• 전기학회논문지
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• 제60권4호
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• pp.705-710
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• 2011

This paper proposes establishment of generator maintenance scheduling(GMS) considering minimization of $CO_2$ emissions. The objective function model to minimize $CO_2$ emissions is used in this paper. In this paper, and also, GMS is established due to freedom of GMS of generators owned by a designated generation company. The practicality and effectiveness of the proposed approach are demonstrated by simulation studies for a real size power system model in Korea in 2010.

• Structural Engineering and Mechanics
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• 제50권3호
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• pp.257-273
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• 2014

This paper introduces a novel optimization technique based on gravitational search algorithm (GSA) for numerical optimization and multi-objective optimization of foundation. In the proposed method, a chaotic time varying system is applied into the position updating equation to increase the global exploration ability and accurate local exploitation of the original algorithm. The new algorithm called global-local GSA (GLGSA) is applied for optimization of some well-known mathematical benchmark functions as well as two design examples of spread foundation. In the foundation optimization, two objective functions include total cost and $CO_2$ emissions of the foundation subjected to geotechnical and structural requirements are considered. From environmental point of view, minimization of embedded $CO_2$ emissions that quantifies the total amount of carbon dioxide emissions resulting from the use of materials seems necessary to include in the design criteria. The experimental results demonstrate that, the proposed GLGSA remarkably improves the accuracy, stability and efficiency of the original algorithm.

• 해양환경안전학회지
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• 제28권3호
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• pp.451-458
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• 2022

In Korea, five major ports have been designated as sulfur oxide emission control areas to reduce air pollutant emissions, in accordance with Article 10 of the "Special Act on Port Air Quality" and Article 32 of the "Ship Pollution Prevention Regulations". As regulations against vessel-originated air pollutants (such as PM, CO2, NOx, and SOx) have been strengthened, the Ministry of Oceans and Fisheries(MOF) enacted rules that newly built public ships should adopt eco-friendly propulsion systems. However, particularly in diesel-electric hybrid propulsion systems,the demand for precise control schemes continues to grow as the fuel saving rate significantly varies depending on the control strategy applied. The conventional Power Take In-Power Take Off(PTI - PTO) mode control adopts a rule-based strategy, but this strategy is applied only in the low-load range and PTI mode; thus, an additional method is required to determine the optimal fuel consumption point. The proposed control method is designed to optimize fuel consumption by applying the equivalent consumption minimization strategy(ECMS) to the PTI - PTO mode by considering the characteristics of the specific fuel oil consumption(SFOC) of the engine in a diesel-electric hybrid propulsion system. To apply this method, a specific fishing vessel model operating on the Korean coast was selected to simulate the load operation environment of the ship. In this study, a 10.2% reduction was achieved in the MATLAB/SimDrive and SimElectric simulation by comparing the fuel consumption and CO2 emissions of the ship to which the conventional rule-based strategy was applied and that to which the ECMS was applied.

• Structural Engineering and Mechanics
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• 제89권5호
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• pp.453-466
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• 2024

In this study, the optimization of the composite floor system with cellular beams is investigated. The objective function is the minimization of carbon dioxide (CO₂) emissions and the optimal solution is defined by 19 design variables for the beam's topology, beams fabricated process, steel deck characteristics, columns. The requirements of the ultimate and serviceability state limits are considered for the composite floor system design. The program is developed within the MATLAB platform. A number of the benchmark test problems of composite floor systems with full web beams are optimized with cellular beams to verify the reduction of total CO₂ emission. The optimum results are obtained by Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Bonobo Algorithm (BO). A comparison of the performance of these algorithms shows that the BO algorithm has a higher search capability and results in better solutions than PSO and GA algorithms in the optimization of the composite floor system with the cellular beams and the use of cellular beams can reduce the total CO₂ emissions of the floor above 20%.

• 한국조경학회지
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• 제27권1호
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• pp.39-53
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• 1999

This study quantified carbon uptake and emissions in urban landscape, and the role of urban greenspace in atmospheric carbon reduction for several cities of Chuncheon and Kangleung in Kangwon province. Mean carbon storage by trees and shrubs was 26.0 t (mertric tons)/ha in Chuncheon and 46.7 t/ha in Kangleung for natural lands, and ranged from 4.7 to 6.3 t/ha for urban lands (all land use types except natural and agricultural lands) in both cities. Mean annual carbon uptake by trees and shrubs ranged from 1.60 to 1.71 t/ha/yr for natural lands, and from 0.56 to 0.71 t/ha/yr for urban lands. There was no significant difference (95% confidence level) between the two cities in the carbon storage and annual carbon uptake per ha, except the carbon storage for natural lands. Organic carbon storage in soils (to a depth of 60 cm) of Chuncheon average 24.8 t/ha for urban lands and 31.6 t/ha for natural lands, 1.3 times greater than for urban lands. Annual carbon accumulation in soils was 1.3 t/hr/yr for natural lands of the study cities. Annual per capita carbon emissions from fossil fuel consumption were 1.3 t/yr in Chunceon and 1.8 t/yr in Kangleung. The principal carbon release in urban landscapes was from transport and industry. Total carbon storage by urban greenspace (trees, shrubs, and soils) equaled 66% of total carbon emissions in Chuncheon and 101% in Kangleung. Carbon uptake by urban greenspace annually offset total carbon emissions by approximately 4% in the study cities. Thus, urban greenspace played a partial important role in reducing atmospheric $CO_2$ concentrations. To increase $CO_2$ uptake and storage by urban greenspace, suggested are conservation of natural lands, minimization of hard surfaces and more plantings, selection of tree species with high growth rate, and proper management for longer healthy tree growth.

• 한국자동차공학회논문집
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• 제15권2호
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• pp.22-27
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• 2007

Our environment is faced with serious problems related to the air pollution from automobiles in these days. In particular, the exhaust emissions of diesel engines are recognized as main causes of the air pollution. CRDI(common rail direct injection) diesel engine is widely used for the sake of minimization on exhaust emission. Because biodiesel fuel is a renewable and alternative fuel for diesel engine, its usability is expanded. In this study, a common rail diesel engine was run with 5% of biodiesel fuel(BDF 5%) more than 150 hours. Engine dynamometer testing was completed at regularly scheduled intervals to investigate the engine performance and exhaust emissions. The data of engine performance and exhaust emissions was sampled at 1 hour intervals for analysis. When a common rail diesel engine runs on BDF 5% for long time, power and energy consumption of the engine are similar to the case using diesel fuel. The smoke emission of BDF 5% was reduced in comparison with diesel fuel, that is, it was reduced approximately 15% at 4000rpm, and load of 90%. And, CO and $CO_2$ were reduced, too. On the other hand, NOx emission of biodiesel fuel was slightly increased about 2%, but it was almost same as a commercial diesel fuel.

• Journal of Electrical Engineering and Technology
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• 제9권2호
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• pp.433-440
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• 2014

In this study, a method for the low-carbon active distribution system (ADS) planning is proposed. It takes into account the impacts of both network capacity and demand correlation to the renewable energy accommodation, and incorporates demand response (DR) as an available resource in the ADS planning. The problem is formulated as a mixed integer nonlinear programming model, whereby the optimal allocation of renewable energy sources and the design of DR contract (i.e. payment incentives and default penalties) are determined simultaneously, in order to achieve the minimization of total cost and $CO_2$ emissions subjected to the system constraints. The uncertainties that involved are also considered by using the scenario synthesis method with the improved Taguchi's orthogonal array testing for reducing information redundancy. A novel cuckoo search (CS) is applied for the planning optimization. The case study results confirm the effectiveness and superiority of the proposed method.