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Abstract In recent years, many countries have been endeavoring to exploit the offshore wind energy in terms of overcoming the limitations of on-land wind energy. Considering that mountains cover 70 percent of the Korean Peninsula and arable plains for wind energy are negligibly small, Korean government aggressively drives the offshore wind development of the Korean Peninsula. In this context, KEPCO-RI (Korea Electric Power Corporation-Research Institute) has been performing a feasibility study for construction of the first offshore wind farm in Korea, including wind resource assessments around the Korean Peninsula. This paper provides a summary of the offshore wind resources of the Korean Peninsula, by analyzing marine buoy datasets measured at 5 positions over the period of 12 years, the QuikSCAT satellite data measured over 9 years, and a numerical wind map based on meteorological data measured for 4 years. Based on these datasets, wind resources are assessed, and economical efficiency is evaluated by means of the expected capacity factor. The analyzing results will be utilized to decide location of the first offshore wind farm in Korea.

Production and utilization of producer gas from mixed plastic wastes were investigated in a pilot-scale moving-grate gasification process. A 500 kWth moving-grate gasifier was developed, including ...

The current study aims to forecast and analyze wind data such as wind speed at a test site called “Urumsill” on Deokjeok Island, South Korea. The measured wind data available at the aforementioned test site are only for two years (2015 and 2016), making it impossible to analyze the long-term wind characteristics. In order to overcome this problem, two measure-correlate-predict (MCP) techniques were adopted using long-term wind data (2000–2016), measured by a meteorological mast (met-mast) installed at a distance of 3 km from the test site. The wind data measured at the test site in 2016 were selected as training data to build the MCP models, whereas wind data of 2015 were used to test the accuracy of MCP models (test data). The wind data at both sites were measured at a height of 10 m and showed a good agreement for the year 2016 (training period). Using the comparison results of the year 2016, wind speed predictions were made for the rest of the years (2000–2016) at the test site. The forecasted values of wind speed had maximum relative error in the range of ±0.8 m/s for the test year of 2105. The predicted wind data values were further analyzed by estimating the mean wind speed, the Weibull shape, and the scale parameters, on a seasonal and an annual basis, in order to understand the wind behavior in the region. The accuracy and presence of possible errors in the forecasted wind data are discussed and presented.

This paper presents the cooling performance of a water-to-refrigerant type ground heat source heat pump system (GSHP) installed in a school building in Korea. The evaluation of the cooling performance has been conducted under the actual operation of GSHP system in the summer of year 2007. Ten heat pump units with the capacity of 10 HP each were installed in the building. Also, a closed vertical typed-ground heat exchanger with 24 boreholes of 175 m in depth was constructed for the GSHP system. To analyze the cooling performance of the GSHP system, we monitored various operating conditions, including the outdoor temperature, the ground temperature, and the water temperature of inlet and outlet of the ground heat exchanger. Simultaneously, the cooling capacity and the input power were evaluated to determine the cooling performance of the GSHP system. The average cooling coefficient of performance (COP) and overall COP of the GSHP system were found to be ∼8.3 and ∼5.9 at 65% partial load condition, respectively. While the air source heat pump (ASHP) system, which has the same capacity with the GSHP system, was found to have the average COP of ∼3.9 and overall COP of ∼3.4, implying that the GSHP system is more efficient than the ASHP system due to its lower temperature of condenser.

AbstractIn order to meet the increasing demand of wind energy utilization, wind turbines (WTs) are developing toward the trend of large size and large capacity. In such a trend, various advanced yaw control strategies have been proposed to improve large WTs' comprehensive performance, but the analysis and summary of these strategies are still lacking. Therefore, it is necessary to have a review of yaw control, which not only enables readers to understand the current status of yaw control research but also promotes the development of wind energy technology. This paper presents a review of the current situation of yaw control for WTs, focusing on the mechanical/aerodynamic parts. The mechanical part is concerned with the WT yaw system and its effect on the fatigue load of the WT, and the aerodynamic part involves the wind energy capture and wake redirection to reduce the impact on adjacent WTs. In this review, the existing yaw control methods are classified in term of three control objectives: (1) increasing the wind energy capture of a single WT, (2) reducing the fatigue load of a single WT, and (3) maximizing the total power production of the whole wind farm and optimizing the wind farm fatigue load. On this basis, the control mechanism, the control algorithm, and the results are presented and analyzed in detail. Meanwhile, the advantages and disadvantages of the existing achievements are discussed. In addition, in a conclusion of the review, the future research direction has been identified.

