Optimal Scheduling for Smart Charging of Electric Vehicles Using Dynamic Programming

2018 ◽  
pp. 279-284
Author(s):  
Karol Lina López ◽  
Christian Gagné
Keyword(s):  
Dynamic Programming ◽  
Electric Vehicles ◽  
Optimal Scheduling ◽  
Smart Charging

scholarly journals Eco-Driving for Different Electric Powertrain Topologies Considering Motor Efficiency

2021 ◽  
Vol 12 (1) ◽  
pp. 6
Author(s):  
Alexander Koch ◽  
Tim Bürchner ◽  
Thomas Herrmann ◽  
Markus Lienkamp
Keyword(s):  
Dynamic Programming ◽  
Electric Vehicles ◽  
Quadratic Functions ◽  
Simultaneous Optimization ◽  
Speed Profile ◽  
Power Demand ◽  
Electric Motors ◽  
Car Following ◽  
Motor Efficiency ◽  
Computationally Expensive

Electrification and automatization may change the environmental impact of vehicles. Current eco-driving approaches for electric vehicles fit the electric power of the motor by quadratic functions and are limited to powertrains with one motor and single-speed transmission or use computationally expensive algorithms. This paper proposes an online nonlinear algorithm, which handles the non-convex power demand of electric motors. Therefore, this algorithm allows the simultaneous optimization of speed profile and powertrain operation for electric vehicles with multiple motors and multiple gears. We compare different powertrain topologies in a free-flow scenario and a car-following scenario. Dynamic Programming validates the proposed algorithm. Optimal speed profiles alter for different powertrain topologies. Powertrains with multiple gears and motors require less energy during eco-driving. Furthermore, the powertrain-dependent correlations between jerk restriction and energy consumption are shown.

scholarly journals Investigation of the Impact of Large-Scale Integration of Electric Vehicles for a Swedish Distribution Network

Energies ◽  
2019 ◽  
Vol 12 (24) ◽  
pp. 4717 ◽  
Author(s):  
Sylvester Johansson ◽  
Jonas Persson ◽  
Stavros Lazarou ◽  
Andreas Theocharis
Keyword(s):  
Electric Vehicles ◽  
Power Distribution ◽  
Large Scale ◽  
Electrical Power ◽  
Distribution Network ◽  
Transport Sector ◽  
Smart Charging ◽  
Large Scale Integration ◽  
Scale Integration ◽  
The Impact

Social considerations for a sustainable future lead to market demands for electromobility. Hence, electrical power distribution operators are concerned about the real ongoing problem of the electrification of the transport sector. In this regard, the paper aims to investigate the large-scale integration of electric vehicles in a Swedish distribution network. To this end, the integration pattern is taken into consideration as appears in the literature for other countries and applies to the Swedish culture. Moreover, different charging power levels including smart charging techniques are examined for several percentages of electric vehicles penetration. Industrial simulation tools proven for their accuracy are used for the study. The results indicate that the grid can manage about 50% electric vehicles penetration at its current capacity. This percentage decreases when higher charging power levels apply, while the transformers appear overloaded in many cases. The investigation of alternatives to increase the grid’s capabilities reveal that smart techniques are comparable to the conventional re-dimension of the grid. At present, the increased integration of electric vehicles is manageable by implementing a combination of smart gird and upgrade investments in comparison to technically expensive alternatives based on grid digitalization and algorithms that need to be further confirmed for their reliability for power sharing and energy management.

Optimal scheduling of electric vehicles charging in battery swapping station considering wind- photovoltaic accommodation

2021 ◽  
Vol 199 ◽  
pp. 107451
Author(s):  
Haifeng Wang ◽  
Hongyuan Ma ◽  
Chang Liu ◽  
Weijun Wang
Keyword(s):  
Electric Vehicles ◽  
Optimal Scheduling

scholarly journals Smart charging for electric vehicles to minimise charging cost

2017 ◽  
Vol 231 (6) ◽  
pp. 526-534 ◽  
Author(s):  
Yue Wang ◽  
David Infield ◽  
Simon Gill
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Distribution System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Low Voltage ◽  
Wholesale Price ◽  
Heuristic Method ◽  
Domain Model ◽  
Smart Charging

