The uncertainty associated with modelling and performance of solar photovoltaic systems could be easily and efficiently solved by using Maximum power point techniques. During the past decade of 2010 to 2021, the classification of techniques based on intelligent, non- intelligent and their hybrid models are found as potential techniques for detecting the maximum power point of a photovoltaic system. In addition, for this decade there is no extensive and comprehensive review on applicability of intelligent, non-intelligent and their hybrid models for performance prediction and modelling of solar photovoltaic systems. Therefore, this article focuses on extensive review on design, modelling, maximum power point tracking, advantages, disadvantages of each technique, evolutionary trend, convergence and tracking speed, and output efficiency prediction of solar photovoltaic systems under partial shading conditions and non-partial shading conditions using intelligent, non-intelligent and their hybrid techniques. Furthermore, a total of 77 selected articles on the solar PV tracking technique and their hybrid models together with the PV technology were reviewed. Total of 22 articles are reviewed and summarized in this review paper for the period of 2010 to 2021 with 12 articles in non- intelligent technique, 7 articles in intelligent technique and 3 articles in their hybrid form. The review showed the suitability and reliability of intelligent, non-intelligent and their hybrid models for accurate detection of maximum power point and the performance characteristics of solar photovoltaic systems. Finally, this review presents the guidance for the researchers and engineers in the field of solar photovoltaic systems to select the suitable techniques for enhancement of the performance characteristics of the solar photovoltaic systems and the utilization of the available solar radiation.
Seminar report on Flexible Photovoltaic TechnologyKumudGarg3
This report is relate to topic of Flexible Solar Cell. In this report you get content is introduction, introduction to flexible solar cell, types of solar cell, types of flexible solar cell, application n etc.
Advance Solar Cells and Printed Solar Cell A Reviewijtsrd
Solar cell technology begin with first generation and third generation solar cells is discussed here by considering different advanced materials on which these technologies are based. The efficiencies attained with different new age solar cell technologies, limitations in their commercial application is overcome with the new technology used in solar cell. This paper is an overview of the advances technology used in solar cell and printed solar cell. Sukhjinder Singh | Nitish Palial | Rohit Kumar "Advance Solar Cells and Printed Solar Cell: A Review" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-5 , October 2023, URL: https://www.ijtsrd.com/papers/ijtsrd59981.pdf Paper Url: https://www.ijtsrd.com/engineering/electrical-engineering/59981/advance-solar-cells-and-printed-solar-cell-a-review/sukhjinder-singh
This presentation covers following points:-
1. Introduction
2. Introduction to Flexible Solar Cell
3. Flexible Photovoltaic Technology
4. Different types of Flexible Solar Cell
5. Manufacturing Process
6. Testing Method
7. Advantages
8. Applications
9. Conclusion
10. Future Scope
Seminar report on Flexible Photovoltaic TechnologyKumudGarg3
This report is relate to topic of Flexible Solar Cell. In this report you get content is introduction, introduction to flexible solar cell, types of solar cell, types of flexible solar cell, application n etc.
Advance Solar Cells and Printed Solar Cell A Reviewijtsrd
Solar cell technology begin with first generation and third generation solar cells is discussed here by considering different advanced materials on which these technologies are based. The efficiencies attained with different new age solar cell technologies, limitations in their commercial application is overcome with the new technology used in solar cell. This paper is an overview of the advances technology used in solar cell and printed solar cell. Sukhjinder Singh | Nitish Palial | Rohit Kumar "Advance Solar Cells and Printed Solar Cell: A Review" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-5 , October 2023, URL: https://www.ijtsrd.com/papers/ijtsrd59981.pdf Paper Url: https://www.ijtsrd.com/engineering/electrical-engineering/59981/advance-solar-cells-and-printed-solar-cell-a-review/sukhjinder-singh
This presentation covers following points:-
1. Introduction
2. Introduction to Flexible Solar Cell
3. Flexible Photovoltaic Technology
4. Different types of Flexible Solar Cell
5. Manufacturing Process
6. Testing Method
7. Advantages
8. Applications
9. Conclusion
10. Future Scope
Optimization of multijunction solar cell by wafer ray tracer for development ...eSAT Journals
Abstract Optical losses limit the excess carriers generation in absorber part of multijuction (MJ) solar cell. The generation of excess carriers is directly proportional to photogenerated current solar cell. Therefore, reduction of optical losses is fundamentally important for improving the power conversion efficiency. Thickness of layers strongly influences the performance of MJ solar cell. In this study we simulated a MJ solar cell of Air/ZnO/SiC/c-Si/a-Si(n)/Al structure using Wafer Ray Tracer (WRT) simulation software and optimized the thicknesses of the layers for photogenerated current. The simulation result shows that without SiC layer, only 57.48% of incident light is absorbed and generates 26.85 mA/cm2 photogenerated current in solar cell. A 70 nm thickness of optimized SiC layer is increasing the light absorption 22.16% and photogenerated current 38.54%. Result shows that there is no transmission of light through the absorber layer. The MJ solar cell without Back Surface Field (BSF) layer of a-Si(n) shows photogenerated current of 37.05 mA/cm2 which can be improved to 37.24 mA/cm2 with a 100 nm thickness of a-Si(n). The c-Si absorber layer shows highest absorptance within 500 nm-1000 nm wavelength of light spectrum with 100 nm thickness of a-Si(n). An a-Si(n) BSF layer at the back surface minimizes the effective back-surface recombination velocity and improves the collection probability of minority carriers of solar cell. Furthermore a 100 nm Al rear contact improves the photogenerated current of MJ solar cell to 37.25 mA/cm2. An Al rear contact layer improves the mechanical strength of c-Si absorber layer. The electrical property of Al improves the excess carriers’ collection probability of MJ solar cell. Keywords: Wafer Ray Tracer, Simulation, Multijunction Solar Cell, Photogeneration, Back Surface Field.
