• 한국태양에너지학회:학술대회논문집
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• 2012.03a
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• pp.248-254
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• 2012

In the situation of expanding domestic solar power supply business long-term performance modeling of a proposed solar-cooling and cleaning system to increase electromotive force and light transmission is carried out to test the effectiveness of the system. To test the effectiveness of the system, the data which comparing the solar power planet installing the system to not installing at the same time is used. A difference between the utilization factor of each comparison group were recorded. Approximately from one year to two years Field Test was performed, Result of apply to cooling/cleaning technology, Each of plant by From least 7 percent up to 16 percent utilization factor increased, and the cooling / cleaning is output through improved as a result of the determined.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1408-1414
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• 2015

The renewable energies such as photovoltaic power, wind power and biomass have grown to a greater extent as decarbonization techniques. The renewable energies are interconnected to power systems (or electrical grids) in order to increase benefits from economies of scale, and the extra attention is focused on the Grid Code. A grid code defines technical parameters that power plants must meet to ensure functions of power systems, and the grid code determined by considering power system characteristics is various across the country. Some TSO (Transmission System Operator) and ISO (Independent System Operator) have issued grid code for wind power and the special requirements for offshore wind farm. The main purpose of the above grid code is that wind farm in power systems has to act as the existing power plants. Therefore wind farm developer and wind turbine manufacturer have great difficulty in grasping and meeting grid code requirements. This paper presents the basic understanding for grid codes of developed countries in the wind power and trends of those technical requirements. Moreover, in grid code viewpoint, the active power control of wind power is also discussed in details.

• Advances in Energy Research
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• v.5 no.2
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• pp.179-205
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• 2017

This research presents an in-depth analysis of location planning of the solar-hydrogen power plants for electricity production in different cities situated in Kerman province of Iran. Ten cities were analyzed in order to select the most suitable location for the construction of a solar-hydrogen power plant utilizing photovoltaic panels. Data envelopment analysis (DEA) methodology was applied to prioritize cities for installing the solar-hydrogen power plant so that one candidate location was selected for each city. Different criteria including population, distance to main road, flood risk, wind speed, sunshine hours, air temperature, humidity, horizontal solar irradiation, dust, and land costare used for the analysis. From the analysis, it is found that among the candidates' cities, the site of Lalezar is ranked as the first priority for the solar-hydrogen system development. A measure of validity is obtained when results of the DEA method are compared with the results of the technique for ordering preference by similarity to ideal solution (TOPSIS). Applying TOPSIS model, it was found that city of Lalezar ranked first, and Rafsanjan gained last priority for installing the solar-hydrogen power plants. Cities of Baft, Sirjan, Kerman, Shahrbabak, Kahnouj, Shahdad, Bam, and Jiroft ranked second to ninth, respectively. The validity of the DEA model is compared with the results of TOPSIS and it is demonstrated that the two methods produced similar results. The solar-hydrogen power plant is considered for installation in the city of Lalezar. It is demonstrated that installation of the proposed solar-hydrogen system in Lalezar can lead to yearly yield of 129 ton-H2 which covers 4.3% of total annual energy demands of the city.

• Journal of Climate Change Research
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• v.8 no.3
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• pp.213-220
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• 2017

The purpose of this study is to analyze effects of Greenhouse Gas (GHG) emission reduction in district energy business mainly based on Combined Heat and Power (CHP) plants. Firstly this paper compares the actual carbon intensity of power production between conventional power plants and district energy plants. To allocate the GHG from CHP plants, two of different methods which were Alternative Generation Method and Power Bonus Method, have been investigated. The carbon intensity of power production in district energy plants ($0.43tonCO_2e/MWh$) was relatively lower than conventional gas-fired power plants ($0.52tonCO_2e/MWh$). Secondly we assessed the cost effectiveness of reduction by district energy sector compared to the other means using TIMES model method. We find that GHG marginal abatement cost of 'expand CHP' scenario (-$134/ton$CO_2$) is even below than renewable energy scenario such as photovoltaic power generation ($87/ton$CO_2$). Finally the GHG emission reduction potential was reviewed on the projected GHG emission emitted when the same amount of energy produced in combination of conventional power plants and individual boilers as substitution of district energy. It showed there were 10.1~41.8% of GHG emission reduction potential in district energy compared to the combination of conventional power plants and individual boilers.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.1
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• pp.111-121
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• 2020

The study measures the resource use efficiency of diesel based power generation in the Maldives and analyses factors which influence efficiency levels. Stochastic frontier analysis (SFA) technique is applied to data on 30 plants over two year period from 2016 to 2017. The study finds that technical efficiency scores varies from 0.44 to 0.98 across power plants. About 33 percent of the plants have scores below the mean technical efficiency score of 0.87. Empirical results indicate ownership and use of solar photovoltaic (PV) have an influence on improving efficiency levels. Privately owned power plants in resort islands obtained higher technical efficiency scores compared to public and community owned power plants. This is a significant finding as the first study that used power plants in tourist sector in a comparative study. Size of the power plants was not found significant, but relatively small installed capacities can also be efficient. This finding is important because in many inhabited islands installed capacities remain oversized compared to the load. The benchmarking exercise offers model power plants that are relatively efficient, for other power plants and policy makers in small islands to learn from.

