• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.4
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• pp.932-938
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• 2017

This paper presents the structure of an energy management system for distributed energy resources of a grid-connected microgrid. The energy management system of a grid-connected microgrid collects information of the microgrid such as the status of distributed energy resources and the time varying pricing plan through various protocols. The energy management system performs forecasting and optimization based on the collected information. It derives the operation schedule of distributed energy resources to reduce the microgrid electricity bill. In order to achieve optimal operation, the energy management system should include an optimal scheduling algorithm and a protocol that transfers the derived schedule to distributed energy resources. The energy management system operates as a rolling horizon controller in order to reduce the effect of a prediction error. Derived control schedules are transmitted to the distributed energy resources in real time through the international standard communication protocol.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.8
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• pp.133-141
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• 2010

MG(Microgrid) is a small power supply system located on-site that can supply both the electricity and the hot-water simultaneously. Engineering S/W is requested to construct Microgrids economically. We developed Engineering S/W that can combine DERs (Distributed Energy Resources) most economically using the linear programming and estimate of the economic. Developed S/W was programed using GAMS(General Algebraic Modeling System) and it is composed of the optimal DER combination module and forecasting module of renewable energy's output. We embody it based on MS Excel considering the user's convenience and we show its validity through a case study. We think that developed S/W will be very useful for planning MGs and energy supply.

• Journal of Power Electronics
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• v.15 no.2
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• pp.455-468
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• 2015

A microgrid (MG) with integrated renewable energy resources can benefit both utility companies and customers. As a result, they are attracting a great deal of attention. The control of a MG is very important for the stable operation of a MG. The droop-control method is popular since it avoids circulating currents among the converters without using any critical communication between them. Traditional droop control methods have the drawback of an inherent trade-off between power sharing and voltage and frequency regulation. An adaptive droop control method is proposed, which can operate in both the island mode and the grid-connected mode. It can also ensure smooth switching between these two modes. Furthermore, the voltage and frequency of a MG can be restored by using the proposed droop controller. Meanwhile, the active power can be dispatched appropriately in both operating modes based on the capacity or running cost of the Distributed Generators (DGs). The global information (such as the average voltage and output active power of the MG and so on) required by the proposed droop control method to restore the voltage and frequency deviations can be acquired distributedly based on the Multi Agent System (MAS). Simulation studies in PSCAD demonstrate the effectiveness of the proposed control method.

• Journal of Power Electronics
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• v.15 no.4
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• pp.1105-1118
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• 2015

Battery energy storage devices (ESDs) have become more and more commonplace to maintain the stability of islanded power systems. Considering the limitation in inverter capacity and the requirement of flexibility in the ESD, the droop control was implemented in paralleled ESDs for higher capacity and autonomous operation. Under the conventional droop control, state-of-charge (SoC) errors between paralleled ESDs is inevitable in the discharging operation. Thus, some ESDs cease operation earlier than expected. This paper proposes an adaptive accelerating parameter to improve the performance of the SoC error eliminating droop controller under the constraints of a microgrid. The SoC of a battery ESD is employed in the active power droop coefficient, which could eliminate the SoC error during the discharging process. In addition, to expedite the process of SoC error elimination, an adaptive accelerating parameter is dedicated to weaken the adverse effect of the constraints due to the requirement of the system running. Moreover, the stability and feasibility of the proposed control strategy are confirmed by small-signal analysis. The effectiveness of the control scheme is validated by simulation and experiment results.

