The Artificial Intelligence Technique for the Energy Generation and Administration of the Hybrid Solar/Wind/Diesel Power System

Ali, L. M. Abd; Ali, Qazi Azher; Кувшинов, В. В.; Bekirov, Eskender; Korovkin, Nikolay

doi:10.37279/2413-1873-2021-22-91-100

Cited by 3 publications

(4 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…5 изображена подсистема фотоэлектрического модуля. Функциональные блоки для (8) и содержатся в этом блоке подсистемы (9). Окончательная модель фотоэлектрической системы создается путем соединения этих функционирующих компонентов здания.…”

Section: построение и моделирование обобщенной фотоэлектрической моделиunclassified

Analysis of Photovoltaic Systems Through Simulation and Design Using MATLAB

Al-Maliki,

Abdali,

Issa

et al. 2023

Intellekt. Sist. Proizv.

View full text Add to dashboard Cite

During the operation of photovoltaic systems, a large amount of converted energy, according to various parameters, does not participate in the consumer power supply. As a result, the efficiency of solar installations and the reliability of electric power supply are reduced. This happens for various reasons, but primarily due to the imperfect operation of automatic control systems for photovoltaic installations. These systems are controlled by the information equipment of the entire installation based on software and control algorithms. The imperfection of these algorithms does not allow the full use of solar generation of photovoltaic panels and degrades the quality of operation of all the main and auxiliary equipment of the power generating complex. In the presented work, studies were carried out to improve the operation of the solar power supply system and increase its reliability. The proposed solutions were based on the use of new methods for tracking the maximum power point using high-tech algorithms to control the photovoltaic generating system. In this paper, a generalized Matlab-Simulink solar cell operation model was proposed. The basis of the proposed model is a simple mathematical equation to simulate the operation of a solar photovoltaic cell, since the output characteristics of photovoltaic modules are non-linear. The output I-V and P-V properties of a photovoltaic cell depend on the temperature of the cell and solar radiation. The physical characteristics of a particular solar photovoltaic cell can be modeled as a function of temperature and solar radiation. Numerous models use various software platforms that are available in the literature. This simulation model is very simple and easy to use. Simulation results in Matlab Simulink demonstrate the functionality and dynamic behavior of the provided solar module. Based on the study, it was found that the proposed algorithms can significantly improve the efficiency of photovoltaic installations, taking into account the use of new control methods. The power generated from solar energy converters was used more efficiently, and the photovoltaic system operated at a high conversion rate.

show abstract

Section: построение и моделирование обобщенной фотоэлектрической моделиunclassified

Analysis of Photovoltaic Systems Through Simulation and Design Using MATLAB

Al-Maliki,

Abdali,

Issa

et al. 2023

Intellekt. Sist. Proizv.

View full text Add to dashboard Cite

show abstract

“…или технологии топливных элементов. Одним из возможных источников энергии будущего является топливный элемент (ТЭ), известный как источник энергии с высокой удельной мощностью [2][3][4]. ТЭ являются экологически устойчивым источником, который очень подходит для использования в микросетях благодаря своей эффективности, надежности и высокой удельной мощности.…”

Section: Introductionunclassified

“…Солнечная энергия является одним из этих экологически чистых видов энергии. Есть два способа извлечь выгоду из солнечной энергии: либо с помощью метода сфокусированной солнечной энергии, основанной на тепловой энергии солнца, либо с помощью солнечных элементов, способных производить прямое преобразование для производства электроэнергии [13][14][15]. Солнечные батареи, в дополнение к другим источникам энергии, таким как ветряные турбины и дизельные двигатели, могут быть включены в микросеть рядом друг с другом.…”

Section: Introductionunclassified

Modeling and Management of Hybrid System Photovoltaic-FC-Ultracapacitors Power Systems

Issa,

Abdali,

Al-Maliki

et al. 2023

Intellekt. Sist. Proizv.

