• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4301-4319
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• 2017

Adopting mobile chargers (MC) in rechargeable wireless sensors network (R-WSN) to recharge sensors can increase network efficiency (e.g., reduce MC travel distance per tour, reduce MC effort, and prolong WSN lifetime). In this study, we propose a mechanism to split the sensing field into partitions that may be equally spaced but differ in distance to the base station. Moreover, we focus on minimizing the MC effort by providing a new charging mechanism called the sector-based charging schedule (SBCS), which works to dispatch the MC in charging trips to the sector that sends many charging requests and suggesting an efficient sensor-charging algorithm. Specifically, we first utilize the high ability of the BS to divide the R-WSN field into sectors then it select the cluster head for each sector to reduce the intra-node communication. Second, we formulate the charging productivity as NP-hard problem and then conduct experimental simulations to evaluate the performance of the proposed mechanism. An extensive comparison is performed with other mechanisms. Experimental results demonstrate that the SBCS mechanism can prolong the lifetime of R-WSNs by increasing the charging productivity about 20% and reducing the MC effort by about 30%.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.4
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• pp.547-554
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• 2016

Analyze the customer daily load patterns, be used to determine the optimal charging and discharging schedule which can minimize the electrical charges through the battery energy storage system(BESS) installed in consumers is an object of this paper. BESS, which analyzes the load characteristics of customer and reduce the peak load, is essential for optimal charging and discharging scheduling to save electricity charges. This thesis proposes optimal charging and discharging scheduling method, using particle swarm optimization (PSO) and penalty function method, of BESS for reducing energy charge. Since PSO is a global optimization algorithm, best charging and discharging scheduling can be found effectively. In addition, penalty function method was combined with PSO in order to handle many constraint conditions. After analysing the load patterns of target BESS, PSO based on penalty function method was applied to get optimal charging and discharging schedule.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.632-639
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• 2018

Recently, a policy has been enforced to supply Plug-in Electric Vehicles (PEVs) but this may require reinforcement of the power system depending on its clustering because PEVs are charged directly from power systems. On the other hand, as the reinforcement of power system is limited by time and budget, it is important to supply the charging demand of PEVs efficiently using the existing power systems to increase the diffusion of PEVs. This paper establishes a charging schedule for Plug-in Electric Vehicles (PEVs) considering the power system constraints. For this, the required amount and time of the charging demand for an individual PEV was modeled to integrate into power systems based on the driving pattern and charging tariff of PEV. Furthermore, the charging schedule of PEVs was established to meet the power system constraints by calculating the operating conditions of the power systems with PEVs.

• ETRI Journal
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• v.41 no.3
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• pp.326-336
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• 2019

A wireless power transfer technique can solve the power capacity problem in wireless rechargeable sensor networks (WRSNs). The charging strategy is a wide-spread research problem. In this paper, we propose a demand-based charging strategy (DBCS) for WRSNs. We improved the charging programming in four ways: clustering method, selecting to-be-charged nodes, charging path, and charging schedule. First, we proposed a multipoint improved K-means (MIKmeans) clustering algorithm to balance the energy consumption, which can group nodes based on location, residual energy, and historical contribution. Second, the dynamic selection algorithm for charging nodes (DSACN) was proposed to select on-demand charging nodes. Third, we designed simulated annealing based on performance and efficiency (SABPE) to optimize the charging path for a mobile charging vehicle (MCV) and reduce the charging time. Last, we proposed the DBCS to enhance the efficiency of the MCV. Simulations reveal that the strategy can achieve better performance in terms of reducing the charging path, thus increasing communication effectiveness and residual energy utility.

• Journal of Internet Computing and Services
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• v.24 no.1
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• pp.87-97
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• 2023

Charger infrastructure facilities are designed and installed based on a constant power supply. Initially designed charging facilities support charging of rapidly growing electric vehicles on a limited power supply basis. In addition, current commercial vehicles can only be fully charged, and are supported by the rapid equalization charging method. However, commercial vehicles operate according to a set schedule, so flexible charging is essential. In this paper, we propose a power operation method with more than 20% efficiency improvement by using a fixed schedule-based charging scheduling and power distribution technique of a commercial bus based on the same amount of power in accordance with the rapid growth and increase of electric vehicles.