This study investigates the performance of the “green refurbishment” of existing buildings. Two ordinary rooms in an existing building were chosen for examination. Refurbishment measures such as additional insulation, high-performance glazing, and air-tightening were applied to the control room. Temperature and electricity use were monitored to identify heating performance in winter and then compared with a baseline. The results of the field tests showed that green refurbishment significantly improved heating performance. Lowered heating load and electricity use with increased airtightness were also verified through building performance simulations. The empirical investigation suggests a predictive model to obtain indoor minimum temperatures as a function of outdoor temperature swings.

AbstractRepublic of Korea is the seventh largest CO2 emission country in 2010 and the third fastest country in the growth of CO2 emission according to the European Commission's Joint Research Center. To mitigate the effect of CO2 on the climate change and global warming, Korea should reduce the anthropogenic CO2 emissions from sources such as the power plants and iron works. So carbon dioxide capture and storage (CCS) technology is regarded as one of the most promising reduction options. This study established the CO2 transport strategies from the sources to sinks (such as the saline aquifers and gas fields in the Southeast Sea of the Korean Peninsula) for the offshore CCS in Korea. Also the cost estimations were carried out with the CO2 transport strategies. The CO2 transport methods suggested in this study were pipelines for both onshore and offshore, and a complex concept consisting of a pipeline for the source to coast (including the liquefaction facility on a barge) and a CO2 carrier for the coast to sink (including the temporary storage near offshore sink). With respect to the onshore pipelines, it was desirable to construct the CO2 transport pipelines along existing roads and/or LNG (liquefied natural gas) pipelines, as already realized in the United Kingdom (UK) and the Australia CO2 transport chains because of the cost and environmental aspects. The CO2 carrier was considered for the offshore CCS demonstration stage starting in 2016 to meet the timeline set by the Korea National CCS Master Plan. To optimize the CO2 transport systems, the advantages and drawbacks for the CO2 transport using the pipeline and shipping were analysed and the costs for them were also estimated with the CO2 transport strategies. There were several factors to be considered before constructing the CO2 pipelines including the amount of CO2, the terrain, the diameter of pipe, the transport pressure, the CO2 quality, the transport temperature, the CO2 state (i.e. gas, liquid or supercritical phases), etc. Also for the CO2 shipping it should be considered such as the amount of CO2, the shape and capacity of CO2 cargo tanks, the ship capacity, the liquefaction pressure and temperature, the type of the temporary storage, etc. Although the present study is now on-going to optimize the CO2 transport infrastructure for the offshore CCS in Korea, the preliminary results show the CO2 transport cost for the pipeline system is lower than that for the shipping in the present status.

$Q$ -learning-based operation strategies are being recently applied for optimal operation of energy storage systems, where, a $Q$ -table is used to store $Q$ -values for all possible state-action pairs. However, $Q$ -learning faces challenges when it comes to large state space problems, i.e., continuous state space problems or problems with environment uncertainties. In order to address the limitations of $Q$ -learning, this paper proposes a distributed operation strategy using double deep $Q$ -learning method. It is applied to managing the operation of a community battery energy storage system (CBESS) in a microgrid system. In contrast to $Q$ -learning, the proposed operation strategy is capable of dealing with uncertainties in the system in both grid-connected and islanded modes. This is due to the utilization of a deep neural network as a function approximator to estimate the $Q$ -values. Moreover, the proposed method can mitigate the overestimation that is the major drawback of the standard deep $Q$ -learning. The proposed method trains the model faster by decoupling the selection and evaluation processes. Finally, the performance of the proposed double deep $Q$ -learning-based operation method is evaluated by comparing its results with a centralized approach-based operation.