• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.87-106
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• 2024

Vehicle-to-Home (V2H) and Home Centralized Photovoltaic (HCPV) systems can address various energy storage issues and enhance demand response programs. Renewable energy, such as solar energy and wind turbines, address the energy gap. However, no energy management system is currently available to regulate the uncertainty of renewable energy sources, electric vehicles, and appliance consumption within a smart microgrid. Therefore, this study investigated the impact of solar photovoltaic (PV) panels, electric vehicles, and Micro-Grid (MG) storage on maximum solar radiation hours. Several Deep Learning (DL) algorithms were applied to account for the uncertainty. Moreover, a Reinforcement Learning HCPV (RL-HCPV) algorithm was created for efficient real-time energy scheduling decisions. The proposed algorithm managed the energy demand between PV solar energy generation and vehicle energy storage. RL-HCPV was modeled according to several constraints to meet household electricity demands in sunny and cloudy weather. Simulations demonstrated how the proposed RL-HCPV system could efficiently handle the demand response and how V2H can help to smooth the appliance load profile and reduce power consumption costs with sustainable power generation. The results demonstrated the advantages of utilizing RL and V2H as potential storage technology for smart buildings.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.22 no.1
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• pp.49-55
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• 2010

The objectives of this study are to analyze the energy independence plan and to propose a suitable sewage treatment plant in Korea. The total amount of electricity consumption for public sewage treatment plant was estimated as 1,812 GWh in 2007. It was estimated that total 16 sewage treatment plants with renewable energy systems produced electricity of 15 GWh per year, which could replace 0.8% of total electricity used for sewage treatment. It was found that domestic sewage treatment plants with power generation plants by digestion gas were installed in 7 places and produced electricity of 13 GWh per year. It was also found that the power generation plants by digestion gas were the most cost-effective for sewage treatment plant out of the renewable energy systems based on the benefit-cost analysis.

• Journal of Power Electronics
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• v.18 no.4
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• pp.1111-1126
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• 2018

In modern power systems, distributed generators (DGs) result in high stress on system frequency stability. Apart from the intermittent nature of DGs, most DGs do not contribute inertia or damping to systems. As a result, a new control method referred to as a virtual synchronous machine (VSM) has been proposed, which brought new characteristics to inverters such as synchronous machines (SM). DGs employing an energy storage system (ESS) provide inertia and damping through VSM control. Meanwhile, energy storage presents some physical constraints in the VSM implementation level. In this paper, a VSM mathematical model is built and analyzed. The dynamic responses of the output active power are presented when a step change in the frequency occurs. The influences of the inertia constant, damping factor and operating point on the ESS volume margins are investigated. In addition, physical constraints are proposed based on these analyses. The proposed physical constraints are simulated using PSCAD/EMTDC software and tested through RTDS experiment. Both simulation and RTDS test results verify the analysis.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.2
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• pp.222-227
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• 2015

This paper presents the optimal energy generation systems for economical EVs(Electric Vehicles) charging stations located in an island area. The system includes grid electricity, diesel generator and renewable energy sources of wind turbines and PV(Photovoltaic) panels. The independent generation system is designed with data resources such as annual average wind speed, solar radiation and the grid electricity price by calculating system cost under different structures. This sensitive analysis on the varying data resources allows for the configuration of the most economical generation system for charging stations by comparing initial capital, operating cost, NPC(Net Present Cost) and COE(Cost of Energy). Depending on the increase of the grid cost, the NPC variation of the most economical system which includes renewable energy generations and grid electricity can be smaller than those of other generation systems.

• Journal of Power Electronics
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• v.15 no.1
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• pp.202-215
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• 2015

This paper investigates the stability and performance of model predictive controlled active-front-end (AFE) rectifiers for energy storage systems, which has been increasingly applied in power distribution sectors and in renewable energy sources to ensure an uninterruptable power supply. The model predictive control (MPC) algorithm utilizes the discrete behavior of power converters to determine appropriate switching states by defining a cost function. The stability of the MPC algorithm is analyzed with the discrete z-domain response and the nonlinear simulation model. The results confirms that the control method of the active-front-end (AFE) rectifier is stable, and that is operates with an infinite gain margin and a very fast dynamic response. Moreover, the performance of the MPC controlled AFE rectifier is verified with a 3.0 kW experimental system. This shows that the MPC controlled AFE rectifier operates with a unity power factor, an acceptable THD (4.0 %) level for the input current and a very low DC voltage ripple. Finally, an efficiency comparison is performed between the MPC and the VOC-based PWM controllers for AFE rectifiers. This comparison demonstrates the effectiveness of the MPC controller.