• Proceedings of the KIPE Conference
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• 2014.07a
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• pp.482-483
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• 2014

In this paper, an electric yard tractor (YT) with furtive charging system is investigated. YT is one of pollution sources in container terminals. The furtive charging system does not impose difficulties on YT day-schedule because charging is performed when a YT is waiting under RTGC (Rubber Type Gantry crane) or Quay-wall crane.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.4
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• pp.395-402
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• 2016

When the operation of battery is converted at charging and discharging system based on a DC micro grid, the voltage is fluctuated. And excessive voltage fluctuation could cause damage or failure of charging and discharging equipment. Therefore, in this paper, we studied the operating schedule of the charging and discharging system based on the DC micro grid and a design point of the capacitor which was able to reduce the voltage fluctuation. A result of computer simulation showed that when a fluctuation-reducing capacitor which had an initial value of 600V/35mF was applied at the charging and discharging system based on a DC micro grid which was operated with three charging battery sets and five discharging battery sets, voltage fluctuation by charging and discharging operation was reduced by about 63.3%. Furthermore, voltage fluctuation which occurred when initial network voltage was stabilized was reduced by about 73%.

• KEPCO Journal on Electric Power and Energy
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• v.6 no.3
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• pp.315-319
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• 2020

The modern transportation and mobility sector is expected to encounter high penetration of Electric Vehicles (EVs) because EVs contribute to reducing the harmful emissions from fossil fuel-powered vehicles. With the prospective growth of EVs, sufficient and convenient facilities for fast charging are crucial toward satisfying the EVs' quick charging demand during their trip. Therefore, the Fast Electric Vehicle Charging Stations (FECS) will be a similar role to gas stations. In this paper, we study a charging scheduling problem for the FECS with solar photovoltaic (PV) and an Energy Storage System (ESS). We formulate an optimization problem that minimizes the operational costs of FECS. There are two cost and one revenue terms that are buying cost from main grid power, ESS degradation cost, and revenue from the charging fee of the EVs. Simulation results show that the proposed scheduling algorithm reduces the daily operational cost by effectively using solar PV and ESS.

• Journal of Communications and Networks
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• v.14 no.6
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• pp.672-681
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• 2012

A potential breakthrough of the electrification of the vehicle fleet will incur a steep rise in the load on the electrical power grid. To avoid huge grid investments, coordinated charging of those vehicles is a must. In this paper, we assess algorithms to schedule charging of plug-in (hybrid) electric vehicles as to minimize the additional peak load they might cause. We first introduce two approaches, one based on a classical optimization approach using quadratic programming, and a second one, market based coordination, which is a multi-agent system that uses bidding on a virtual market to reach an equilibrium price that matches demand and supply. We benchmark these two methods against each other, as well as to a baseline scenario of uncontrolled charging. Our simulation results covering a residential area with 63 households show that controlled charging reduces peak load, load variability, and deviations from the nominal grid voltage.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.3
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• pp.343-351
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• 2018

Renewable energy sources has drawn considerable attention as clean energy sources because of changing public attitudes regarding greenhouse gas and fine dust. Recently, in this respect, the government provides the drivers of electric vehicles with various benefits such as tax reduction, financial incentives and free parking from the public to the private sector. Plug-in electric vehicles are the most common in the private sector. Otherwise, different types of battery-based buses in the public sector are being developed, and there are three main types of charging: plug-in, battery swapping and wireless. Therefore, economic assessment of charging types in each bus route is required in order to facilitate the use of battery-based buses instead of the existing CNG buses. In this paper, net present value(NPV) and B/C ratio of charging types are evaluated in consideration of the bus schedule, the cost of charging station, and the life cycle of battery, etc. per each bus route. In case study, main bus routes in Daegu City are simulated with the proposed evaluation method to validate the eco-bus project.