• Proceedings of the KIPE Conference
• /
• 2015.11a
• /
• pp.155-156
• /
• 2015

본 논문은 마이크로그리드의 seamless mode transfer 를 위한 부하 위치에 따른 고조파 보상 기능을 가진 간접 전류 제어기법을 다루고 있다. 분산 발전 기반의 마이크로그리드는 계통 연계 모드와 독립 운전 모드시 각각 전류 제어기와 전압 제어기로 정의되며 각 모드에서 고품질의 전력공급을 위하여 강인한 제어기가 필요되어진다. 이때 계통 왜곡이나 비선형 부하의 연결등은 시스템의 전력 품질 악화를 초래할 수 있으며 이러한 문제를 해결하고자 많은 연구가 진행되었다. 본 논문에서는 계통연계 모드 뿐만 아니라 독립 운전 모드에서도 사용 가능한 비례공진 제어 기반의 간접 전류 제어기법을 제안하였고 부하 위치에 따른 고조파 보상 기법과 안정적인 모드변환을 동시에 고려하였다. 또한 비례 공진 제어기의 실용적인 모델을 사용함으로 인해 때때로 야기되는 독립 운전시의 전압 크기 감소에 대한 대책으로 적용이 간편한 전압 회복 기법도 추가되었다. 결과적으로 비선형 부하를 공급하기 위한 제안된 방식은 계통 연계와 독립 운전 모드에서 안정적인 전력 공급과 모드 절환 특성을 가짐을 PSIM 시뮬레이션을 통해 입증되었다.

• Journal of the Korean Society of Industry Convergence
• /
• v.23 no.6_2
• /
• pp.989-998
• /
• 2020

Recently, demands for large-capacity electronic loads are increasing in various industries such as a reliability test for the performance of a DC power supply device or a dummy-load for improving the stability of an independent microgrid to be actively built in the future. The electronic load required in these various fields requires an operation such as a continuously variable resistance load while minimizing the switching harmonic component generated in the electric load current in order to reduce the influence of interference from the load peripheral device. Electronic loads require a system that minimizes switching current ripple for load control. Therefore, in this paper, we propose a three-level module converter structure to reduce the current ripple of an electronic load, and a multilevel interleaved power converter topology to reduce the current ripple. The validity of the proposed electronic load, 3-level 6 interleaver converter, was verified by simulation and experiment. In addition, the user's convenience was provided by applying the emotional command curve interface method.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.1
• /
• pp.97-115
• /
• 2022

Smart power grid is a user friendly system that transforms the traditional electric grid to the one that operates in a co-operative and reliable manner. Demand Response (DR) is one of the important components of the smart grid. The DR programs enable the end user participation by which they can communicate with the electricity service provider and shape their daily energy consumption patterns and reduce their consumption costs. The increasing demands of electricity owing to growing population stresses the need for optimal usage of electricity and also to look out alternative and cheap renewable sources of electricity. The solar and wind energy are the promising sources of alternative energy at present because of renewable nature and low cost implementation. The proposed work models a smart home with renewable energy units. The random nature of the renewable sources like wind and solar energy brings an uncertainty to the model developed. A stochastic dual descent optimization method is used to bring optimality to the developed model. The proposed work is validated using the simulation results. From the results it is concluded that proposed work brings a balanced usage of the grid power and the renewable energy units. The work also optimizes the daily consumption pattern thereby reducing the consumption cost for the end users of electricity.

• New & Renewable Energy
• /
• v.18 no.1
• /
• pp.35-45
• /
• 2022

The renewable energy based MG is becoming one of the prominent solutions for greenhouse gas and constructing less power lines. However, how to procure the economics of MG considering the CO₂ emission and utility network impact is one of major issues as the proportion of renewable resource increases. This paper proposes the feasibility study scheme of campus MG and shows that the LCOE and CO₂ emission can be reduced by utilizing the excess power and introducing hydrogen system and plus DR. For this, the three cases: (a) adding the PV and selling excess power to utility, (b) producing and selling hydrogen using excess power, and (c) participating in plus DR are considered. For each case, not only the topology and component capacity of MG to secure economic feasibility, but also CO₂ emission and utility network effects are derived. If an electrolyzer with a capacity of 400 kW participates in plus DR for 3,730hours/year, the economic feasibility is securable if plus DR settlement and hydrogen sale price are more than 7.08¢/kWh and 8.3USD/kg or 6.25¢/kWh and 8.6USD/kg, respectively. For this end, continuous technical development and policy support for hydrogen system and plus DR are required.

• Korean Journal of Artificial Intelligence
• /
• v.11 no.2
• /
• pp.1-6
• /
• 2023

This paper presents a comprehensive scheme for assessing the importance of multiple microgrids (MGs) network that includes distributed energy resources (DERs), renewable energy systems (RESs), and energy storage system (ESS) facilities. Due to the uncertainty of severe weather, large-scale cascading failures are inevitable in energy networks. making the assessment of the structural vulnerability of the energy network an attractive research theme. This attention has led to the identification of the importance of measuring energy nodes. In multiple MG networks, the energy nodes are regarded as one MG. This paper presents a modified PageRank algorithm to assess the importance of MGs that include multiple DERs and ESS. With the importance rank order list of the multiple MG networks, the core MG (or node) of power production and consumption can be identified. Identifying such an MG is useful in preventing cascading failures by distributing the concentration on the core node, while increasing the effective link connection of the energy flow and energy trade. This scheme can be applied to identify the most profitable MG in the energy trade market so that the deployment operation of the MG connection can be decided to increase the effectiveness of energy usages. By identifying the important MG nodes in the network, it can help improve the resilience and robustness of the power grid system against large-scale cascading failures and other unexpected events. The proposed algorithm can point out which MG node is important in the MGs power grid network and thus, it could prevent the cascading failure by distributing the important MG node's role to other MG nodes.

