scholarly journals Energy Trading with Electric Vehicles in Smart Campus Parking Lots

2018 ◽  
Vol 8 (10) ◽  
pp. 1749 ◽  
Author(s):  
Mohamed Ahmed ◽  
Young-Chon Kim
Keyword(s):  
Electric Vehicles ◽  
Market Mechanism ◽  
University Campus ◽  
Energy Trading ◽  
Control Center ◽  
Parking Lots ◽  
Electric Vehicle Charging ◽  
Parking Lot ◽  
Demand Information ◽  
Knapsack Algorithm

Energy trading with electric vehicles provides opportunities to eliminate the high peak demand for electric vehicle charging while providing cost saving and profits for all participants. This work aims to design a framework for local energy trading with electric vehicles in smart parking lots where electric vehicles are able to exchange energy through buying and selling prices. The proposed architecture consists of four layers: the parking energy layer, data acquisition layer, communication network layer, and market layer. Electric vehicles are classified into three different types: seller electric vehicles (SEVs) with an excess of energy in the battery, buyer electric vehicles (BEVs) with lack of energy in the battery, and idle electric vehicles (IEVs). The parking lot control center (PLCC) plays a major role in collecting all available offer/demand information among parked electric vehicles. We propose a market mechanism based on the Knapsack Algorithm (KPA) to maximize the PLCC profit. Two cases are considered: electric vehicles as energy sellers and the PLCC as an energy buyer, and electric vehicles as energy buyers and the PLCC as an energy seller. A realistic parking pattern of a parking lot on a university campus is considered as a case study. Different scenarios are investigated with respect to the number of electric vehicles and amount of energy trading. The proposed market mechanism outperforms the conventional scheme in view of costs and profits.

scholarly journals Design and Implementation of a Blockchain-Based Energy Trading Platform for Electric Vehicles in Smart Campus Parking Lots

Energies ◽  
2019 ◽  
Vol 12 (24) ◽  
pp. 4814 ◽  
Author(s):  
Felipe Condon Silva ◽  
Mohamed A. Ahmed ◽  
José Manuel Martínez ◽  
Young-Chon Kim
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Energy Trading ◽  
Parking Lots ◽  
Vehicle Owner ◽  
Blockchain Technology ◽  
Smart Campus ◽  
Physical Infrastructure ◽  
Parking Lot ◽  
Cyber Infrastructure

This paper proposes a blockchain-based energy trading platform for electric vehicles in smart campus parking lots. Smart parking lots are smart places capable of supporting both parking and charging services for electric vehicles. The electric vehicle owner may want to charge energy at a low price and sell it during peak hours at a higher price. The proposed system architecture consists of two layers: the physical infrastructure layer and the cyber infrastructure layer. The physical infrastructure layer represents all of the physical components located in the campus distribution power system, such as electric vehicles charging stations, transformers, and electric feeders, while the cyber infrastructure layer supports the operation of the physical infrastructure layer and enables selling/buying energy among participants. Blockchain technology is a promising candidate to facilitate auditability and traceability of energy transactions among participants. A real case of a parking lot with a realistic parking pattern in a university campus is considered. The system consists of a university control center and various parking lot local controllers (PLLCs). The PLLC broadcasts the electricity demand and the grid price, and each electric vehicle owner decides whether to charge/discharge based on their benefits. The proposed system is implemented on Hyperledger Fabric. Participants, assets, transactions, and smart contracts are defined and discussed. Two scenarios are considered. The first scenario represents energy trading between electric vehicles as sellers and the PLLC as a buyer, while the second scenario involves energy trading between electric vehicles as buyers and the PLLC as a seller. The proposed platform provides profits for participants, as well as enables balancing for the university load demand locally.

scholarly journals A Novel Power Market Mechanism Based on Blockchain for Electric Vehicle Charging Stations

Electronics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 307
Author(s):  
Zhaoxiong Huang ◽  
Zhenhao Li ◽  
Chun Sing Lai ◽  
Zhuoli Zhao ◽  
Xiaomei Wu ◽  
...  
Keyword(s):  
Social Welfare ◽  
Real Time ◽  
Electric Vehicle ◽  
Peak Load ◽  
Market Mechanism ◽  
Double Auction ◽  
Energy Trading ◽  
Charging System ◽  
Electric Vehicle Charging ◽  
System Operator