Advancements in Photovoltaic Materials for Sustainable Energy GenerationChristo Ananth
Christo Ananth, Rajini K R Karduri, "Advancements in Photovoltaic Materials for Sustainable Energy Generation", International Journal of Advanced Research in Basic Engineering Sciences and Technology (IJARBEST), Volume 7,Issue 1,January 2021,pp 28-38
Academic Journal Writing and Types of Journals.pdfssuser793b4e
Academic journal writing serves as the lifeblood of scholarly communication, fostering the
dissemination of knowledge and innovation within various academic disciplines. This
seminar paper provides a comprehensive exploration of the significance of academic journal
writing and an in-depth analysis of the diverse types of scholarly journals available. The
paper delves into the fundamental structure and components of academic journal articles,
emphasizing their pivotal role in presenting original research, conducting literature reviews,
and fostering academic discourse. Additionally, it outlines the distinct characteristics of
various types of journals, including research journals, review journals, scholarly versus trade
journals, open access journals, and interdisciplinary journals. Furthermore, the seminar
paper offers crucial insights into the selection criteria for appropriate journals, highlighting
considerations such as scope, audience, impact factor, and adherence to submission
guidelines. Understanding these factors aids researchers, scholars, and academics in
effectively navigating the complex landscape of academic publishing, ensuring the
successful dissemination of their work within their respective fields. This seminar paper
serves as a valuable guide for individuals involved in academic research, offering a
comprehensive understanding of academic journal writing and equipping them with the
knowledge necessary to navigate the scholarly publishing landscape effectively. This
abstract encapsulates the key points and objectives covered in the seminar paper on
academic journal writing and types of journals, providing a concise overview of its contents
and significance within the academic community
The Differences between Single Diode Model and Double Diode Models of a Solar...ssuser793b4e
This research paper systematically reviewed and investigated single
diode model and double diode model of a solar photovoltaic systems in terms
of accuracy, differences under major unknown PV parameters, different
optimization and fabrication. This research paper reviewed the differences and
the similarities between the single diode model and double diode model. From
the review, it was clear that single diode model has less computation time and
number of unknown parameters compared to double diode model. The double
diode model on its own superiority is more accurate under solar shading
condition effect than single diode model but single diode model performs
better under high insolation levels. None of the two models is superior than
the other but the solar photovoltaic modelers/installers should bear the solar
irradiance of the environment before installation
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Optimization of multijunction solar cell by wafer ray tracer for development ...eSAT Journals
Abstract Optical losses limit the excess carriers generation in absorber part of multijuction (MJ) solar cell. The generation of excess carriers is directly proportional to photogenerated current solar cell. Therefore, reduction of optical losses is fundamentally important for improving the power conversion efficiency. Thickness of layers strongly influences the performance of MJ solar cell. In this study we simulated a MJ solar cell of Air/ZnO/SiC/c-Si/a-Si(n)/Al structure using Wafer Ray Tracer (WRT) simulation software and optimized the thicknesses of the layers for photogenerated current. The simulation result shows that without SiC layer, only 57.48% of incident light is absorbed and generates 26.85 mA/cm2 photogenerated current in solar cell. A 70 nm thickness of optimized SiC layer is increasing the light absorption 22.16% and photogenerated current 38.54%. Result shows that there is no transmission of light through the absorber layer. The MJ solar cell without Back Surface Field (BSF) layer of a-Si(n) shows photogenerated current of 37.05 mA/cm2 which can be improved to 37.24 mA/cm2 with a 100 nm thickness of a-Si(n). The c-Si absorber layer shows highest absorptance within 500 nm-1000 nm wavelength of light spectrum with 100 nm thickness of a-Si(n). An a-Si(n) BSF layer at the back surface minimizes the effective back-surface recombination velocity and improves the collection probability of minority carriers of solar cell. Furthermore a 100 nm Al rear contact improves the photogenerated current of MJ solar cell to 37.25 mA/cm2. An Al rear contact layer improves the mechanical strength of c-Si absorber layer. The electrical property of Al improves the excess carriers’ collection probability of MJ solar cell. Keywords: Wafer Ray Tracer, Simulation, Multijunction Solar Cell, Photogeneration, Back Surface Field.
Advancements in Photovoltaic Materials for Sustainable Energy GenerationChristo Ananth
Christo Ananth, Rajini K R Karduri, "Advancements in Photovoltaic Materials for Sustainable Energy Generation", International Journal of Advanced Research in Basic Engineering Sciences and Technology (IJARBEST), Volume 7,Issue 1,January 2021,pp 28-38
Academic Journal Writing and Types of Journals.pdfssuser793b4e
Academic journal writing serves as the lifeblood of scholarly communication, fostering the
dissemination of knowledge and innovation within various academic disciplines. This
seminar paper provides a comprehensive exploration of the significance of academic journal
writing and an in-depth analysis of the diverse types of scholarly journals available. The
paper delves into the fundamental structure and components of academic journal articles,
emphasizing their pivotal role in presenting original research, conducting literature reviews,
and fostering academic discourse. Additionally, it outlines the distinct characteristics of
various types of journals, including research journals, review journals, scholarly versus trade
journals, open access journals, and interdisciplinary journals. Furthermore, the seminar
paper offers crucial insights into the selection criteria for appropriate journals, highlighting
considerations such as scope, audience, impact factor, and adherence to submission
guidelines. Understanding these factors aids researchers, scholars, and academics in
effectively navigating the complex landscape of academic publishing, ensuring the
successful dissemination of their work within their respective fields. This seminar paper
serves as a valuable guide for individuals involved in academic research, offering a
comprehensive understanding of academic journal writing and equipping them with the
knowledge necessary to navigate the scholarly publishing landscape effectively. This
abstract encapsulates the key points and objectives covered in the seminar paper on
academic journal writing and types of journals, providing a concise overview of its contents
and significance within the academic community
The Differences between Single Diode Model and Double Diode Models of a Solar...ssuser793b4e
This research paper systematically reviewed and investigated single
diode model and double diode model of a solar photovoltaic systems in terms
of accuracy, differences under major unknown PV parameters, different
optimization and fabrication. This research paper reviewed the differences and
the similarities between the single diode model and double diode model. From
the review, it was clear that single diode model has less computation time and
number of unknown parameters compared to double diode model. The double
diode model on its own superiority is more accurate under solar shading
condition effect than single diode model but single diode model performs
better under high insolation levels. None of the two models is superior than
the other but the solar photovoltaic modelers/installers should bear the solar
irradiance of the environment before installation
Redefining Academic Performance Metrics Evaluating the Excellence of Research...ssuser793b4e
The Redefining Academic Performance Metrics: Evaluating the Excellence of Researchers, Academics, and Scholars
explores the evolving landscape of academia, focusing on the shift from traditional metrics like publication and
citation counts to a more inclusive, open, and equitable approach. The study acknowledges the limitations of
traditional metrics and celebrates pioneers in shaping the future of scholarly endeavors, highlighting the importance
of inclusivity, openness, and equitable evaluations in assessing academic excellence.
Qualities and Characteristics of a Good Scientific Research.pdfssuser793b4e
Many young researchers find it difficult to write a good and quality research thesis/article
because they are not prone to article writing ethics and training. Yet, a thesis/publication is
often vital and paramount for career advancement, grants, academic qualifications and
others. This research work described the basics and systematic steps to follow in writing a
good scientific thesis/article. This research also outlined the main sections that an average
thesis/article should contain, the elements that should appear in each section, the systematic
approaches in writing research, the characteristics of a good thesis/article, the attributes of
a good research thesis/article, qualities of a good researcher and finally the ethics guiding
research
Maximizing Journal Article Impact Strategies for Enhanced Visibility in Today...ssuser793b4e
In the dynamic realm of academia, researchers face the dual challenge of generating
groundbreaking insights and ensuring widespread visibility for their contributions. This
article explores the evolving strategies employed by researchers to enhance the visibility of
their journal articles in the changing landscape of academic technology. Online publishing
platforms have transformed scholarly communication, democratizing knowledge through
open-access journals, preprint servers, and institutional repositories. Beyond traditional
metrics, we delve into innovative methods, collaboration, and technology-driven solutions
that amplify the reach and impact of scholarly articles. Visibility extends beyond
dissemination, encapsulating the art of captivating diverse audiences and transcending
disciplinary boundaries. This research article illuminates the path towards heightened
visibility, empowering researchers to contribute to the collective tapestry of knowledge
through means such as Academia.edu, ISSUU, Scribd, ResearchGate, social media, Search
Engine Optimization (SEO), and ORCID. Enhanced visibility offers multifaceted advantages,
including increased citations, higher impact factors, knowledge dissemination, international
collaboration, career advancement, public engagement, and job opportunities within the
scholarly community. Researchers are equipped with the insights needed to thrive in the
evolving landscape of journal article visibility in the digital cosmos.