• International conference on construction engineering and project management
• /
• 2022.06a
• /
• pp.937-944
• /
• 2022

Electric vehicles (EVs) have been growing to reduce energy consumption and greenhouse gas (GHG) emissions in the transportation sector. The increasing number of EVs requires adequate recharging infrastructure, and at the same time, adopts low- or zero-emission electricity production because the GHG emissions are highly dependent on primary sources of electricity production. Although previous research has studied solar photovoltaic (PV) -integrated EV charging stations, it is challenging to optimize spatial areas between where the charging stations are required and where the renewable energy sources (i.e., solar photovoltaic (PV)) are accessible. Therefore, the primary objective of this research is to support decisions of siting EV charging stations using a spatial data clustering method integrated with Geographic Information System (GIS). This research explores spatial relationships of PV power outputs (i.e., supply) and traffic flow (i.e., demand) and tests a community in the state of Indiana, USA for optimal sitting of EV charging stations. Under the assumption that EV charging stations should be placed where the potential electricity production and traffic flow are high to match supply and demand, this research identified three areas for installing EV charging stations powered by rooftop PV in the study area. The proposed strategies will drive the transition of existing energy infrastructure into decentralized power systems. This research will ultimately contribute to enhancing economic efficiency and environmental sustainability by enabling significant reductions in electricity distribution loss and GHG emissions driven by transportation energy.

• Journal of the Korean Society of Industry Convergence
• /
• v.26 no.6_3
• /
• pp.1259-1267
• /
• 2023

In recent years, as the demand for distributed power has increased, the need for microgrids connected to grid power and renewable power generation sources has emerged. In the case of DC microgrids, reactive power does not occur, and power conversion losses are reduced compared to AC when connecting to the load and power grid[2]. With the revitalization of the DC distribution network industry, various studies and demonstrations of DC microgrids have been carried out. In the case of the recent unit distribution, its stability and effectiveness have been verified through empirical and research analysis. However, there is a lack of empirical tests to prevent chain accidents for the protection of the power grid circuits and the misoperation of the distributed power system caused by individual accidents when connecting various distributed power sources and power grids. In this paper, the operation plan of a stable multi-circuit DC distribution connection for the demonstration site was verified through the protection cooperation and operation algorithm for the stable linkage management of the DC distribution network composed of such a multi-circuit.

• Journal of the Korean Society of Industry Convergence
• /
• v.26 no.6_3
• /
• pp.1269-1278
• /
• 2023

This paper presents an operational technique that can secure the stability of DC-Grid centering on MG operated based on ESS in multiple MG where three DC-based microgrid(MG) are interconnected. MG1(PV 600kWp, ESS 1.5MWh) has an 830Vdc grid voltage, MG2(PV 300kWp, ESS 1.1MWh) and MG3(PV 100kWp, ESS 500kWh) are DC-based MG with a 750Vdc grid voltage, and MG1 and MG2, 3 are linked by separate DC/DC converters (BTB). In order to keep different grid voltages stable, the power transmission capacity between MG1 and two MG(MG2, MG3) connected with an independent BTB converter was adjusted to secure the overall stability of the system, and this was verified by confirming that the surplus capacity of ESS was maintained in actual operation.

• Korean Journal of Artificial Intelligence
• /
• v.12 no.1
• /
• pp.17-24
• /
• 2024

This paper introduces a novel approach to time-series estimation for energy load forecasting within Virtual Power Plant (VPP) systems, leveraging advanced artificial intelligence (AI) algorithms, namely Long Short-Term Memory (LSTM) and Seasonal Autoregressive Integrated Moving Average (SARIMA). Virtual power plants, which integrate diverse microgrids managed by Energy Management Systems (EMS), require precise forecasting techniques to balance energy supply and demand efficiently. The paper introduces a hybrid-method forecasting model combining a parametric-based statistical technique and an AI algorithm. The LSTM algorithm is particularly employed to discern pattern correlations over fixed intervals, crucial for predicting accurate future energy loads. SARIMA is applied to generate time-series forecasts, accounting for non-stationary and seasonal variations. The forecasting model incorporates a broad spectrum of distributed energy resources, including renewable energy sources and conventional power plants. Data spanning a decade, sourced from the Korea Power Exchange (KPX) Electrical Power Statistical Information System (EPSIS), were utilized to validate the model. The proposed hybrid LSTM-SARIMA model with parameter sets (1, 1, 1, 12) and (2, 1, 1, 12) demonstrated a high fidelity to the actual observed data. Thus, it is concluded that the optimized system notably surpasses traditional forecasting methods, indicating that this model offers a viable solution for EMS to enhance short-term load forecasting.

• International Journal of Computer Science & Network Security
• /
• v.24 no.6
• /
• pp.33-40
• /
• 2024

Introducing renewable energy sources, such as wind and photovoltaic arrays, in microgrids that supply remote regions with electricity represents a significant leap in electricity generation. Combining photovoltaic panels and diesel engines is one of the most common ways to supply electricity to rural communities. Such hybrid systems can reduce the cost of electricity generation in these remote power systems because they use free energy to balance the power generated by diesel engines. However, the combination of renewable energy sources and diesel engines tends to complicate the sizing and control of the entire system due to the intermittent nature of renewable energy sources. This study sought to investigate this issue in depth. It proposes a robust hybrid controller that can be used to facilitate optimum power sharing between a PV power source and diesel generators based on the dynamics of the available PV energy at any given time. The study also describes a hybrid PV-diesel power plant's essential functional parts that produce electricity for a microgrid using a renewable energy source. Power control needs to be adjusted to reduce the cost of power generation.