This work presents a novel blockchain-based energy trading mechanism for electric vehicles consisting of day-ahead and real-time markets. In the day-ahead market, electric vehicle users submit their bidding price to participate in the double auction mechanism. Subsequently, the smart match mechanism will be conducted by the charging system operator, to meet both personal interests and social benefits. After clearing the trading result, the charging system operator uploads the trading contract made in the day-ahead market to the blockchain. In the real-time market, the charging system operator checks the trading status and submits the updated trading results to the blockchain. This mechanism encourages participants in the double auction to pursue higher interests, in addition to rationally utilize the energy unmatched in the auction and to achieve the improvement of social welfare. Case studies are used to demonstrate the effectiveness of the proposed model. For buyers and sellers who successfully participate in the day-ahead market, the total profit increase for buyer and seller are 22.79% and 53.54%, respectively, as compared to without energy trading. With consideration of social welfare in the smart match mechanism, the peak load reduces from 182 to 146.5 kW, which is a 19.5% improvement.

scholarly journals Electric Vehicle Charging Scheduling by an Enhanced Artificial Bee Colony Algorithm

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2752 ◽  
Author(s):  
Jorge García Álvarez ◽  
Miguel González ◽  
Camino Rodríguez Vela ◽  
Ramiro Varela
Keyword(s):  
Electric Vehicles ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Physical Structure ◽  
Mating Strategies ◽  
Abc Algorithm ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Bee Colony ◽  
Parking Lot

Scheduling the charging times of a large fleet of Electric Vehicles (EVs) may be a hard problem due to the physical structure and conditions of the charging station. In this paper, we tackle an EV’s charging scheduling problem derived from a charging station designed to be installed in community parking where each EV has its own parking lot. The main goals are to satisfy the user demands and at the same time to make the best use of the available power. To solve the problem, we propose an artificial bee colony (ABC) algorithm enhanced with local search and some mating strategies borrowed from genetic algorithms. The proposal is analyzed experimentally by simulation and compared with other methods previously proposed for the same problem. The results of the experimental study provided interesting insights about the problem and showed that the proposed algorithm is quite competitive with previous methods.

scholarly journals Parking Demand vs Supply: An Optimization-Based Approach at a University Campus

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Navid Nadimi ◽  
Sanaz Afsharipoor ◽  
Amir Mohammadian Amiri
Keyword(s):  
Fuzzy Inference ◽  
Programming Model ◽  
University Campus ◽  
Administrative Positions ◽  
Inference System ◽  
Parking Lots ◽  
Proposed Model ◽  
Parking Lot ◽  
Parking Management ◽  
Parking Demand

Parking management has always been a major concern for universities and other activity centers. Nowadays, many universities are suffering from a lack of campus parking capacity. To tackle this problem, it is necessary to take parking lots assignment into consideration, regarding intercampus users’ needs. These users have different ages, physical characteristics, expectations, and administrative positions that should be considered before any parking assignment. Here, a new method is proposed to optimize parking lots management for those universities where staff (academic and administrative), in contrast to students, are allowed to park inside the campus area. For this purpose, first, the probability of using a specific parking lot by each group is determined. For staff, this is done based on their choices, revealed by the relative frequency of using parking lots. This probability for students can be calculated using a fuzzy inference system model. To develop the model, a survey is conducted to extract students’ preferences, regarding parking spaces assignment inside the campus area. Afterward, an integer linear programming model with the objective function of maximizing parking probability is employed, considering several related constraints. The proposed model is applied to Shahid Bahonar University of Kerman (SBUK), Iran, as the case study. According to the results, it can be concluded that the proposed method can help to reduce wandering time of finding an appropriate parking space for both staff and students. In addition, the proposed application can help increase the satisfaction level of staff and students with regard to parking management.

scholarly journals Electric Vehicle Charging Fault Monitoring and Warning Method Based on Battery Model