Impact of Urban Planning on Household Poverty Reduction in Uganda A Review.pdfssuser793b4e
The study analyzed the impact of urban planning on reducing household poverty in
Uganda. It found that both negative and positive factors significantly influence household
poverty. The study also identified five key factors that contribute to household poverty:
social services, research and development, employment, and investment. The findings
suggest that urban planners should align their policies with government policies when
allocating resources to reduce poverty caused by unplanned urbanization. The study
recommends that urban planners work to improve the quality of life for households in
Uganda
Government Interventions and Household Poverty in Uganda A Comprehensive Revi...ssuser793b4e
This comprehensive review explores the multifaceted impact of government interventions
on household poverty in Uganda, a nation grappling with socio-economic challenges.
Through an in-depth analysis of diverse policies and programs implemented by the
Ugandan government, this study examines their efficacy in alleviating poverty and
enhancing the overall well-being of households. Drawing upon a wide array of scholarly
articles, policy documents, and empirical studies, the research assesses the effectiveness
of interventions such as social welfare programs, economic programs, pro-poor programs
and educational reforms. The review delves into the intricate interplay between these
government interventions and household poverty dynamics, considering factors like
income disparity, access to education, healthcare services, and employment opportunities.
By synthesizing existing literature, this study elucidates the successes and shortcomings of
various strategies, shedding light on the key determinants of their effectiveness.
Additionally, it analyzes the role of governance, accountability mechanisms, and resource
allocation in shaping the outcomes of poverty-alleviation initiatives. Hence, this review
critically examines the challenges faced by marginalized households in accessing and
benefiting from government interventions, highlighting areas that require targeted policy
reforms and targeted interventions. By identifying gaps in existing research and policy
frameworks, this study provides valuable insights for policymakers, researchers, and
development practitioners, aiming to inform evidence-based decision-making processes.
Ultimately, this review contributes to the ongoing discourse on poverty reduction
strategies in Uganda and offers recommendations for enhancing the impact of government
interventions on vulnerable households, thereby fostering sustainable socio-economic
development in the region.
The Effect of Financial Management on the Learning Ability of Students in.pdfssuser793b4e
This review explores the crucial nexus between financial
management and the learning environment within government-aided primary
schools in Ibanda Municipality, Uganda. Education in developing nations
heavily depends on the efficient allocation and utilization of funds, directly
impacting the quality of education and overall learning experience for
students. Drawing upon a comprehensive analysis of selected schools in
Ibanda Municipality, this review investigates the diverse financial
management strategies employed and their subsequent influence on essential
educational components, including infrastructure, teaching resources, and
student welfare. This review research revealed that there is a direct correlation
between effective financial management and the overall enhancement of the
learning environment. Schools with robust financial planning mechanisms
demonstrate improved infrastructure, better teacher-student ratios, and
enhanced availability of educational resources whereas those schools facing
financial constraints struggle to survive financially which affects the quality
of education. Moreover, this review sheds light on the challenges faced by
schools in resource allocation and highlights potential solutions to enhance
financial sustainability. It emphasizes the need for strategic financial
planning, transparent budgeting, and community involvement to ensure the
effective utilization of limited resources.
Quantification of Earth Material for Sustainable Road Works in Southeast Nige...ssuser793b4e
This paper examines the use of earth materials in sustainable road
construction in South East, Nigeria. The study aims to determine factors
associated with the use of earth materials, identify limiting factors, and
examine strategies to improve their use. The study population comprised 60
engineers and craftsmen using local materials. The results show limitations in
the use of earth materials in sustainable road works. The study recommends
contracting firms to develop better storage facilities for earth materials to
prevent damage and wastage. It also suggests incorporating earth materials
into construction education curriculums to sensitize students to their potential
benefits. The government should adopt a policy of adapting earth materials
that require minimal capital and foreign exchange and utilizing available raw
materials and skills in small-scale operations. The study's findings highlight
the importance of sustainable road construction in Nigeria's socio-economic
growth.
Navigating Challenges and Maximizing Benefits in the Integration of Informati...ssuser793b4e
The integration of Information and Communication Technology
(ICT) in the educational systems of both public and private primary schools in
Africa has become a crucial factor in enhancing teaching and learning. This
paper explores the role of ICT tools in education, including computers,
interactive whiteboards, learning management systems, educational apps,
online collaboration tools, television, and online assessment tools. It discusses
their applications and the advantages they offer, such as fostering creativity,
improving academic performance, increasing motivation and responsibility,
and promoting teamwork. However, it also acknowledges the challenges
associated with ICT integration, including distractions, excessive usage,
exposure to false information, data theft, reduced human contact, and
cyberbullying. Moreover, the paper highlights key challenges in African
education, such as the lack of computer literacy among instructors, low
teledensity, unstable power supply, inadequate financing, and the absence of a
comprehensive ICT curriculum. It concludes by emphasizing the need for a
holistic approach to ICT integration, addressing infrastructure, teacher
training, curriculum development, and organizational support to realize the
full potential of ICT in education especially at the Primary school level.
Mobile Disinfectant Spraying Robot and its Implementation Components for Viru...ssuser793b4e
The virus pandemic COVID-19 outbreak brought a huge pressure
to the public healthcare system worldwide, especially in developing African
countries like Uganda. The Educational system and institutions were put on a
standstill due to no quick countermeasures to make the environment clean and
safe for normal activities to continue. This paper successfully and
comprehensively reviewed the Bluetooth and smart disinfectant spraying
robot that successfully controlled the spread of the deadly virus. It also
detailed different components that made up the complete spraying robot
systems and from this it was observed that spraying robot systems are made
up of almost the same components for implementations but differs on
program that is embedded on the microcontroller due to different functions.
This programing differs based on the functions that the designer/programmer
wants the robot to do despite using almost the same components. This
research review paper will act as guide for future researchers when designing
and implementing a mobile spraying robot.
Assessing Energy Policies, Legislation and Socio-Economic Impacts in the Ques...ssuser793b4e
The energy sector in Africa, particularly in countries like Uganda,
plays a pivotal role in shaping economic development, social progress, and
environmental sustainability. This study delves into the nuanced interplay
between energy policies, legislation, and their real-world consequences in
Uganda. By employing a case study approach, this research investigates the
multifaceted impact of Uganda's energy policies and legislation on various
stakeholders, including government institutions, businesses, and local
communities. This study provides an overview of Uganda's energy landscape,
highlighting the challenges faced by the nation in ensuring a stable and
sustainable energy supply. It then meticulously examines the evolution of
energy policies and legislation over the past few decades, analysing their
formulation, implementation, and effectiveness. Through qualitative and
quantitative analyses, this research assesses the socio-economic consequences
of these policies and legislations. It explores how regulatory decisions have
influenced energy accessibility, affordability, and reliability for urban and
rural populations. Additionally, the environmental impact of energy policies
is scrutinized, focusing on their contributions to climate change mitigation,
natural resource conservation, and the promotion of sustainable practices. The
study also evaluates the social repercussions, including the empowerment of
local communities, employment generation, and overall improvements in the
quality of life resulting from energy policy interventions. This research
critically examines the challenges faced during policy implementation, such
as bureaucratic hurdles, financial constraints, and political influences, which
often hinder the desired outcomes. It identifies key lessons from Uganda's
experiences, offering valuable insights for other African nations grappling
with similar energy challenges.
