• Journal of Korea Water Resources Association
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• v.43 no.2
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• pp.131-138
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• 2010

Due to the increased water demand and severe drought as an effect of the global warming, the effluent from wastewater treatment plants becomes considered as an alternative water source to supply agricultural, industrial, and public (gardening) water demand. The effluent from the wastewater treatment plant is a sustainable water source because of its good quality and stable amount of water discharge. In this study, the water reuse system was developed to minimize total construction cost to cope with the uncertain water demand in future using two-stage stochastic linear programming with binary variables. The pipes in the water reuse network were constructed in two stages of which in the first stage, the water demands of users are assumed to be known, while the water demands in the second stage have uncertainty in the predicted value. However, the water reuse system has to be designed now when the future water demands are not known precisely. Therefore, the construction of a pipe parallel with the existing one was allowed to meet the increased water demands in the second stage. As a result, the trade-off of construction costs between a pipe with large diameter and two pipes having small diameters was evaluated and the optimal solution was found. Three scenarios for the future water demand were selected and a hypothetical water reuse network considering the uncertainties was optimized. The results provide the information about the economies of scale in the water reuse network and the long range water supply plan.

• Environmental and Resource Economics Review
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• v.30 no.2
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• pp.237-268
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• 2021

As variable renewable sources rapidly increase due to the Energy Transition plan, integration cost of renewable sources to the power system is rising sharply. The increase in variable renewable energy reduces the capacity factor of existing traditional power capacity, and this undermines the efficiency of the overall power supply, and demand resources are drawing attention as a solution. In this study, we analyzed how much electric vehicle demand resouces, which has great potential among other demand resources, can reduce power supply costs if it is used as a flexible resource for renewable generation. As a methodology, a stochastic form of power system optimization model that can effectively reflect the volatile characteristics of renewable generation is used to analyze the cost induced by renewable energy and the benefits offered by electric vehicle demand resources. The result shows that virtual power plant-based direct control method has higher benefits than the time-of-use tariff, and the higher the proportion of renewable energy is in the power system, the higher the benefits of electric vehicle demand resources are. The net benefit after considering commission fee for aggregators and battery wear-and-tear costs was estimated as 67% to 85% of monthly average fuel cost under virtual power plant with V2G capability, and this shows that a sufficient incentive for market participation can be offered when a rate system is applied in which these net benefits of demand resources are effectively distributed to consumers.

• Environmental and Resource Economics Review
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• v.33 no.2
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• pp.113-133
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• 2024

Variable renewable energy (VRE) such as solar and wind power is the main sources of achieving carbon net zero, but it undermines the stability of power supply due to high variability and uncertainty. Energy storage system (ESS) can not only reduce the curtailment of VRE by load shifting but also contribute to stable power system operation by providing ancillary services. This study analyzes how the allocation of ESS resources between load shifting and ancillary service can contribute to maximizing the efficiency of power supply in a situation where the problems caused by VRE are becoming more and more serious. A stochastic power system optimization model that can realistically simulate the variability and uncertainty of VRE was applied. The analysis time point was set to 2023 and 2036, and the optimal resource allocation strategy and benefits of ESS by varying VRE penetration levels were analyzed. The analysis results can be largely summarized into the following three. First, ESS provides excellent functions for both load shifting and ancillary service, and it was confirmed that the higher the reserve price, the more limited the load shifting and focused on providing reserve. Second, the curtailment of VRE can be a effective substitute for the required reserve, and the higher the reserve price level, the higher the curtailment of VRE and the lower the required amount of reserve. Third, if a reasonable reserve offer price reflecting the opportunity cost is applied, ESS can secure economic feasibility in the near future, and the higher the proportion of VRE, the greater the economic feasibility of ESS. This study suggests that cost-effective low-carbon transition in the power system is possible when the price signal is correctly designed so that power supply resources can be efficiently utilized.

• The KIPS Transactions:PartB
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• v.10B no.6
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• pp.657-664
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• 2003

Reliable tracking of moving humans is essential to motion estimation, video surveillance and human-computer interface. This paper presents a new approach to human motion tracking that combines appearance-based and model-based techniques. Monocular color video is processed at both pixel level and object level. At the pixel level, a Gaussian mixture model is used to train and classily individual pixel colors. At the object level, a 3D human body model projected on a 2D image plane is used to fit the image data. Our method does not use inverse kinematics due to the singularity problem. While many others use stochastic sampling for model-based motion tracking, our method is purely dependent on nonlinear programming. We convert the human motion tracking problem into a nonlinear programming problem. A cost function for parameter optimization is used to estimate the degree of the overlapping between the foreground input image silhouette and a projected 3D model body silhouette. The overlapping is computed using computational geometry by converting a set of pixels from the image domain to a polygon in the real projection plane domain. Our method is used to recognize various human motions. Motion tracking results from video sequences are very encouraging.