• Journal of Power Electronics
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• v.18 no.3
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• pp.892-901
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• 2018

SiC MOSFETs have been used to improve system efficiency in high frequency converters due to their extremely high switching speed. However, this can result in undesirable parasitic oscillations in practical systems. In this paper, models of the key components are introduced first. Then, theoretical formulas are derived to calculate the switching oscillation frequencies after full turn-on and turn-off in clamped inductive circuits. Analysis indicates that the turn-on oscillation frequency depends on the power loop parasitic inductance and parasitic capacitances of the freewheeling diode and load inductor. On the other hand, the turn-off oscillation frequency is found to be determined by the output parasitic capacitance of the SiC MOSFET and power loop parasitic inductance. Moreover, the shifting regularity of the turn-off maximum peak voltage with a varying switching speed is investigated on the basis of time domain simulation. The distortion of the turn-on current is theoretically analyzed. Finally, experimental results verifying the above calculations and analyses are presented.

• Journal of Power Electronics
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• v.4 no.2
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• pp.117-126
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• 2004

This paper focuses on the electrical modeling techniques of renewable energy sources and storage devices such as batteries, fuel cells (FCs), photovoltaic (PVs) arrays, ultra-capacitors (UCs), and flywheel energy storage systems (FESS). All of these devices are being investigated recently for their typical storage and supply capabilities for various industrial applications. Hence, these devices must be modeled precisely taking into account the concerned practical issues. An obvious advantage of electrically modeling these renewable energy sources and storage devices is the fact that they can easily be simulated in real-time in any CAD simulation program. This paper reviews several types of suitable models for each of the above-mentioned devices and the most appropriate model amongst them is presented. Furthermore, a few important applications of these devices shall also be highlighted.

• Ocean Systems Engineering
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• v.13 no.3
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• pp.247-268
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• 2023

Tidal stream energy extraction remains a site-specific resource due to the "first generation" criteria requiring high-velocity tidal streams. Most studies on tidal energy and turbine blade design heavily focus on installation sites with higher velocity conditions that are non-existent in tropical countries such as the Philippines. To shorten this gap, this review paper tackles tidal turbine design considerations for low-energetic regions such as the tropics. In-depth discussions of operating principles, methods of analysis, and designs of tidal turbine blades are presented. Notable tidal stream projects around the world are also mentioned in the paper. Also, it provides a perspective on the potential of this renewable energy to produce electricity for various sites in the Philippines. Finally, the paper emphasizes the need for new tidal turbine blade designs to be viable in tropical regions, such as the Philippines.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.201-211
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• 2022

The economic development of most countries in the world has negatively impacted fossil energy resources. Fossil energy sources such as petroleum and coal are increasingly depleted. When energy sources are exhausted, renewable energy sources are growing strongly. Renewable energy development can help to replace diminishing fossil fuels. Furthermore, the usage of renewable energy can contribute to a green economy and sustainable development by protecting the environment. Solar power on the roof is one of the many renewable energy sources available. But at present, the investment in roof voltage systems has not developed strongly in Vietnam. This paper uses the SEM model to evaluate the factors affecting investment in rooftop solar power in some provinces of Vietnam. The article uses the household interview method. The article has given 8 factors affecting the decision to invest in rooftop solar power for households. Research results show that most of the factor variables have a positive impact on the decision to invest in rooftop solar power. Based on assessing the factors affecting the decision to invest in rooftop solar power, the article will provide conclusions and policy suggestions to increase investment in rooftop solar power in Vietnam.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1123-1146
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• 2023

In South Korea, there have been many studies on efficient building-energy management using renewable energy facilities in single zero-energy houses or buildings. However, such management was limited due to spatial and economic problems. To realize a smart zero-energy city, studying efficient energy integration for the entire city, not just for a single house or building, is necessary. Therefore, this study was conducted in the eco-friendly energy town of Chungbuk Innovation City. Chungbuk successfully realized energy independence by converging new and renewable energy facilities for the first time in South Korea. This study analyzes energy data collected from public buildings in that town every minute for a year. We propose a smart city building-energy management model based on the results that combine various renewable energy sources with grid power. Supervised learning can determine when it is best to sell surplus electricity, or unsupervised learning can be used if there is a particular pattern or rule for energy use. However, it is more appropriate to use reinforcement learning to maximize rewards in an environment with numerous variables that change every moment. Therefore, we propose a power distribution algorithm based on reinforcement learning that considers the sales of Energy Storage System power from surplus renewable energy. Finally, we confirm through economic analysis that a 10% saving is possible from this efficiency.