A Review of Cross-Platform Document File Reader Using Speech Synthesis.pdfssuser793b4e
Document files are files used to store documents on storage
devices primarily for computer use. Software is used to view these files,
displaying their text content in a legible way. However, it is essential to have
programs for transforming electronic files into versions usable by those who
suffer from specific disabilities. This paper reviewed fifteen published articles
in the field of document file reading. It was observed from the review that
various attempts have been made by different researchers in order to develop
a software cable for converting document files that consist of text to an audio
format. Text may now be easily translated into natural-sounding voice across
many platforms using different software. It was observed from the systematic
review that the use of AI such as the GPT-3.5 and GPT-4 Turbo Large
Language Model (LLM) technologies has the best performance because it
does not end at producing a vocal sound that is similar to human own, but it
also translates different languages. In conclusion, cross-platform document
file reader (text-to-speech) synthesis has improved user experiences in a
variety of applications such as language learning, audiobooks and virtual
assistants.
A Critical Assessment of Data Loggers for Farm Monitoring Addressing Limitati...ssuser793b4e
This comprehensive review examines thirty-nine data loggers and
their associated literature, systematically critiquing their design and
implementation. The integration of data loggers in farm monitoring proves
cost-effective, enabling the simultaneous monitoring of multiple parameters
without human intervention. The accrued data, when logged over time,
contributes to more accurate weather predictions, empowering farmers to
strategically plan for upcoming seasons. However, the review reveals a
prevalent issue among existing data loggers: many cannot read and record
various weather parameters concurrently, coupled with insufficient storage
capacity. This limitation hinders their suitability for prolonged, unattended
data storage. Additionally, a significant number of the reviewed data loggers
lack long-range wireless data transmission capabilities, restricting effective
weather monitoring from a distance. The findings underscore the need for
researchers to focus on developing advanced long-range data logger systems
with enhanced memory storage capacities to address these identified
shortcomings.
A Comparative Analysis of Renewable Energy Policies and its Impact on Economi...ssuser793b4e
Renewable energy has been identified as a critical component of
global efforts to address climate change, enhance energy security, and foster
sustainable economic growth. As a result, many countries have implemented
renewable energy policies to promote the development and deployment of
renewable energy technologies. However, the impact of these policies on
economic growth remains a subject of debate. This article provides a
comparative analysis of renewable energy policies and their impact on
economic growth. The study employs a systematic review of the literature and
utilizes qualitative and quantitative methods to compare renewable energy
policies and their economic impacts across different countries. The findings
suggest that the impact of renewable energy policies on economic growth
varies across countries and is influenced by factors such as policy design,
institutional context, and economic structure. This research article finally,
examined the challenges associated with implementing renewable energy
policies, analyzed the implications of the findings for policymakers and
further gave some potential solutions that will help the policymakers and
future researchers
The study investigated principals’ administrative strategies as correlates of teachers’ job
performance in public secondary schools in Obollo-Afor Education Zone of Enugu State. Four
research questions and four null hypotheses guided the study. The study adopted a
correlational survey design. The population of the study was 1,854 principals and teachers in
48 secondary schools in the Zone. A sample of 605 teachers was drawn using proportionate
stratified random sampling technique. Questionnaire was used as the instrument for data
collection and was subjected to face-validation by three experts. The internal consistency of
the instrument was obtained using Cronbach Alpha, which yielded an index of 0.72. Data
collected were analyzed using regression analysis while regression ANOVA was used in testing
the formulated hypotheses at 0.05 level of significance. The result of the study revealed that,
open communication, carrying teachers’ along and providing for teachers’ welfare among
others are principals’ administrative strategies for enhancing teachers’ job performance in
secondary schools. The result also, revealed a high positive significant relationship existing
between principals’ administrative strategies in decision making, delegation of duties, open
communication and management of staff welfare and teachers’ job performance in secondary
schools. The study recommended among others that principals in public secondary schools
should adopt positive administrative strategies as identified in this study to promote
teachers’ job performance.
A Systematic Review of Renewable Energy Trend.pdfssuser793b4e
This paper systematically and successfully reviewed the renewable energy trend from 2010 to 2023. This review
detailed the difference renewable energy and conclusion was drawn that solar photovoltaic (PV) energy has the
leading trend in power generation growth and innovation. This research work explained in detail the most recent
solar photovoltaic optimization techniques and it was observed from the review that hybridization of intelligent and
non-intelligent maximum power point tracking technique has the best tracking power conversion efficiency. The
advantages and disadvantage of solar PV together with the solar optimization and innovational growth trends were
examined. This research showed that clean and renewable energy sources will continue to grow and the solar energy
industry is expected to experience significant growth and rapid innovation in the next 10 years. From the observed
rapid growth and innovation trend in solar energy, the world will have a very cheap, abundant and clean energy
before 2050.
Automated Hybrid Smart Door Control System.pdfssuser793b4e
This research paper successfully designed, developed and implemented an automated hybrid smart door control system which has the ability to secure a home up to 92% electronically. This smart door system is designed and implemented by building a hardware made up of the Bluetooth module and fingerprint scanner which are interfaced with the Microcontroller system that uses +5V power supply. The written programs were interfaced into the microcontroller chips by plugging the Arduino USB cable into the laptop and upload the codes. The microcontroller chips helped in enrolling the users fingerprint into the fingerprint scanner and it automatically administers and saves the users fingerprint after enrollment. Furthermore, after all the processes the user places the enrolled or registered finger into the fingerprint scanner which either accepts or denies the user by triggering the solenoid lock to either unlock, lock or deny access. This process of unlocking and locking requires using Bluetooth and fingerprint to either lock or unlock the door smartly without stress and it can be done within one second that is why the Solenoid lock is used in building this security system. This automated hybrid smart door control system developed has curbed the problem of door breaking theft for about 92%, strengthened security and as well made it so easy for the physically challenged people to have access to their homes without third party assistance.
Design and Implementation of a Smart Surveillance Security System.pdfssuser793b4e
Home security is essential for occupant’s conveniences and protection. This research project designed and implemented a comparatively inexpensive smart surveillance security system that automatically captures an intruder’s image through a raspberry pi camera module and PIR sensor and sends mail to the user via Wi-Fi using the users registered email address. This system operates by triggering the Pi Camera through Raspberry Pi whenever an intruder comes in range using PIR sensor. The Pi camera will capture the image, save it and send the image of the intruder via mail to the user through the help of the command codes embedded in the Raspberry pi microcontroller. This research project will enable home/supermarket and office owners to secure their facilities and monitor the activities of their employers at any location at cheaper cost which is the earnest desire of an Engineer. Proteus 2022 was used as the simulation tool.
Review of the Implications of Uploading Unverified Dataset in A Data Banking ...ssuser793b4e
This review paper comprehensively detailed the methodologies involved in data analysis and theevaluation steps. It showed that steps and phases are the two main methodological parameters to be considered during data assessment for data of high qualities to be obtained.It is reviewed from this research that poor data quality is always caused by incompleteness, inconsistency, integrity and time-related dimensions and the four major factors that causes error in a dataset are duplication, commutative entries, incorrect values and black entries which always leads to catastrophe. This paper also reviewed the types of datasets, adopted techniques to ensure good data quality, types of data measurement and its classifications.Furthermore, the Kaggle site was used as a case study to show the trend of data growth and its consequences to the world and the data bankers. It is then deduced that low data quality which is caused as a result of errors during primary data mining and entries leads to wrong results which bring about the wrong conclusions. It was advised that critical data quality measures should be adopted by the data bankers such as Kaggle before uploading the data into their site to avoid catastrophe and harm to humans.Finally, the outlined solutions as reviewed in this paper will serve as a guide to data bankers and miners to obtain data of high quality, fit for use and devoid of a defect.
Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
For more technical information, visit our website https://intellaparts.com
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CW RADAR, FMCW RADAR, FMCW ALTIMETER, AND THEIR PARAMETERSveerababupersonal22
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Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
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When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
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using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
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Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
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A Comprehensive Review on Recent MPPT of a Solar PV Systems using Intelligent, Non-Intelligent &Hybrid based Tech.pdf
1. Volume 6, Issue 5, May – 2021 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
IJISRT21MAY271 www.ijisrt.com 456
A Comprehensive Review on Recent Maximum
Power Point Tracking of a Solar Photovoltaic
Systems using Intelligent, Non-Intelligent and
Hybrid based Techniques
Val Hyginus Udoka EZE1
Department of Electronic Engineering,
University of Nigeria, Nsukka, Enugu State, Nigeria.
Samuel Anezichukwu UGWU3
Department of Electronic Engineering,
University of Nigeria, Nsukka, Enugu State, Nigeria
Ogbonna Ukachukwu OPARAKU2
Department of Electronic Engineering,
University of Nigeria, Nsukka, Enugu State, Nigeria,
Chibuzo Chidubem OGBONNA4
Department of Electronic Engineering,
University of Nigeria, Nsukka, Enugu State, Nigeria
Abstract:- The uncertainty associated with modelling
and performance of solar photovoltaic systems could be
easily and efficiently solved by using Maximum power
point techniques. During the past decade of 2010 to 2021,
the classification of techniques based on intelligent, non-
intelligent and their hybrid models are found as potential
techniques for detecting the maximum power point of a
photovoltaic system. In addition, for this decade there is
no extensive and comprehensive review on applicability
of intelligent, non-intelligent and their hybrid models for
performance prediction and modelling of solar
photovoltaic systems. Therefore, this article focuses on
extensive review on design, modelling, maximum power
point tracking, advantages, disadvantages of each
technique, evolutionary trend, convergence and tracking
speed, and output efficiency prediction of solar
photovoltaic systems under partial shading conditions
and non-partial shading conditions using intelligent,
non-intelligent and their hybrid techniques.
Furthermore, a total of 77 selected articles on the solar
PV tracking technique and their hybrid models together
with the PV technology were reviewed. Total of 22
articles are reviewed and summarized in this review
paper for the period of 2010 to 2021 with 12 articles in
non- intelligent technique, 7 articles in intelligent
technique and 3 articles in their hybrid form. The review
showed the suitability and reliability of intelligent, non-
intelligent and their hybrid models for accurate
detection of maximum power point and the performance
characteristics of solar photovoltaic systems. Finally, this
review presents the guidance for the researchers and
engineers in the field of solar photovoltaic systems to
select the suitable techniques for enhancement of the
performance characteristics of the solar photovoltaic
systems and the utilization of the available solar
radiation.
Keywords:- Hybrid, Intelligent Technique, Maximum Power
Point Tracking, Non-Intelligent Technique, Performance,
Solar Photovoltaic.
I. INTRODUCTION
The conversion of solar energy into electricity has
been conventionally used for some years now. The IEA’s
comprehensive and comparative study of the world energy
consumption reviewed that in 2050, more than 45% of
necessary generated and transmitted energy in the world will
be exclusively produced by solar PV arrays [1]. IEA also
stated that as regional energy consumption falls by 7%, the
new generation will grow by 41% with renewable sources
providing 81% of total output by 2050 which is the largest
share in the world [2].
The major component of a solar photovoltaic (PV)
system is the PV module which is made up of solar cells. A
solar cell converts the energy in the photons of sunlight into
electricity by the means of the PV phenomenon found in
certain types of semiconductor materials such as selenium
(Se) germanium (Ge) and silicon (Si). In isolated operation,
Photovoltaic cell produces a negligible amount of power. To
produce substantial electrical output power, solar cells are
connected in series and parallel to form a PV module. PV
cells are connected in series to increase voltage output and
connected in parallel to increase the current output [3].
The efficiency and performance of solar PV module
depends on factors such as: geographical factors (latitude,
longitude and irradiation), Environmental factors (pollution,
humidity, wind, temperature, Dust and rain) and
Photovoltaic technology (crystalline, monocrystalline,
polycrystalline and thin film). So, for PV solar energy to be
efficiently and economically used, there is a need to study
the environmental parameters that can negatively affect the
performance of the PV system and also to deploy the best
method to minimize it. However, the solar modules are rated
2. Volume 6, Issue 5, May – 2021 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
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under Standard Test Conditions (STC) with irradiance of
1000W/m2
, ambient temperature of 25˚C and Air Mass of
1.5 [4].
II. CLASSIFICATIONS OF SOLAR
PHOTOVOLTAIC TECHNOLOGY
The Solar PV cell technologies are generally classified
as thin-film solar PV cell technology, Wafer-based
crystalline solar PV cell technology and other recently
emerging technologies.
Figure 1: Classification of Solar Cell Technologies [5]
The two major commercial photovoltaic technologies
being used by the PV designers due to their trending
availability in the renewable energy market as in figure 1
are:
(a) Wafer-based Solar cells made from crystalline silicon
either as single or polycrystalline wafers.
(b) Thin-film products typically incorporate thin layers of
PV active material placed on a glass/metal substrate using
vacuum deposition. The disadvantage of commercial thin-
film materials is that there is huge loss in the output
thickness of the PV array [6].
2.1 Crystalline Silicon (c-Si)
Crystalline silicon (c-Si) is the most used
semiconductor material for the manufacturing of
photovoltaic solar cells. These cells are arranged in parallel
and series into a solar panel to produce solar power from the
sunlight. Electronically, a monocrystalline silicon is used in
the production of microchips. Crystalline silicon is also
known as the first generational solar cells, as they were the
first silicon wafer and rampant type with good quality. The
c-Si known as wafer based silicon solar cells are made from
wafers with characteristics such as thickness of 160/190μm,
efficiency of 25.6± 0.5%, areas of 143.7cm2
and Voc of
0.740V [7][5].
2.2 Polycrystalline Solar Cell (Multi-Si)
Another name for polycrystalline silicon is Polysilicon
(Poly-Si) and it is a highly purified type of silicon used by
solar PV companies as raw material. Siemen process is a
method of producing polysilicon from high grade
metallurgical silicon using chemical purification processes.
This process is directly cast into multi-crystalline ingots to
grow single boule of silicon crystals. The crystals are then
sliced into wafers, assembled for the production of solar PV
cells. The advantage of Polysilicon cells used in
photovoltaics is that it is less expensive. The disadvantage is
that it is less efficient compare to those made from
monocrystalline silicon [8][9].
2.3 Amorphous Silicon Solar Cells (a-Si)
Amorphous silicon is one of the most well-developed
of the thin-film technologies for over the years. Amorphous
silicon comprised of non-crystalline or microcrystalline
form of silicon. The high band gap (of 1.7eV) of amorphous
silicon materials made it an outstanding type of silicon
technology which gave it an advantage over c-Si of 1.1eV
energy. The visible light spectrum was absorbed by top cells
of the amorphous silicon while the infrared spectrum of the
bottom cells will be taken care of by Nc-Si. An a-Si is
widely used in the production of pocket calculators and also
to power some private homes and thin-film transistor in
LCDs [10][9][11].
2.4 Multi-Junction Solar Cell (M-J)
Multi junction solar cell consists of different
semiconductor materials that were made of multiple p-n
junctions. The type of p-n junction material and the
wavelengths of light absorbed by the cell will determine the
quantity of electric current to be generated. The use of
multiple semi-conducting materials improves the efficiency
and rate of conversion of sunlight by the cell to electrical
energy. Furthermore, each layer of the junction has different
band gap which allows it to absorb electromagnetic radiation
over different portions of the spectrum. The Advantage of
M-J cells is that it is used in special application such as
space exploration and satellite. It is also used in
Concentrator Photovoltaics (CPV) to focus sunlight on a
small highly efficient M-J solar cells [12] [9].
