Algorithm for Multivariate Solution of Mathematical Models in MATLAB to Create a Database of Environmental Parameters

Komilov, A.

doi:10.3103/s0003701x20010077

Cited by 5 publications

(2 citation statements)

References 30 publications

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“…The variables are set to the following ranges: τ (sunrise:sunset), n (1:365), β (0:180), γ (− 180:180) and ρ (0:1). The details of the model are given in a previous work in the literature 31 …”

Section: Methodsmentioning

confidence: 99%

“…The details of the model are given in a previous work in the literature. 31 The core of the model is based on the mathematical model for calculating hourly direct, diffuse, and reflected solar radiation for clear sky conditions described by Duffie and Beckman. 32 Calculation of diffuse radiation uses the Liu-Jordan isotropic model, which was found to be the most accurate by Mousavi Maleki et al 33 The values of local clearness index (K T ) are applied to the calculated clear sky insolation data (I CS ).…”

Section: Pv Orientation-based Power Outputmentioning

confidence: 99%

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Location and orientation based LCOE: Simplified visual analysis and generalization of the levelized cost of electricity from storageless photovoltaic systems

Komilov

2020

Intl J of Energy Research

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This article describes a multidimensional visualization approach to the analysis of the levelized cost of energy (LCOE), which shows that the influence of a single parameter deviates with respect to different values of other parameters. It also demonstrates that the proportionality of the LCOE to the photovoltaic power output makes the same data set suitable for analyzing the dependence of LCOE on the location and orientation of the PV system (PVS). Conversion of the Photovoltaic Electricity Potential map into the LCOE-map is demonstrated in the example of Uzbekistan. A method is presented, which simply converts the PV orientation-dependent photovoltaic power output data into the PV orientation-dependent LCOE data. The universal approach to calculate degrees of freedom for the azimuthal angle and inclination angle of the PV is demonstrated in the example of the LCOE minima fluctuations of 2%. The demonstrated methods can help decision making by initially assessing the potential for installing a PV system in various locations and reducing the balance of system (BOS) by integrating the system into a building, taking into account the orientation of the integrated surface, and its impact on electricity costs.

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Section: Methodsmentioning

confidence: 99%

Section: Pv Orientation-based Power Outputmentioning

confidence: 99%

Location and orientation based LCOE: Simplified visual analysis and generalization of the levelized cost of electricity from storageless photovoltaic systems

Komilov

2020

Intl J of Energy Research

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Intelligent prediction method for power generation based on deep learning and cloud computing in big data networks

Zhou

2023

International Journal of Intelligent Networks

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Mass data processing and multidimensional database management based on deep learning

Shen

Tian

et al. 2022

Open Computer Science

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With the rapid development of the Internet of Things, the requirements for massive data processing technology are getting higher and higher. Traditional computer data processing capabilities can no longer deliver fast, simple, and efficient data analysis and processing for today’s massive data processing due to the real-time, massive, polymorphic, and heterogeneous characteristics of Internet of Things data. Mass heterogeneous data of different types of subsystems in the Internet of Things need to be processed and stored uniformly, so the mass data processing method is required to be able to integrate multiple different networks, multiple data sources, and heterogeneous mass data and be able to perform processing on these data. Therefore, this article proposes massive data processing and multidimensional database management based on deep learning to meet the needs of contemporary society for massive data processing. This article has deeply studied the basic technical methods of massive data processing, including MapReduce technology, parallel data technology, database technology based on distributed memory databases, and distributed real-time database technology based on cloud computing technology, and constructed a massive data fusion algorithm based on deep learning. The model and the multidimensional online analytical processing model of the multidimensional database based on deep learning analyze the performance, scalability, load balancing, data query, and other aspects of the multidimensional database based on deep learning. It is concluded that the accuracy of multidimensional database query data is as high as 100%, and the accuracy of the average data query time is only 0.0053 s, which is much lower than the general database query time.

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Algorithm for Multivariate Solution of Mathematical Models in MATLAB to Create a Database of Environmental Parameters

Cited by 5 publications

References 30 publications

Location and orientation based LCOE: Simplified visual analysis and generalization of the levelized cost of electricity from storageless photovoltaic systems

Location and orientation based LCOE: Simplified visual analysis and generalization of the levelized cost of electricity from storageless photovoltaic systems

Intelligent prediction method for power generation based on deep learning and cloud computing in big data networks

Mass data processing and multidimensional database management based on deep learning

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