Smart grids and their technologies transform the traditional electric grids to assure safe,secure,cost-effective,and reliable power transmission.Non-linear phenomena in power systems,such as voltage collapse and oscil...Smart grids and their technologies transform the traditional electric grids to assure safe,secure,cost-effective,and reliable power transmission.Non-linear phenomena in power systems,such as voltage collapse and oscillatory phenomena,can be investigated by chaos theory.Recently,renewable energy resources,such as wind turbines,and solar photovoltaic(PV)arrays,have been widely used for electric power generation.The design of the controller for the direct Current(DC)converter in a PV system is performed based on the linearized model at an appropriate operating point.However,these operating points are everchanging in a PV system,and the design of the controller is usually accomplished based on a low irradiance level.This study designs a fractional-order proportional-integrated-derivative(FOPID)controller using deep learning(DL)with quasi-oppositional Archimedes Optimization algorithm(FOPID-QOAOA)for cascaded DC-DC converters in micro-grid applications.The presented FOPIDQOAOA model is designed to enhance the overall efficiency of the cascaded DC-DC boost converter.In addition,the proposed model develops a FOPID controller using a stacked sparse autoencoder(SSAE)model to regulate the converter output voltage.To tune the hyper-parameters related to the SSAE model,the QOAOA is derived by the including of the quasi-oppositional based learning(QOBL)with traditional AOA.Moreover,an objective function with the including of the integral of time multiplied by squared error(ITSE)is considered in this study.For validating the efficiency of the FOPID-QOAOA method,a sequence of simulations was performed under distinct aspects.A comparative study on cascaded buck and boost converters is carried out to authenticate the effectiveness and performance of the designed techniques.展开更多
The suitability of using precipitated silica(PS) from the burning of rice husk was investigated to improve the geotechnical engineering properties of a black cotton soil. A laboratory experimental program consisting o...The suitability of using precipitated silica(PS) from the burning of rice husk was investigated to improve the geotechnical engineering properties of a black cotton soil. A laboratory experimental program consisting of series of specific gravity, Atterberg limits, compaction, California bearing ratio(CBR), unconfined compression and consolidation tests was conducted on the untreated and PS treated soil samples. The application of PS to the soil significantly changed its properties by reducing its plasticity and making it more workable, improving its soaked strength, and increasing its permeability and the rate at which the soil gets consolidated. An optimal PS content of 50%, which provided the highest soaked strength, is recommended for the improvement of the subgrade characteristics of the BC soil for use as a pavement layer material.展开更多
文摘Smart grids and their technologies transform the traditional electric grids to assure safe,secure,cost-effective,and reliable power transmission.Non-linear phenomena in power systems,such as voltage collapse and oscillatory phenomena,can be investigated by chaos theory.Recently,renewable energy resources,such as wind turbines,and solar photovoltaic(PV)arrays,have been widely used for electric power generation.The design of the controller for the direct Current(DC)converter in a PV system is performed based on the linearized model at an appropriate operating point.However,these operating points are everchanging in a PV system,and the design of the controller is usually accomplished based on a low irradiance level.This study designs a fractional-order proportional-integrated-derivative(FOPID)controller using deep learning(DL)with quasi-oppositional Archimedes Optimization algorithm(FOPID-QOAOA)for cascaded DC-DC converters in micro-grid applications.The presented FOPIDQOAOA model is designed to enhance the overall efficiency of the cascaded DC-DC boost converter.In addition,the proposed model develops a FOPID controller using a stacked sparse autoencoder(SSAE)model to regulate the converter output voltage.To tune the hyper-parameters related to the SSAE model,the QOAOA is derived by the including of the quasi-oppositional based learning(QOBL)with traditional AOA.Moreover,an objective function with the including of the integral of time multiplied by squared error(ITSE)is considered in this study.For validating the efficiency of the FOPID-QOAOA method,a sequence of simulations was performed under distinct aspects.A comparative study on cascaded buck and boost converters is carried out to authenticate the effectiveness and performance of the designed techniques.
文摘The suitability of using precipitated silica(PS) from the burning of rice husk was investigated to improve the geotechnical engineering properties of a black cotton soil. A laboratory experimental program consisting of series of specific gravity, Atterberg limits, compaction, California bearing ratio(CBR), unconfined compression and consolidation tests was conducted on the untreated and PS treated soil samples. The application of PS to the soil significantly changed its properties by reducing its plasticity and making it more workable, improving its soaked strength, and increasing its permeability and the rate at which the soil gets consolidated. An optimal PS content of 50%, which provided the highest soaked strength, is recommended for the improvement of the subgrade characteristics of the BC soil for use as a pavement layer material.
