systems Considering the Differences of Multiple Functional Areas

2019 ◽  
Vol 9 (10) ◽  
pp. 2103 ◽  
Author(s):  
Liusong Li ◽  
Weichao Jin ◽  
Meiyan Shen ◽  
Li Yang ◽  
Fei Chen ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Electric Vehicles ◽  
Transmission Lines ◽  
Distribution System ◽  
Energy Systems ◽  
Actual Distribution ◽  
Integrated Energy Systems ◽  
Transmission Distance ◽  
Proposed Model ◽  
Functional Areas

A large amount of wind turbine power and photovoltaic power is abandoned in many areas with abundant renewable energy due to thermal-electric coupling, inadequate local consumption capacity, and limited capacity of transmission lines, etc. To solve the above problems, a coordinated dispatching method for integrated energy systems is proposed in this paper. Firstly, the spatiotemporal characteristics of diversified loads in multiple functional areas are introduced, including the inertia and elasticity of heating/cooling loads, the spatiotemporal distribution of electric vehicles, and the optimum transmission distance of diversified loads, etc. Secondly, a coordinated dispatching model of integrated energy systems is proposed, which considers the differences of multiple functional areas and various forms of energy systems. Finally, an actual distribution system in Jianshan District, Haining, Zhejiang Province of China is investigated for demonstrating the effectiveness of the proposed model. The results illustrate that the proposed model could effectively improve the consumption rate of renewable energy and reduce the volatility of renewable energy by considering the coordination of electric vehicles, tie lines, and heating/cooling systems in multiple functional areas.

scholarly journals Dynamic Scheduling Model of Bike-Sharing considering Invalid Demand

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Liu He ◽  
Tangyi Guo ◽  
Kun Tang
Keyword(s):  
Optimization Model ◽  
Dynamic Scheduling ◽  
Demand Forecasting ◽  
Optimal Solution ◽  
Coupling Model ◽  
Service Level ◽  
Demand Prediction ◽  
Dynamic Relationship ◽  
Proposed Model ◽  
Bike Sharing

System resources allocation optimization through dynamic scheduling is key to improving the service level of bike-sharing. This study innovatively introduces three types of invalid demand with negative effect including waiting, transfer, and abandoning, which consists of the total demand of bike-sharing system. Through exploring the dynamic relationship among users’ travel demands, the quantity and capacity of bikes at the rental points, the records of bicycles borrowed and returned, and the vehicle scheduling schemes, a demand forecasting model for bike-sharing is established. According to the predicted bikes and the maximum capacity limit at each rental point, an optimization model of scheduling scheme is proposed to reduce the invalid demand and the total scheduling time. A two-layer dynamic coupling model with iterative feedback is obtained by combining the demand prediction model and scheduling optimization model and is then solved by Nicked Pareto Genetic Algorithm (NPGA). The proposed model is applied to a case study and the optimal solution set and corresponding Pareto front are obtained. The invalid demand is greatly reduced from 1094 to 26 by an effective scheduling of 3 rounds and 96 minutes. Empirical results show that the proposed model is able to optimize the resource allocation of bike-sharing, significantly reduce the invalid demand caused by the absence of bikes at the rental point such as waiting in a place, walking to other rental points, and giving up for other travel modes, and effectively improve the system service level.

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