• Journal of Power Electronics
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• v.19 no.3
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• pp.784-793
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• 2019

Two objectives can be pursued simultaneously with the ${\delta}$ control of a single-phase electric spring (ES). These objectives are the stabilization of the voltage across the critical load (CL) of a power system, and the achievement of a specific functionality similar to the pure compensation of reactive power or the correction of the power factor. However, existing control systems implementing the ${\delta}$ control do not cope with non-ideal operating conditions, such as line voltage distortions, and exhibit a somewhat sluggish regulation of the CL voltage. In an effort to improve both the steady-state and transient performances of an ES power system, this paper proposes implementing the ${\delta}$ control by means of a control system built up on the repetitive control and assisted by state feedback with pole assignment. This paper starts by analyzing the dynamics of an ES power system in terms of its poles and zeros. After that, a reduced second-order model of the dynamics is formulated to avoid a notch filter in the pole assignment. A repetitive control for an ES power system is then designed to meet the two above mentioned objectives. Experimental tests carried out on a laboratory setup demonstrate the effectiveness of the proposed control system in significantly improving the ES power system performance, while reaching the two objectives. In particular, the tests outline the large mitigation of harmonics in the CL voltage under line voltage distortions and its fast stabilization action.

• Current Photovoltaic Research
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• v.9 no.2
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• pp.59-73
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• 2021

The purpose of this study is to develop a business model that efficiently converts diesel power generation systems to renewable energy microgrids (MG) in large-scale islands. Most of the previous studies on the conversion of renewable energy MG in islands had limitations dealing with efficiency from the perspective of suppliers. However, the microgrid has the characteristic of getting benefits through the interaction between the consumer and the supplier. In addition, the efficient MG business model from the perspective of new institutional economics is a structure in which consumers and suppliers jointly participate. Therefore, this study assumed that the MG business model in which the supplier's MG and the consumer's community solar participated would benefit all participants, and verified the assumptions using domestic island data. In terms of supplier investment, the cost of power supply (LCOE) of assumed model was calculated to be 14.0% lower than that of the diesel model and 3.7% lower than that of the supplier-only MG model. From the perspective of consumer investment, electricity bills are expected to be reduced by more than 200,000 won per household per year through self-generation of solar power. Social benefits are expected to reduce external environmental costs. The CO₂ emissions of the assumed model were calculated to be 39.5% lower than the diesel model and 1.5% lower than the supplier-only MG model. Therefore, the MG business model with consumer participation proposed in this study is expected to be an efficient alternative to renewable energy MG conversion in domestic islands, and is meaningful as an energy plan that improves the benefits of local residents.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.175-181
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• 2021

This paper analyzes the artificial intelligence-based approach for short-term energy consumption prediction. In this paper, we employ the reinforcement learning algorithms to improve the limitation of the supervised learning algorithms which usually utilize to the short-term energy consumption prediction technologies. The supervised learning algorithm-based approaches have high complexity because the approaches require contextual information as well as energy consumption data for sufficient performance. We propose a deep reinforcement learning algorithm based on multi-agent to predict energy consumption only with energy consumption data for improving the complexity of data and learning models. The proposed scheme is simulated using public energy consumption data and confirmed the performance. The proposed scheme can predict a similar value to the actual value except for the outlier data.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.36 no.4
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• pp.369-375
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• 2023

In this paper, we compared and analyzed the power load patterns of dormitory buildings and office buildings to use them as basic data (demand analysis and capacity design) for the design and operation of microgrids for multi-use facilities, and the following conclusions were got. During the daytime on regular weekdays, the power consumption load pattern of office buildings was relatively large at 264.0~332.3 kWh, and during the evening hours, the power consumption load pattern of dormitory buildings was relatively large at 233.0~258.3 kWh. In the case of vacation, during the daytime on weekdays, the power consumption load pattern of office buildings was relatively large at 279.1~407.4 kWh, and in the evening, the power consumption load pattern of dormitory buildings was relatively high at 280.1~394.1 kWh. During the daytime on regular weekends, the power consumption of dormitory-type buildings was relatively high at 133.5~201.6 kWh, and it was found that the power consumption of dormitory-type buildings appeared relatively high at 187.5~252.1 kWh. During a vacation in the daytime on weekends, the power consumption of dormitory-type buildings was found to be 186.5 kWh~ and 218.6 kWh. The increase in power consumption during a vacation (December-February) compared to normal (April-June) was thought to be due to an increase in electricity demand, and the reason for the higher power consumption in dormitory buildings during the vacation was due to reduced working hours in office buildings.