• Journal of Platform Technology
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• v.6 no.3
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• pp.38-46
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• 2018

Smart Grid is an intelligent power grid for efficiently producing and consuming electricity through bi-directional communication between power producers and consumers. As renewable energy develops, the share of renewable energy in the smart grid is increasing. Renewable energy has a problem that it differs from existing power generation methods that can predict and control power generation because the power generation changes in real time. Applying a self-adaptative framework to the Smart Grid will enable efficient operation of the Smart Grid by adapting to the amount of renewable energy power generated in real time. In this paper, we assume that smart villages equipped with photovoltaic power generation facilities are installed, and apply the self-adaptative framework, AiTES, to show that smart grid can be efficiently operated through self adaptation framework.

• ETRI Journal
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• v.45 no.4
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• pp.636-649
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• 2023

Renewable energy generation cannot be consistently predicted or controlled. Therefore, it is currently not widely used in the electricity market, which requires dependable production. In this study, reliability- and variance-based controls of energy storage strategies are proposed to utilize renewable energy as a steady contributor to the electricity market. For reliability-based control, photovoltaic (PV) generation is assumed to be registered in the power generation plan. PV generation yields a reliable output using energy storage units to compensate for PV prediction errors. We also propose a runtime state-ofcharge management method for sustainable operations. With variance-based controls, changes in rapid power generation are limited through ramp rate control. This study introduces new reliability and variance indices as indicators for evaluating these strategies. The reliability index quantifies the degree to which the actual generation realizes the plan, and the variance index quantifies the degree of power change. The two strategies are verified based on simulations and experiments. The reliability index improved by 3.1 times on average over 21 days at a real power plant.

• The Journal of Information Systems
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• v.27 no.2
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• pp.95-114
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• 2018

Purpose The recent concern over environmental problems such as greenhouse gas emission and fine dust contributes increasing interest in renewable energies. However the intrinsic characteristics of renewable energies, intermittent and stochastic generation, might cause serious problems to the stability and controllability of power grid. Therefore countermeasures such as virtual power plant (VPP) must be prepared in advance of the spread of uncontrollable distributed renewable energy resources to be one of major energy sources. Design/methodology/approach This study deals with the design concept of the VPP platform. we proposed as a technology solution for achieving the stability of power grid by guaranteeing a single power profile combining multiple distributed power sources with ICT. The core characteristics of VPP should be able to participate in the grid operation by responding to operation instructions from the system operator, KPX, as well as the wholesale electricity market. Findings Therefore this study includes energy storage device(ESS) as a controllable component as well as renewable energy resources such as photovoltaic and wind power generation. Based on this configuration, we discussed core element technologies of VPP and protype design of VPP solution platform according to system requirements. In the proposed solution platform, UX design for the integrated control center and brokerage system were included as well as ancillary service function to respond to KPX's operation instruction with utilizing the capability of ESS. In addition, a simulator was suggested to verify the VPP operations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.4
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• pp.113-118
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• 2019

A solar power plant is a facility that produces electricity. As the risk of fire and electric shock accidents is diversified, the risk of workers, surrounding people, and facilities is increased, preventing safety accidents and promptly responding to safety accidents Is emerging. In light of the necessity of such development, it is necessary to develop a solar power generation management system that can diagnose and maintain the problems of the power generation system in real time by developing technologies for collecting and analyzing the data produced by the solar power generation system As a result, the utilization rate and the maintenance cost can be reduced. In order to do this, it is necessary to accurately predict the solar power generation amount in the present state, to diagnose the abnormality of the current power generation state and to grasp the abnormal position, and to use the model considering economical efficiency when the abnormal position is grasped, And the time and other information should be provided.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.219-224
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• 2019

The number of solar power installation companies including domestic small scale (50kW or less) is increasing rapidly, but the efficient operation system and management are insufficient. Therefore, a new type of operating system is needed as a maintenance management aspect to maximize the generation amount in the current state rather than the additional function which causes the increase of the generation cost. In this paper, we utilize Big Data and sensor network to maximize the operating efficiency of solar power plant and analyze the expert system to develop power generation prediction technology, module unit fault detection technology, life prediction of inverter components and report technology, maintenance optimization And to develop a smart monitoring system that enables optimal operation of photovoltaic power plants such as development of algorithms and economic analysis.