2.5 Quantum Dot Solar Cells (QDSC)
A QDSC was designed to make use of quantum dots as
a PV absorbing material. With the rapid growth of QDSC, if
no characteristic defect is detected in nearest feature it will
replace other bulky materials such as Copper Indium
Gallium Selenide (CIGS) or CdTe and Silicon. The
excellent characteristics of changing the dots' size of QDSC
due to its tunable band gap makes it attractive for multi
junction solar cells. This is because varieties of materials are
used to improve the efficiency of QDSC by effectively
harnessing M-J portions of the solar [9][13].
2.6 Dye-Sensitized Solar Cells (DSSC)
Dye-sensitized solar cell (DSSC) is a third
generational PV solar cell that converts visible light into
electrical energy. DSSC is a disruptive technology that is
very sensitive to light that it produces electricity at indoors
and outdoors. Its high sensitivity to light enables it to rapidly
converts both natural and artificial light to a reasonable
quantity of electrical energy. A DSSC is a thin-film PV
formed between electrolyte and photo-sensitized anode to
yield photo-electrochemical system. The advantage of
DSSC is that it is less expensive compare to conventional
solid state electronic solar cell designs [14][9]. Another
advantage is that, it also converts artificial light into
electrical energy even at indoor state.
3. Volume 6, Issue 5, May – 2021 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
IJISRT21MAY271 www.ijisrt.com 458
2.7 Perovskite Solar Cells (PSC)
Perovskite cells are lead-halide based with crystal
structures. A perovskites material is a hybrid solar cell
material known as organic-inorganic solar cell material
[15][16]. The general chemical formula for perovskite
material is given by ABX3 where A is organic or inorganic
Cation (Na+
, CH3NH3
+
etc), B is inorganic Cation (Pb2+,
Sn2+,
Fe2+
etc) and X is inorganic Anion (Cl-
, I-
, O2-
) [17]
[18] [19]. It is produced from the by-products of crude oil
(methyl ammonium and ethyl ammonium) and inorganic
compounds (lead iodide, tin iodide) [20]. The advantages of
Perovskite materials are (a) direct optical band gap (b) broad
light absorption (c) bipolar transport (d) long carrier
diffusion length and finally its flexibility [11] [21][22].
III. MAXIMUM POWER POINT TRACKING
(MPPT)
Maximum Power Point (MPP) can be defined as the
point along PV curve where the output power has the
maximum value with minimum conductance. An embedded
device that continually searches and locates the MPP of a
photovoltaic panel is called Maximum Power Point Tracker
(MPPT) [23].
Maximum power point tracking is a tracker
enhancement incorporated into a charge controller that
isolates the charging equipment output power from the
restrictive effect of the battery, for effective utilization of the
output maximum power of the charging equipment. MPPT
can also be described as an electronic system that operates
the photovoltaic modules in a sequential and chronological
manner that permits the module to transfer nearly all the
generated power to the load.
3.1 Theory of Maximum Power Point Tacking
MPPT is not a mechanical form of tracking where
there is a physical move of the panel to make it point
directly at the direction of the rays of the sun. Solar
tracking system was one of the popular ancient manual
ways of tracking, that involves aligning Photovoltaic solar
panels to the direction where the solar irradiation is at
highest. The disadvantage of this conventional technique is
that it consumes times, power losses during manual panel
transfer from low irradiance position to higher irradiance
position. However, the aforementioned drawbacks of solar
tracking technique led to introduction of MPPT.
Furthermore, MPPT technique was embraced to effectively
and efficiently transfer the generated power from the
Photovoltaic panel to the load with minimal power loss.
Despite the use of MPPT not all the power generated by the
photovoltaic panel were transferred to the load due to losses
as a result of hysteresis.
MPP is a point along P-V curve where the photovoltaic
module transfers the highest percentage of the power
generated to the load. It can also be described as the point
along P-V characteristic curve where the impedance of the
load is equivalent to the impedance of the solar photovoltaic
panel. At this mentioned point the generated power is nearly
transferred to the load with negligible loss. The quantity of
power transferred from the solar PV panel to the load
depends on the available maximum power harvested form
the PV panel and also on the efficiency of the MPPT
[24][25].
3.2 Maximum Power Point Tracking Technique
MPPT technique is one of the various tracking
techniques that has been validated and adopted to ensure
that almost all the generated power from the solar
photovoltaic panel are transferred to the load with minimal
energy loss. Many techniques have been used in MPPT to
ensure effective power transfer. MPPT technique is broadly
classified into intelligent and non-intelligent techniques.
Some of the non-intelligent techniques are Fractional Short
Circuit Current (FSCC) Technique, Fractional Open Circuit
Voltage (FOCV) Technique, Perturb and Observe (P&O)
technique, Adaptive Perturb and Observe (AP&O)
technique, Incremental Conductance (INC) technique,
Improved Incremental Conductance (IINC) technique,
Random search method, DIRECT Search (DIRECT SA)
method [26] and Optimized Adaptive Differential
Conductance (OADC) technique. Intelligent MPPT
techniques comprises Particle Swarm Optimization (PSO),
Takagi-Sugeno (T-S) Fuzzy technique, Artificial Neural
Network (ANN) and Fuzzy logic techniques, scanning
particle swarm optimization [27][28].
3.2.1 Non-Intelligence Maximum Power Point Tracking
Technique
The non-intelligence MPPT technique is one of the
conventional tracking techniques with little improvements.
They have excellent performance with fast response without
overshoot and less fluctuations/oscillation at MPP when
experiencing rapid atmospheric change. It is implementable
at low cost and with high efficiency. Examples of Non-
intelligence MPPT techniques are Perturb & Observe
(P&O), Improved Incremental Conductance (IINC),
Dividing Rectangle Search (DIRECT SA), Incremental
Conductance (INC), Fractional Open Circuit Voltage
(FOCV), Random Search Method (RSM). Centralized,
Distributed and Reconfiguration Technique for Mismatching
Conditions, Variable Indicator and Scaling Factor,
Fractional Short Circuit Current (FSCC), Adaptive Perturb
& Observe (AP&O) and Optimized Adaptive Differential
Conductance (OADC) [29] [30] [31].
3.2.1.1 Fractional Short Circuit Current (FSCC)
Technique
Fractional Short Circuit Current under varying
atmospheric conditions is determined when current at its
maximum power point is equivalent to the product of
proportionality constant and short circuit current in a PV
arrays as shown in (1).
𝐼𝑚𝑝𝑝 = 𝐾2 ∗ 𝐼𝑠𝑐 (1)
Where: 𝐾2 = proportionality constant; 𝐼𝑠𝑐= short circuit
current
The proportionality constant determined from the PV
array range from 0.78 to 0.98 [32]. Boost converter is used
to enhance the efficiency of the technique because the
4. Volume 6, Issue 5, May – 2021 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
IJISRT21MAY271 www.ijisrt.com 459
switching elements in the power converter acts as switch to
short down the circuit [33]. At STC short circuit current is
equal to current of the photovoltaic.
The main advantage of fractional short circuit current
technique is its low cost of implementation and simplicity.