2021 ◽  
Vol 12 (1) ◽  
pp. 14
Author(s):  
Yuanxing Zhang ◽  
Taoyong Li ◽  
Xiangwu Yan ◽  
Ling Wang ◽  
Jing Zhang ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
State Of Charge ◽  
Battery Charging ◽  
State Information ◽  
Battery Model ◽  
Electric Vehicle Charging ◽  
Fault Monitoring ◽  
Power Battery ◽  
Demand Information ◽  
Charging Demand

With the development of electric vehicles in China, the fault monitoring and warning systems for the charging process of electric vehicles have received the industry’s attention. A method for the monitoring and warning of electric vehicle charging faults based on a battery model is proposed in this paper. Through online estimation of the state of charge of the power battery model and battery electromotive force, parameters such as battery state of charge, voltage, and temperature can be adjusted in real time to simulate the charging response of the power battery, which can simulate power batteries of different types, specifications, and parameters. During the charging process, CAN (Controller Area Network) bus monitoring technology is used to receive and analyze the charging information of the charger, as well as the battery charging information and battery charging demand information. The charging response information simulated by the battery model is compared with the battery charging state information, and the charging state information of the charger is compared with the battery charging demand information to determine whether the charging process is normal. When it is judged that a charging fault occurs, a fault warning signal is sent. This method can identify more than 10 types of faults, including the failure of the BMS (Battery Management System) function. The comparison and analysis of actual charging accident data and power battery model data verifies the feasibility of the charging fault monitoring method proposed in this paper.

scholarly journals Market Interfaces for Electric Vehicle Charging

2017 ◽  
Vol 59 ◽  
pp. 175-227 ◽  
Author(s):  
Sebastian Stein ◽  
Enrico H. Gerding ◽  
Adrian Nedea ◽  
Avi Rosenfeld ◽  
Nicholas R. Jennings
Keyword(s):  
Electric Vehicles ◽  
Market Mechanism ◽  
Electric Vehicle Charging ◽  
Learning Agent ◽  
Performance Trends ◽  
Different Types ◽  
Secondary Objective ◽  
Key Features ◽  
Ev Charging ◽  
Desirable Effect

We consider settings where owners of electric vehicles (EVs) participate in a market mechanism to charge their vehicles. Existing work on such mechanisms has typically assumed that participants are fully rational and can report their preferences accurately via some interface to the mechanism or to a software agent participating on their behalf. However, this may not be reasonable in settings with non-expert human end-users.Thus, our overarching aim in this paper is to determine experimentally if a fully expressive market interface that enables accurate preference reports is suitable for the EV charging domain, or, alternatively, if a simpler, restricted interface that reduces the space of possible options is preferable. In doing this, we measure the performance of an interface both in terms of how it helps participants maximise their utility and how it affects deliberation time. Our secondary objective is to contrast two different types of restricted interfaces that vary in how they restrict the space of preferences that can be reported. To enable this analysis, we develop a novel game that replicates key features of an abstract EV charging scenario. In two experiments with over 300 users, we show that restricting the users' preferences significantly reduces the time they spend deliberating (by up to half in some cases). An extensive usability survey confirms that this restriction is furthermore associated with a lower perceived cognitive burden on the users. More surprisingly, at the same time, using restricted interfaces leads to an increase in the users' performance compared to the fully expressive interface (by up to 70%). We also show that some restricted interfaces have the desirable effect of reducing the energy consumption of their users by up to 20% while achieving the same utility as other interfaces. Finally, we find that a reinforcement learning agent displays similar performance trends to human users, enabling a novel methodology for evaluating market interfaces.

scholarly journals Intelligent System for Determining Parking Locations in Campus Areas Using Fuzzy Logic Based on Internet of Things

2019 ◽  
Vol 7 (2) ◽  
pp. 64-70
Author(s):  
Dody Ichwana ◽  
Surya Dwi Saputra ◽  
Shelvi Ekariani
Keyword(s):  
Fuzzy Logic ◽  
Internet Of Things ◽  
Intelligent System ◽  
The Internet ◽  
University Campus ◽  
Campus Environment ◽  
Parking Lots ◽  
Parking Lot ◽  
Total Capacity

The increasing use of vehicles at campus locations makes it more difficult to find an empty parking lot. This paper develops a system for determining parking locations on campus areas using cloud-based fuzzy logic and Internet of Things (IoT). NFC is used to confirm the order code of the location that has been generated by the system. At the parking location, a sensor is installed to detect parking availability. The concept of IoT has been applied to build this system. Applications on smartphone devices are used for reservations at desired parking locations via the internet. The results show that the system has been able to detect the location of empty parking lots and make reservations in the Andalas University campus environment. The application of fuzzy logic has succeeded in obtaining parking location sequences based on distance and total capacity to find the best parking location.