This paper assumes a smart grid framework where the driving patterns for electric vehicles are known, time variations in electricity prices are communicated to householders, and data on voltage variation throughout the distribution system are available. Based on this information, an aggregator with access to this data can be employed to minimise electric vehicles charging costs to the owner whilst maintaining acceptable distribution system voltages. In this study, electric vehicle charging is assumed to take place only in the home. A single-phase Low Voltage (LV) distribution network is investigated where the local electric vehicles penetration level is assumed to be 100%. Electric vehicle use patterns have been extracted from the UK Time of Use Survey data with a 10-min resolution and the domestic base load is generated from an existing public domain model. Apart from the so-called real time price signal, which is derived from the electricity system wholesale price, the cost of battery degradation is also considered in the optimal scheduling of electric vehicles charging. A simple and effective heuristic method is proposed to minimise the electric vehicles’ charging cost whilst satisfying the requirement of state of charge for the electric vehicles’ battery. A simulation in OpenDSS over a period of 24 h has been implemented, taking care of the network constraints for voltage level at the customer connection points. The optimisation results are compared with those obtained using dynamic optimal power flow.

A Lightweight User Interface for Smart Charging of Electric Vehicles: A Real-World Application

2021 ◽  
Author(s):  
Stefan Meisenbacher ◽  
Karl Schwenk ◽  
Johannes Galenzowski ◽  
Simon Waczowicz ◽  
Ralf Mikut ◽  
...  
Keyword(s):  
User Interface ◽  
Electric Vehicles ◽  
Real World ◽  
Real World Application ◽  
Smart Charging

Dominated GSO Algorithm for Optimal Scheduling of Renewable Microgrids with Penetration of Electric Vehicles and Energy Storages considering DRP

2021 ◽  
pp. 1-24
Author(s):  
Navid Taghizadegan ◽  
Selma Cheshmeh Khavar ◽  
Arya Abdolahi ◽  
Faezeh Arasteh ◽  
Reza Ghoreyshi
Keyword(s):  
Electric Vehicles ◽  
Optimal Scheduling

Multi-Objective Optimal Scheduling of the Microgrid with Electric Vehicles

2021 ◽  
Author(s):  
Yu Mei ◽  
Bin Li ◽  
Honglei Wang ◽  
Xiaolin Wang ◽  
Michael Negnevitsky
Keyword(s):  
Electric Vehicles ◽  
Optimal Scheduling ◽  
Multi Objective

Optimal scheduling algorithms of system chip power density based on network on chip

2021 ◽  
pp. 120-127
Author(s):  
Jiashen Li ◽  
◽  
Yun Pan ◽  
Keyword(s):  
Dynamic Programming ◽  
Power Density ◽  
Simulated Annealing Algorithm ◽  
Dynamic Programming Algorithm ◽  
Network On Chip ◽  
Thermal Design ◽  
Optimal Scheduling ◽  
Programming Algorithm ◽  
System Throughput ◽  
On Chip

The improvement of chip integration leads to the increase of power density of system chips, which leads to the overheating of system chips. When dispatching the power density of system chips, some working modules are selectively closed to avoid all modules on the chip being turned on at the same time and to solve the problem of overheating. Taking 2D grid-on-chip network as the research object, an optimal scheduling algorithm of system-on-chip power density based on network-on-chip (NoC) is proposed. Under the constraints of thermal design power (TDP) and system, dynamic programming algorithm is used to solve the optimal application set throughput allocation from bottom to top by dynamic programming for the number and frequency level of each application configuration processor under the given application set of network-on-chip. On this basis, the simulated annealing algorithm is used to complete the application mapping aiming at heat dissipation effect and communication delay. The open and closed processor layout is determined. After obtaining the layout results, the TDP is adjusted. The maximum TDP constraint is iteratively searched according to the feedback loop of the system over-hot spots, and the power density scheduling performance of the system chip is maximized under this constraint, so as to ensure the system core. At the same time, chip throughput can effectively solve the problem of chip overheating. The experimental results show that the proposed algorithm increases the system chip throughput by about 11%, improves the system throughput loss, and achieves a balance between the system chip power consumption and scheduling time.

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