The drawback of this technique is its inability to track the
real MPP due to parametric approximation. Secondly, power
losses due to periodical shortening of the solar PV array
using additional switches in control of 𝐼𝑠𝑐
3.2.1.2 Fractional Open Circuit Voltage (FOCV)
Technique
Fractional open circuit voltage technique is one of the
simplest MPP techniques that is used to determine the MPP
of a PV array at constant voltage. This technique makes use
of linear relationship between Voltage Maximum Power
Point (Vmpp) and Open circuit Voltage (Voc) of the PV
array under varying temperature and irradiance as expressed
in equation (2) [33].
𝑉
𝑚𝑝𝑝 = 𝑘1 ∗ 𝑉
𝑜𝑐 (2)
Where; 𝑘1= proportionality constant (0.71≤k1≤0.78);
Voc = Open Circuit Voltage
Vmpp = Maximum Power Point Voltage
The proportionality constant is dependent on the PV
array characteristics in use as it is computed by dividing
𝑉
𝑚𝑝𝑝 𝑏𝑦 𝑉
𝑜𝑐 at different temperature and irradiance
[32]. 𝑉
𝑚𝑝𝑝 can be obtained by measuring Voc. Intermittently.
The advantage of this method is that it is easy to
implement because of the use of analog devices which is
simple and cheap unlike digital components. The drawbacks
of FOCV are; it has low algorithm efficiency due to power
loss during the measurement of Voc and the error in 𝑘1.
Secondly, inability to tracking the real MPP due to the use
of approximation to determine the relationship between Voc
and Vmpp [33].
3.2.1.3 Perturb & Observe (P&O) Technique
The P&O technique makes use of operating voltage
modification concept to modify the operating voltage of the
photovoltaic panel until the maximum power is harnessed.
The PV array operating voltage is perturbed by small
increment which results to observable change in power [34].
The positive change in power led to voltage perturbation
moving closer to the MPP which further voltage
perturbation along same direction will make the MPPT to
locate the maximum power point. Furthermore, the negative
change in power shows that the OP has moved away from
the MPP and the direction of the voltage perturbation should
be reversed to return back towards the maximum power
point as shown in figure 2 [34].
Figure 2: P-V Characteristics for P&O Algorithm [34].
Equation (3) and table 1 showed the working principle
of P&O algorithm. The algorithm continuously decrements
or increments with respect to reference voltage based on the
previous data until the MPP is attained. When
𝑑𝑃
𝑑𝑉
> 0, the
operating voltage of the Photovoltaic array will be
perturbing within a specified direction, that means that the
perturbation has moved operating point of Photovoltaic
array towards the MPP and reverse is the case when
𝑑𝑃
𝑑𝑉
< 0.
Perturb & Observe technique therefore, will continue to
hover the PV voltage in the direction of the MPP [35].
𝑊ℎ𝑒𝑛 𝛥𝑃 < 0, &𝑉(𝑗) < 𝑉(𝑗 − 1), 𝑡ℎ𝑒𝑛 𝑉𝑟𝑒𝑓 = 𝑉 (𝑗 +
1) = 𝑉 (𝑗) + 𝛥𝑉 (3)
Table 1: Truth Table Summarizing P&O Algorithm
[36][37][38]
Sign of ∆𝒗 Sign of ∆𝑷 Direction of next step
Positive Positive +C
Negative Negative +C
Negative Positive -C
Positive Negative -C
The two approaches used for successful modelling of
perturb and observe algorithm are the Reference Voltage
Perturbation which is used as control parameter together
with PI controller to regulate the duty ratio of the MPP
output power converter and Direct Duty Ratio
Perturbation that is used as control parameter to limit the
need for a Proportional-Integral controller which enhanced
stability and minimized circuit complexity of the system.
This technique led to better energy utilization and enhance
stability characteristic at lower transient response but was
worse performance achieved at rapid atmospheric change
[36].
The advantage(s) of P&O technique is inexpensive,
simple and ease of implementation. The main drawback of
this technique is the inability to determine the real MPP and
its deviate from MPP during rapidly atmospheric change
such as shading [39] [40]. This drawback has caused a lot of
problem in MPPT and that leads to improvement in P&O
technique to adaptive perturb and observe.
5. Volume 6, Issue 5, May – 2021 International Journal of Innovative Science and Research Technology
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3.2.1.4 Adaptive Perturb and Observe (AP&O) Technique
The Adaptive Perturb and Observe technique is
developed to sort out the pitfalls of conventional P&O [41].
In this technique the current perturbation is considered
instead of voltage perturbation unlike the conventional
P&O. Two algorithms are developed for this technique
which are Current Perturbation Algorithm (CPA) and
Adaptive Control Algorithm (ACA). ACA is developed to
set the operating point closer to MPP by estimating optimal
proportional constant (Ksc-opt) and the Short Circuit
Current (Isc). Sudden change in irradiance (∆𝑆) or PV
current (∆𝐼𝑝ℎ) activates ACA. CPA was developed based on
tracking current perturbation by increasing tracking speed.
ACA is developed using a concept where the new operating
point is ascertained based on its nearness to MPP. The new
operating point is obtained by multiplying 𝑘𝑠𝑐_𝑜𝑝𝑡 with 𝐼𝑠𝑐.
This algorithm will be activated when there is sudden
change in irradiance. The AP&O algorithm is calculated
using equation (4)
𝐼𝑟𝑒𝑓 = 𝐼𝑝𝑣(𝑘) + 𝑠𝑖𝑔𝑛 (𝐼𝑝𝑣(𝑘) − 𝐼𝑝𝑣(𝑘 − 1)) ∗
𝑠𝑖𝑔𝑛 (𝑝𝑝𝑣(𝑘) − 𝑝𝑝𝑣(𝑘 − 1)) ∆𝐼 ( 4)
Where; 𝐼𝑝𝑣(𝑘) = PV panel current at kth iteration;
𝑝𝑝𝑣(𝑘) = PV panel power at kth iteration
∆𝐼 = Change in current perturbation size; Sign = Polarity
(±1) of the inside value.
The major advantage of AP&O technique is that the
oscillation around the MPP is drastically reduced due to
variable current perturbation [39]. The drawback of AP&O
technique is its expensiveness, circuit complexity and
inability to locate the real MPP at rapid atmospheric change
which led to development of incremental conductance
technique.
3.2.1.5 Incremental Conductance (INC) Technique
Incremental conductance technique based its
technology on adjustment of MPP voltage to suit the
terminal voltage of the grid [42]. This technique deals with
the incremental and instantaneous conductance of the
photovoltaic module. From equation (5) and figure 3, it
showed that at MPP the slope of the Photovoltaic array
power curve is zero, and equation (6) showed that when the
incremental conductance is greater than the instantaneous
conductance the MPP is located at the left-hand side and
when the incremental conductance is less than the
instantaneous conductance the MPP is located at the right-
hand side. The equations were based on
𝜕𝑖
𝜕𝑣
, where V and I
are the output voltage and output current respectively. The
direction at which the MPPT operating point tracks is
calculated based on the relationship between
𝑑𝐼
𝑑𝑉
𝑎𝑛𝑑 −
𝐼
𝑉
.