Advanced Vehicle Parking System using PLC and SCADA

2019 ◽  
Vol 8 (6S2) ◽  
pp. 467-470
Keyword(s):  
Open Space ◽  
Organization Structure ◽  
General System ◽  
General Control ◽  
Control Center ◽  
Unit Process ◽  
Basic Goal ◽  
Parking Lot ◽  
Access Information ◽  
The Right

This work is to perceive the open space in the halting reach using PLC and SCADA. The rule target is to recognize the unfilled space and demonstrating the driver to a particular opening. This paper tries to layout and execute an electronic stopping region organization structure. Robotized Parking Lot Management System is a totally utilitarian and painstakingly controlled parking structure organization system that is executed with the usage and compromise of different electronic equipment and littler scale figuring. The layout incorporates assorted stages, from the rule unit; process is passed on to different subunits to achieve the target of full motorization. A moving toward auto will pass on (through the driver) remotely with the essential unit associated with the Parking Office Gate. The essential unit will check the transmitted access information and will pass control after affirmation to the gateway framework drivers, this in this way drives the right entryway control (either exit or segment unit). The system currently screens the development of the driver some time later, and for entry, as the driver moves a destined eparation into the workplace ,the system turns back the entryway segment (for finish of entryway) and passes control to the space part and organization unit. The objective of this later unit is to manage the parking spaces available in the package by watching the development of the automobiles inside, allocating the spaces in a precise manner, watching consistence what's more, prompt the general control center (watched out for) of the space(s) open. It has a show interface for talking with the customers of the workplace. There is in like manner a control center that is watched out for by work power and screens the activities inside the parking structure. It is educated regarding any development, space(s) open and moreover the general system can be shut down or changed on from the control center. The basic goal of this errand is to achieve full motorization and it will find snappy use in tremendous workplaces with different access restrictions, government properties, and school grounds to sectionalize educator's auto stop and understudy's auto stop, etc.

scholarly journals Optimized Strategic Planning of Future Norwegian Low-Voltage Networks with a Genetic Algorithm Applying Empirical Electric Vehicle Charging Data

Electricity ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 91-109
Author(s):  
Julian Wruk ◽  
Kevin Cibis ◽  
Matthias Resch ◽  
Hanne Sæle ◽  
Markus Zdrallek
Keyword(s):  
Genetic Algorithm ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Low Voltage ◽  
Network Planning ◽  
Voltage Regulation ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
The Impact

This article outlines methods to facilitate the assessment of the impact of electric vehicle charging on distribution networks at planning stage and applies them to a case study. As network planning is becoming a more complex task, an approach to automated network planning that yields the optimal reinforcement strategy is outlined. Different reinforcement measures are weighted against each other in terms of technical feasibility and costs by applying a genetic algorithm. Traditional reinforcements as well as novel solutions including voltage regulation are considered. To account for electric vehicle charging, a method to determine the uptake in equivalent load is presented. For this, measured data of households and statistical data of electric vehicles are combined in a stochastic analysis to determine the simultaneity factors of household load including electric vehicle charging. The developed methods are applied to an exemplary case study with Norwegian low-voltage networks. Different penetration rates of electric vehicles on a development path until 2040 are considered.

EVBlocks: A Blockchain-Based Secure Energy Trading Scheme for Electric Vehicles underlying 5G-V2X Ecosystems

2021 ◽  
Author(s):  
Pronaya Bhattacharya ◽  
Sudeep Tanwar ◽  
Umesh Bodkhe ◽  
Ashwani Kumar ◽  
Neeraj Kumar
Keyword(s):  
Electric Vehicles ◽  
Energy Trading ◽  
Trading Scheme
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