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Smart Control of an Electric Vehicle for Ancillary Service in DC Microgrid
- Source :
- IEEE Access, Vol 8, Pp 197222-197235 (2020)
- Publication Year :
- 2020
- Publisher :
- IEEE, 2020.
-
Abstract
- This article presents a two-stage framework for optimal Electric Vehicle (EV) charging/discharging strategy for DC Microgrid (MG) with Distributed Generators (DGs). A multi-objective optimisation task aimed at minimising system losses and EV battery degradation with Vehicle-to-Grid (V2G) peak shaving service has been realised. This coordinated EV integration into the DCMG was formulated as a directed weighted single source shortest path problem that was solved using a modified Dijkstra’s algorithm. The weights of the edges were obtained using primal-dual interior point method. The proposed framework has been experimentally verified using simulations with a test DCMG system with practical IEEE European low voltage test feeder load profiles. Results show realisation of peak demand shaving leveraging on EV discharge with minimal on-board battery degradation as well as reduced system losses. It is also shown that the proposed two-stage framework reduces the battery state of charge (SOC) sample space requirements in the analysis, thus, reducing the computational burden.
- Subjects :
- Technology
business.product_category
Computer science
Resistance
Vehicle-to-grid
multi-objective optimisation
PV
02 engineering and technology
09 Engineering
Automotive engineering
POWER QUALITY
Engineering
DESIGN
Peak demand
modified Dijkstra’
10 Technology
Electric vehicle
0202 electrical engineering, electronic engineering, information engineering
General Materials Science
optimal power flow
Computer Science, Information Systems
ALGORITHMS
V2G
State of charge
General Engineering
NETWORKS
Peaking power plant
Telecommunications
Microgrid
lcsh:TK1-9971
Optimization
dc microgrid
General Computer Science
020209 energy
s algorithm
EV integration
Batteries
power losses
ENERGY MANAGEMENT
Microgrids
Load modeling
Science & Technology
020208 electrical & electronic engineering
Engineering, Electrical & Electronic
Computer Science
OPERATION
08 Information and Computing Sciences
lcsh:Electrical engineering. Electronics. Nuclear engineering
business
Low voltage
control
SYSTEM
battery degradation
Subjects
Details
- Language :
- English
- ISSN :
- 21693536
- Volume :
- 8
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....dc1e5f67589bcf649f684cb2428b10e0