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[IEEE 2020 IEEE 33rd International Conference on Micro Electro Mechanical Systems (MEMS) - Vancouver, BC, Canada (2020.1.18-2020.1.22)] 2020 IEEE 33rd International Conference on Micro Electro Mechanical Systems (MEMS) - RGB all Liquid-Based Microfluidic Quantum Dots Light-Emitting Diodes Using Deep-Blue Liquid Organic Semiconductor Backlight
摘要： This paper presents a cost-effective system-level restoration scheme to improve power grids resilience by efficient response to the damages due to natural or manmade disasters. A post-disaster decision making model is developed to find the optimal repair schedule, unit commitment solution, and system configuration in restoration of the damaged power grid. The physical constraints of the power grid, associated with the unit commitment and restoration, are considered in the proposed model. The value of lost load is used as a viable measure to represent the criticality of each load in the power grid. The model is formulated as a mixed-integer program and, then, is decomposed into an integer master problem and a dual linear subproblem to be solved using Benders decomposition algorithm. Different scenarios are developed to analyze the proposed model on the standard IEEE 118-bus test system. This paper provides a prototype and a proof of concept for utility companies to consider economics of disaster and include unit commitment model into the post-disaster restoration process.
关键词： restoration,power grid,unit commitment,Disaster management
更新于2025-09-23 15:21:01
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Switched Capacitor-Coupled Inductor DCa??DC Converter for Grid-Connected PV System using LFCSO-Based Adaptive Neuro-Fuzzy Inference System
摘要： In this paper, the Levy °ight-based chicken swarm optimization (LFCSO) is proposed to follow the highest power of grid-joined photovoltaic (PV) framework. To analyze the grid-associated PV framework, the characteristics of current, power, voltage, and irradiance are determined. Because of the low yield voltage of the source PV, a big advance up converter with big productivity is required when the source PV is associated with the matrix power. A tale great advance up converter dependent on the exchanged capacitor and inductor is illustrated in this paper. The LFCSO algorithm with the adaptive neuro-fuzzy inference system is used to generate the control pulses of the transformer-coupled inductor DC–DC converter-less switched capacitor. While using the switched capacitor-coupled inductor, the voltage addition is expanded in the DC–DC converter and the power of PV is maximized. Here, the normal CSO algorithm is updated with the help of Levy °ight functions to generate optimal results. To get the accurate optimal results, the output of the proposed LFCSO algorithm is given as the input of the ANFIS technique. After that, the optimal results are generated and they provide the pulses for the system. The working guideline is analyzed and the voltage addition is derived with the utilization of the proposed technique. From that point forward, it predicts the exact maximum power of the converter according to its inputs. Under the variety of solar irradiance and partial shading conditions (PSCs), the PV system is tested and its characteristics are analyzed in di?erent time instants. The proposed LFCSO with ANFIS method is actualized in Simulink/MATLABstage, and the tracking executing is examined with a traditional method such as genetic algorithm (GA), perturb and observe (P&O) technique–neuro-fuzzy controller (NFC) and fuzzy logic controller (FLC) technique.
关键词： irradiance,Levy °ight-based chicken swarm optimization algorithm,partial shading conditions,transformer-less switched capacitor-coupled inductor DC–DC converter voltage,current,power,grid-connected PV,GA-NFC and FLC methods
更新于2025-09-23 15:19:57
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[IEEE 2019 21st International Conference on Transparent Optical Networks (ICTON) - Angers, France (2019.7.9-2019.7.13)] 2019 21st International Conference on Transparent Optical Networks (ICTON) - Progress in Development of Nanostructured Gradient Index Optical Fibers and Micro-Optical Components
摘要： This paper presents a cost-effective system-level restoration scheme to improve power grids resilience by efficient response to the damages due to natural or manmade disasters. A post-disaster decision making model is developed to find the optimal repair schedule, unit commitment solution, and system configuration in restoration of the damaged power grid. The physical constraints of the power grid, associated with the unit commitment and restoration, are considered in the proposed model. The value of lost load is used as a viable measure to represent the criticality of each load in the power grid. The model is formulated as a mixed-integer program and, then, is decomposed into an integer master problem and a dual linear subproblem to be solved using Benders decomposition algorithm. Different scenarios are developed to analyze the proposed model on the standard IEEE 118-bus test system. This paper provides a prototype and a proof of concept for utility companies to consider economics of disaster and include unit commitment model into the post-disaster restoration process.
关键词： power grid,restoration,Disaster management,unit commitment
更新于2025-09-19 17:13:59