View full text Add to dashboard Cite

This study shows an improved DC microgrid power management technique. The value of utilizing renewable energy has long been debatable, and this article suggests a typical DC microgrid because of the advantages it has over AC technology. A solar cell (PV), fuel cell (FC) and storage component - an ultracapacitor (UC)-make up the standard microgrid. The most important goal of the paper is to optimize the management strategy for the bus voltage with arranged power-sharing between these types of renewable energy that are used here. For variable solar irradiance and various loading conditions, the proposed management seeks to deliver high-quality energy to the load while taking into consideration the FC state. The ultracapacitor was prepared to furnish the transient period due to the FC's slow dynamics. To maintain the DC bus voltage steady in the face of load variations, a management algorithm is put into practice. To generate the references, the management controller relies on a differential flatness method. The electricity from the ultracapacitor controls the DC bus. Earlier studies showed that the circuit of the fuel cell was integrated with a standalone photovoltaic system and discovered that the fuel cell doesn't have the same properties. In the current research, observations were made on power quality elements like voltage, current, and power for energy storage systems. With several self-definition elements of the photovoltaic, fuel cell, and ultracapacitor, along with their parameters, simulation is used as the study method medium. The outcome demonstrates that since the ultracapacitor serves as the primary storage, the fuel cell integration has little impact on it, and only small changes in voltage and current were observed. Due to the fuel cell integration characteristic of providing the system a major perturbation, most perturbation from the system had been absorbed while in an ultracapacitor

show abstract

“…Recognized as a cheap and sustainable option, renewables including solar and wind energy technologies provide clean energy options that contribute heavily to the reduction of ecological problems globally, particularly CO2 emission [1][2][3][4][5]. Solar as well as wind technologies are projected to be the major energy source by the year 2025, with solar energy production contributing 60% of the capacity additions [6,7].This projection is highly feasible provided that the reliability, accessibility, and performance issues are continuously monitored and resolved.…”

Section: Introductionmentioning

confidence: 99%

Solar Photovoltaic Modules’ Performance Reliability and Degradation Analysis—A Review

2022

View full text Add to dashboard Cite

The current geometric increase in the global deployment of solar photovoltaic (PV) modules, both at utility-scale and residential roof-top systems, is majorly attributed to its affordability, scalability, long-term warranty and, most importantly, the continuous reduction in the levelized cost of electricity (LCOE) of solar PV in numerous countries. In addition, PV deployment is expected to continue this growth trend as energy portfolio globally shifts towards cleaner energy technologies. However, irrespective of the PV module type/material and component technology, the modules are exposed to a wide range of environmental conditions during outdoor deployment. Oftentimes, these environmental conditions are extreme for the modules and subject them to harsh chemical, photo-chemical and thermo-mechanical stress. Asides from manufacturing defects, these conditions contribute immensely to PV module’s aging rate, defects and degradation. Therefore, in recent times, there has been various investigations into PV reliability and degradation mechanisms. These studies do not only provide insight on how PV module’s performance degrades over time, but more importantly, they serve as meaningful input information for future developments in PV technologies, as well as performance prediction for better financial modelling. In view of this, prompt and efficient detection and classification of degradation modes and mechanisms due to manufacturing imperfections and field conditions are of great importance towards minimizing potential failure and associated risks. In the literature, several methods, ranging from visual inspection, electrical parameter measurements (EPM), imaging methods, and most recently data-driven techniques have been proposed and utilized to measure or characterize PV module degradation signatures and mechanisms/pathways. In this paper, we present a critical review of recent studies whereby solar PV systems performance reliability and degradation were analyzed. The aim is to make cogent contributions to the state-of-the-art, identify various critical issues and propose thoughtful ideas for future studies particularly in the area of data-driven analytics. In contrast with statistical and visual inspection approaches that tend to be time consuming and require huge human expertise, data-driven analytic methods including machine learning (ML) and deep learning (DL) models have impressive computational capacities to process voluminous data, with vast features, with reduced computation time. Thus, they can be deployed for assessing module performance in laboratories, manufacturing, and field deployments. With the huge size of PV modules’ installations especially in utility scale systems, coupled with the voluminous datasets generated in terms of EPM and imaging data features, ML and DL can learn irregular patterns and make conclusions in the prediction, diagnosis and classification of PV degradation signatures, with reduced computation time. Analysis and comparison of different models proposed for solar PV degradation are critically reviewed, in terms of the methodologies, characterization techniques, datasets, feature extraction mechanisms, accelerated testing procedures and classification procedures. Finally, we briefly highlight research gaps and summarize some recommendations for the future studies.

show abstract

The Artificial Intelligence Technique for the Energy Generation and Administration of the Hybrid Solar/Wind/Diesel Power System

Cited by 3 publications

References 1 publication

Analysis of Photovoltaic Systems Through Simulation and Design Using MATLAB

Analysis of Photovoltaic Systems Through Simulation and Design Using MATLAB

Modeling and Management of Hybrid System Photovoltaic-FC-Ultracapacitors Power Systems

Solar Photovoltaic Modules’ Performance Reliability and Degradation Analysis—A Review

Contact Info

Product

Resources

About