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RISS 인기검색어
- 검색키워드
- 저자 : Yuwei Gao (검색결과 5 건)
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Yang Yuwei,Gao Jie,Gu Hai,Imani Marani Hashem 대한전기학회 2023 Vol.18 No.1
This paper presents a novel hybrid approach by integrating the imperialist competitive algorithm (ICA) with particle swarm optimization (PSO) method to deal with the combined heat and power economic dispatch (CHPED) problem with the bounded feasible operating region. Unlike many previous methods, this approach takes the valve-point eff ects explicitly into account as an absolute sinusoidal term in the conventional polynomial cost function. The effi ciency and feasibility of the hybrid scheme are evaluated on three small (with three diff erent scenarios), medium and large test systems. The simulation results suggest the superior performance of the proposed hybrid algorithm in fi nding optimum solutions compared to other existing methods.
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Yang Yuwei,Gao Jie,Gu Hai,Imani Marani Hashem 대한전기학회 2023 Journal of Electrical Engineering & Technology Vol.18 No.1
This paper presents a novel hybrid approach by integrating the imperialist competitive algorithm (ICA) with particle swarm optimization (PSO) method to deal with the combined heat and power economic dispatch (CHPED) problem with the bounded feasible operating region. Unlike many previous methods, this approach takes the valve-point effects explicitly into account as an absolute sinusoidal term in the conventional polynomial cost function. The efficiency and feasibility of the hybrid scheme are evaluated on three small (with three different scenarios), medium and large test systems. The simulation results suggest the superior performance of the proposed hybrid algorithm in finding optimum solutions compared to other existing methods.
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Li Zhufeng,Gao Jie,Yang Yuwei 대한전기학회 2024 Journal of Electrical Engineering & Technology Vol.19 No.3
With the advancement of technology and human movement towards evolution, intelligent control methods are becoming more important. One of the areas of progress is related to the development of new frameworks for electricity generation and distribution systems, and the microgrid structure with economic capabilities is one of the frameworks. Accordingly, this paper presents a new practical method for controlling the frequency of microgrids and is able to cover the following issues at the same time. 1- It considers the nonlinear model of provisional microgrid which has a hybrid structure (AC and DC) in addition to renewable energy sources. 2- Introduces a method for microgrid frequency control under different operational conditions that performs based on the brain emotional learning. 3- Ensures the operation and applicability of the control method for the provisional microgrid through implementation of FPGA for the first time 4- Confirms the robustness of the proposed method under extreme load changes. So, in the simulation scenarios, the effects of wind turbine and solar energy are considered and under the influence of various changes in load and system uncertainties, the robustness and efficiency of the proposed method are well demonstrated. With the advancement of technology and human movement towards evolution, intelligent control methods are becoming more important. One of the areas of progress is related to the development of new frameworks for electricity generation and distribution systems, and the microgrid structure with economic capabilities is one of the frameworks. Accordingly, this paper presents a new practical method for controlling the frequency of microgrids and is able to cover the following issues at the same time. 1- It considers the nonlinear model of provisional microgrid which has a hybrid structure (AC and DC) in addition to renewable energy sources. 2- Introduces a method for microgrid frequency control under diferent operational conditions that performs based on the brain emotional learning. 3- Ensures the operation and applicability of the control method for the provisional microgrid through implementation of FPGA for the frst time 4- Confrms the robustness of the proposed method under extreme load changes. So, in the simulation scenarios, the efects of wind turbine and solar energy are considered and under the infuence of various changes in load and system uncertainties, the robustness and efciency of the proposed method are well demonstrated.
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Yuetao Li,Yongkun Zhao,Cuiling Wang,Xuexing Zheng,Hualei Wang,Weiwei Gai,Hongli Jin,Feihu Yan,Boning Qiu,Yuwei Gao,Nan Li,Songtao Yang,Xianzhu Xia 대한수의학회 2018 Journal of Veterinary Science Vol.19 No.2
Rift Valley fever (RVF) is an acute, febrile zoonotic disease that is caused by the RVF virus (RVFV). RVF is mainly prevalent on the ArabianPeninsula, the African continent, and several islands in the Indian Ocean near southeast Africa. RVFV has been classified by the WorldOrganisation for Animal Health (OIE) as a category A pathogen. To avoid biological safety concerns associated with use of the pathogen inRVFV neutralization assays, the present study investigated and established an RVFV pseudovirus-based neutralization assay. This study usedthe human immunodeficiency virus (HIV) lentiviral packaging system and RVFV structural proteins to successfully construct RVFVpseudoviruses. Electron microscopy observation and western blotting indicated that the size, structure, and shape of the packagedpseudoviruses were notably similar to those of HIV lentiviral vectors. Infection inhibition assay results showed that an antibody against RVFVinhibited the infective ability of the RVFV pseudoviruses, and an antibody neutralization assay for RVFV detection was then established. Thisstudy has successfully established a neutralization assay based on RVFV pseudoviruses and demonstrated that this method can be used toeffectively evaluate antibody neutralization.
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