Adaptive V2G Peak Shaving and Smart Charging Control for Grid Integration of PEVs

2018 ◽  
Vol 46 (13) ◽  
pp. 1494-1508 ◽  
Author(s):  
Fatih Erden ◽  
Mithat C. Kisacikoglu ◽  
Nuh Erdogan
Keyword(s):  
Grid Integration ◽  
Peak Shaving ◽  
Smart Charging ◽  
Charging Control

scholarly journals VxG Pattern-Based Analysis and Battery Deterioration Diagnosis

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5422
Author(s):  
Jungho Lim ◽  
Sung-Eun Lee ◽  
Kwang-Yong Park ◽  
Hee-Soo Kim ◽  
Jin-Hyeok Choi
Keyword(s):  
Ac Impedance ◽  
Internal Resistance ◽  
Analysis Method ◽  
Stabilization Time ◽  
Accelerated Degradation ◽  
Nickel Cobalt ◽  
Smart Charging ◽  
Charging Control ◽  
Nominal Capacity ◽  
Pattern Repetition

This paper presents the results of an analysis using the direct current internal resistance (DCIR) method on a nickel-cobalt-manganese oxide (NCM)-based battery with a nominal capacity of 55.6 Ah. The accelerated degradation test was performed on V0G, V1G, and V2G patterns, representing existing simple power supply, smart charging control, and bi-directional charge/discharge control, respectively. We assumed V0G, V1G, and V2G patterns and conducted charging and discharging experiments according to the set conditions. According to the pattern repetition, changes in the internal resistance of DCIR and AC-impedance were analyzed and battery deterioration was diagnosed. By comparing DCIR and AC-impedance, we confirmed that the changes in internal resistance has a similar trend. In particular, we propose a new DCIR analysis method in the “stop-operation” part rather than the traditional DCIR method. In the case of traditional DCIR method, time is required for the battery to stabilize. However, the newly proposed DCIR analysis method has the advantage of diagnosing the deterioration of the battery during system operation by analyzing the internal resistance without the stabilization time of the battery.

scholarly journals Electromobility and Flexibility Management on a Non-Interconnected Island

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1337
Author(s):  
Enea Mele ◽  
Anastasios Natsis ◽  
Aphrodite Ktena ◽  
Christos Manasis ◽  
Nicholas Assimakis
Keyword(s):  
Electricity Markets ◽  
Distributed Storage ◽  
Renewable Energy Sources ◽  
Electricity Demand ◽  
Distribution Grid ◽  
Mobility Patterns ◽  
Peak Shaving ◽  
Smart Charging ◽  
Challenges And Opportunities ◽  
Generating Capacity

The increasing penetration of electrical vehicles (EVs), on the way to decarbonizing the transportation sector, presents several challenges and opportunities for the end users, the distribution grid, and the electricity markets. Uncontrollable EV charging may increase peak demand and impact the grid stability and reliability, especially in the case of non-interconnected microgrids such as the distribution grids of small islands. On the other hand, if EVs are considered as flexible loads and distributed storage, they may offer Vehicle to Grid (V2G) services and contribute to demand-side management through smart charging and discharging. In this work, we present a study on the penetration of EVs and the flexibility they may offer for services to the grid, using a genetic algorithm for optimum valley filling and peak shaving for the case of a non-interconnected island where the electricity demand is several times higher during the summer due to the influx of tourists. Test cases have been developed for various charging/discharging strategies and mobility patterns. Their results are discussed with respect to the current generating capacity of the island as well as the future case where part of the electricity demand will have to be met by renewable energy sources, such as photovoltaic plants, in order to minimize the island’s carbon footprint. Higher EV penetration, in the range of 20–25%, is enabled through smart charging strategies and V2G services, especially for load profiles with a large difference between the peak and low demands. However, the EV penetration and available flexibility is subject to the mobility needs and limited by the population and the size of the road network of the island itself rather than the grid needs and constraints. Limitations and challenges concerning efficient V2G services on a non-interconnected microgrid are identified. The results will be used in the design of a smart charging controller linked to the microgrid’s energy management system.

Distribution transformer tests for PEV smart charging control

2012 ◽  
Author(s):  
Q. Gong ◽  
S. Midlam-Mohler ◽  
E. Serra ◽  
V. Marano ◽  
G. Rizzoni
Keyword(s):  
Distribution Transformer ◽  
Smart Charging ◽  
Charging Control

Implementation of Fuzzy Logic Control on Battery Charging System

2019 ◽  
Vol 3 (1) ◽  
pp. 118-126 ◽  
Author(s):  
Prihangkasa Yudhiyantoro
Keyword(s):  
Complex System ◽  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Expert Knowledge ◽  
Experimental Result ◽  
Rule Base ◽  
Battery Charging ◽  
Charging System ◽  
Logic Control ◽  
Charging Control

This paper presents the implementation fuzzy logic control on the battery charging system. To control the charging process is a complex system due to the exponential relationship between the charging voltage, charging current and the charging time. The effective of charging process controller is needed to maintain the charging process. Because if the charging process cannot under control, it can reduce the cycle life of the battery and it can damage the battery as well. In order to get charging control effectively, the Fuzzy Logic Control (FLC) for a Valve Regulated Lead-Acid Battery (VRLA) Charger is being embedded in the charging system unit. One of the advantages of using FLC beside the PID controller is the fact that, we don’t need a mathematical model and several parameters of coefficient charge and discharge to software implementation in this complex system. The research is started by the hardware development where the charging method and the combination of the battery charging system itself to prepare, then the study of the fuzzy logic controller in the relation of the charging control, and the determination of the parameter for the charging unit will be carefully investigated. Through the experimental result and from the expert knowledge, that is very helpful for tuning of the  embership function and the rule base of the fuzzy controller.

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