• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.6
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• pp.820-827
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• 2014

Since a microgrid has renewable energy sources, imbalance between power supply and power demand occurs in the islanded mode. In order to solve the imbalance, several energy storage systems (ESSs) such as bettary energy storage system (BESS), EDLC (electric double layer capacitor), flywheel, and SMES (superconducting magnetic energy storage) are generally used. Especially, their electrical characteristics are different. For efficient use of them, a coordinated control scheme is required. In this paper, a coordinated control scheme for using a Lead-acid BESS, a Lithium BESS, and a EDLC is designed to efficient frequency control for a microgrid in the islanded mode. The coordinated frequency control strategy is designed based on their electrical characteristics. The feasibility of the proposed coordinated frequency control strategy is verified through the simulation.

• Advances in Energy Research
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• v.4 no.1
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• pp.47-68
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• 2016

A well designed hybrid power system (HPS) can deliver electrical energy in a cost effective way. In this paper, model for HPS consisting of photo voltaic (PV) module and wind mill as renewable energy sources (RES) and solar lead acid battery as storage device connected to unidirectional grid is developed for peak demand reduction. Life time energy cost of the system is evaluated. One year hourly site condition and load pattern are taken into account for analysing the HPS. The optimal HPS is determined for least life time energy cost subject to the constraints like state of charge of the battery bank, dump load, renewable energy (RE) generation etc. Optimal solutions are also found out individually for PV module and wind mill. These three systems are compared to find out the most feasible combination. The results show that the HPS can deliver energy in an acceptable cost with reduced peak consumption from the grid. The proposed optimization algorithm is suitable for determining optimal HPS for desired location and load with least energy cost.

• Journal of Electrical Engineering and Technology
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• v.10 no.1
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• pp.165-175
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• 2015

Energy storage system has been widely applied in power distribution sectors as well as in renewable energy sources to ensure uninterruptible power supply. This paper presents a model predictive algorithm to control a bidirectional AC-DC converter, which is used in an energy storage system for power transferring between the three-phase AC voltage supply and energy storage devices. This model predictive control (MPC) algorithm utilizes the discrete behavior of the converter and predicts the future variables of the system by defining cost functions for all possible switching states. Subsequently, the switching state that corresponds to the minimum cost function is selected for the next sampling period for firing the switches of the AC-DC converter. The proposed model predictive control scheme of the AC-DC converter allows bidirectional power flow with instantaneous mode change capability and fast dynamic response. The performance of the MPC controlled bidirectional AC-DC converter is simulated with MATLAB/Simulink(R) and further verified with 3.0kW experimental prototypes. Both the simulation and experimental results show that, the AC-DC converter is operated with unity power factor, acceptable THD (3.3% during rectifier mode and 3.5% during inverter mode) level of AC current and very low DC voltage ripple. Moreover, an efficiency comparison is performed between the proposed MPC and conventional VOC-based PWM controller of the bidirectional AC-DC converter which ensures the effectiveness of MPC controller.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.5
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• pp.1093-1101
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• 2017

Microgrid as a unit component consisting a smart grid is an isolated system, which has a decentralized power supply system. This paper proposes an electrical isolation of the microgrid from the utiliy grid based on a power conditioning system, and also proposes an operation method maintaining the isolated state efficiently using diverse distributed energy resources such as renewable energy sources and energy storage system. The proposed system minimizes the influence of the grid connection on the internal load though a phase detection and synchrnoization to the utiligy grid and the microgrid can be stable even if the grid is failed.

• Journal of Power Electronics
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• v.17 no.6
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• pp.1433-1444
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• 2017

A family of non-isolated DC-DC three-port converters (TPCs) that allows for a more flexible power flow among a renewable energy source, an energy storage device and a current-reversible DC bus is introduced. Most of the reported non-isolated topologies in this area consider only a power consuming load. However, for applications such as hybrid-electric vehicle braking systems and DC microgrids, the load power generating capability should also be considered. The proposed three-port family consists of one unidirectional port and two bi-directional ports. Hence, they are well-suited for photovoltaic (PV)-battery-DC bus systems from the power flow viewpoint. Three-port converters are derived by combining different commonly known power converters in an integrated manner while considering the voltage polarity, voltage levels among the ports and the overall voltage conversion ratio. The derived converter topologies are able to allow for seven different modes of operation among the sources and load. A three-port converter which integrates a boost converter with a buck converter is used as a design example. Extensions of these topologies by combining the soft-switching technique with the proposed design example are also presented. Experiment results are given to verify the proposed three-port converter family and its analysis.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.12
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• pp.2157-2164
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• 2010

Microgrid is generally defined as cluster of small distributed generators, energy storages and loads. Through monitoring and coordinated control, microgrid can provide various benefits such as reduction of energy cost, peak shaving and power quality improvement. In design stage of microgrid, system dynamic simulation is necessary for optimizing of sizing and siting of DER(distributed energy resources). As number of the system components increases, simulation time will be longer. This problem can restrict optimal design. So we used simplified modeling on energy sources and average switching model on power converters to reduce simulation time. The effectiveness of this method is verified by applying to prototype microgrid system, which is consist of photovoltaic, wind power, diesel engine generators, battery energy storage system and loads installed in laboratory. Simulation by Matlab/Simulink and measurements on prototype microgrid show that the proposed method can reduce simulation time not sacrificing dynamic characteristics.

• Proceedings of the KIPE Conference
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• 2019.07a
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• pp.422-423
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• 2019

In accordance with the Carbon-Free Island by 2030 policy of Jeju Special Self-Governing Province, renewable energy sources are increasing in Jejudo Island. Due to the intermittent output characteristics of wind turbines, one of the renewable energy sources, which can cause unbalanced system conditions between the demand load and the power generation of Jejudo Island. The Korea Power Exchange limits the output of wind turbines for stabilizing the Jeju power system. Therefore, this paper proposes a method to supply a limited output of Sangmyeong Wind Farm in Jeju Power system to Energy Storage System(ESS) and Water Electrolysis Device(WED). The voltage and frequency fluctuation of the Jeju power system is checked accordingly. The simulation results are performed using the PSCAD/EMTDC program.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.2
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• pp.272-276
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• 2010

Renewable energy sources are considered to be environment-friendly alternatives those are increasingly introduced in the power systems. Microgrid is one of the systems in which renewable sources have a main role as a energy suppliers. Decision of constitution rates of renewable energy sources is very important for the economical and stable operation of microgird systems. In this paper, we present a method to assess an optimal constitution rate of renewable sources especially of windturbine and photovoltaic systems.

• 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.