This relationship is glean from the fact that
𝑑𝑃
𝑑𝑉
is always
negative when the algorithm needs to track back because the
MPP is located at the right hand side and when positive
reverse is the case [43]. The left-hand side and the right-
hand side of equation (6) were the incremental conductance
and instantaneous conductance of the solar photovoltaic
module respectively. In this technique, both current and
voltage are sensed simultaneously and it reduced tracking
error due to rapid atmospheric change. The drawback of this
technique is its circuit complexity and high cost of
implementation [44][32]. Secondly the accuracy is low as it
kept on tracking and re-tracking
𝑑𝐼
𝑑𝑣
= −
𝐼
𝑣
𝐴𝑡 𝑀𝑃𝑃 (5)
𝑑𝐼
𝑑𝑣
> −
𝐼
𝑣
𝑙𝑒𝑓𝑡 𝑜𝑓 𝑀𝑃𝑃
𝑑𝐼
𝑑𝑣
< −
𝐼
𝑣
𝑅𝑖𝑔ℎ𝑡 𝑜𝑓 𝑀𝑃𝑃
} (6)
The working principle of this technique makes use of
hypothetic ideology that takes the cognizant of the
differential of output power with respect to output voltage to
be equal to the output instantaneous conductance. Power
transferred to the load from the solar PV panel is expressed
by (7) [36].
𝑃 = 𝑉𝐼 (7)
Differentiating with respect to V and equate dp/dv to
zero at MPP equation (4) will be obtained.
𝑑𝐼
𝑑𝑉
= −
𝐼
𝑉
(8)
Figure 3: P-V Characteristic for Incremental
Conductance Algorithm [42]
Incremental conductance technique follows the
photovoltaic curve as expressed in figure 3 and it follows the
working procedures of increasing and decreasing as: when
the present sensed power is greater than the previous sensed
power, the operating voltage increases and vice versa. And
when the present sensed power is equal to the precious
sensed power, the operating voltage remains constant [25].
The control signal of the INC output is used to adjust the
reference voltage of the PV array by either increasing or
decreasing a constant change in voltage to the previous
reference voltage [45].
The advantage of this technique is that it has good
tracking efficiency and also the ability to extracted/harvest
power from the panel effectively. Therefore, Incremental
conductance technique solved the drawback of P&O which
is the inability to track MPP under rapid atmospheric
change. INC technique curbed this aforementioned pitfall of
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P&O by having the ability to determine when MPP has
attained with better accuracy despite the rapid atmospheric
change. The drawback of INC technique is that its control
circuitry is expensive and it oscillates within the MPP. The
MPP is inaccurately determined under low computation of
incremental conductance due to low tracking speed. Hence,
this drawback lead to another technique called improved
incremental technique (IINC) [46].
3.2.1.6 An Improved Incremental Conductance (IINC)
Technique
In [46], an Improved Incremental Conductance (IINC)
technique was developed to solve the problem of
conventional INC technique. This method was achieved by
computing the differential of power to voltage as in (9).
𝑑𝑃
𝑑𝑉
=
p(k) − p(k − 1)
v(k) − v(k − 1)
(9)
Furthermore, incremental conductance and constant
voltage (CV) algorithms were combined for the estimation
of the Voltage Maximum Power Point (Vmpp) which limits
the search space for incremental Conductance algorithm.
The Constant Voltage technique makes use of operating
voltage at the MPP which is linearly proportional to the Voc
of the solar PV panels with rapid change in irradiance and
temperature. The ratio of Vmpp to (Voc) is commonly used
for INC technique. The IINC technique is implemented by
dividing the PV characteristic into three areas where area 1
is from 0 - 70%Voc, area 2 is from 70%Voc - 80%Voc, and
area 3 is from 80%Voc – Voc. The area 2 is the area of
major interest as shown in Figure 4. The IINC technique
searches for the MPP within the mapped area of interest as
in equation (12)
𝑉𝑟𝑒𝑓 = (70% − 80%)𝑉𝑜𝑐 = (𝑉1 − 𝑉2) (12)
The MPPT algorithm of IINC sets the solar
photovoltaic panel current momentarily to zero and allowed
it to measure and record the panels’ Voc.
The advantage of this method over conventional INC
and P&O is the increase in convergence speed which
improves the accuracy of the tracking. The drawbacks of
this technique is that it operates under ideal condition where
shading and irradiance were not considered as a factor and it
has a complex circuitry. This drawback leads to more
research work by researchers to improve MPP tracking
technique.
3.2.1.7 Random Search Method (RSM)
RSM technique is developed to curb the problem of
MPPT under Partially Shaded Condition (PSC)[47].
Random Search Method is a direct search and gradient-free
model with mathematical analysis. The Power generated by
PV systems under PSC are largely non-linear and
multimodal in nature and as a result of that, global
optimization technique is required to maximize the power
generated and transferred to the load. In RSM, random
numbers were used to locate the global optima and gradient
independent of the system. This technique works by
generating and moving a sequence of improved functions
towards a better solution. Consider a function, with n
variables 𝑓(𝑥1, 𝑥2, … , 𝑥𝑛), this function is to be maximized
using RSM step by step technique.
Therefore, iteration number k= 1. Assign a random
number to each variable 𝑋𝑖
𝑘
(𝑋𝑖,𝑚𝑖𝑛, 𝑋𝑖,𝑚𝑎𝑥). For n –
dimensional function 𝑓𝑘
= 𝑓(𝑋1,
𝑘
𝑋2,
𝑘
,… , 𝑋𝑛,
𝑘 ) = 𝑓(𝑋𝑘). This
generates a set of n random numbers 𝑟1,𝑟2…,𝑟𝑛 each lying
within the range [-1, 1] and unit vector u as given in (11)
u =
1
(𝑟1
2+𝑟2
2+⋯+𝑟𝑛
2)(1
2
⁄ )
{
𝑟1
𝑟2
.
.
.
𝑟𝑛 }
(11)
For the next iteration, a new vector 𝑋𝑘+1
is computed
and the corresponding function values is as given in (12) and
(13)
𝑋𝑘+1
= 𝑋𝑘
+ 𝑢𝝀 (12)
𝑓𝑘+1
= 𝑓(𝑋𝑘+1
) (13)
Where: 𝝀 = initial step length
The microcontroller embedded in this technique
continuously monitors PV output power and ensure that the
deviation is not beyond 0.4% of the rated power else the
microcontroller reinitiate the RSM [47][48].
The advantage of RSM is its less memory requirement
and simple computational steps. The drawback is that the
MPP accuracy is not guaranteed as the compiler has a
random computer generator library that can generate wrong
values/data.
3.2.1.8 Dividing Rectangular Search Algorithm (DIRECT
SA) Technique
The Dividing Rectangular Search Algorithm
(DIRECT SA) was developed to solve the problems of
Perturb and Observe and Incremental conductance
techniques [26] . DIRECT SA has the same ease of
implementation, better performance and fast-tracking speed,
especially during PSC as P&O and INC techniques. The
approach is based on the DIRECT SA algorithm which was
developed for searching the global maxima of a Lipchitz
function with a specified interval. The flowchart and
working principles were as shown in in figure 5a. The
advantage of DIRECT SA is its fast and better tracking
speed. The disadvantage is inability to detect the real MPP
during tracking which lead to introduction of optimized
adaptive differential conductance.
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Figure 5a: Flowchart of DIRECT SA Technique.
3.2.1.9 Optimized Adaptive Differential Conductance
(OADC) Technique
This involves analytical method that uses single diode
model for its derivation. It deals with comparing and
balancing the impedance of the load with the impedance of
the solar PV panel with respect to their respective
conductance. The major difference between this technique
and the existing conventional INC technique was that
conventional INC differentiated the current and the voltage
while OADC differentiated current and voltage at its
maximum power points.
Equation (12) is the analytical equation of OADC
which through its recursive nature solved curbed the
inaccuracy in tracking under partial shading conditions.
ϒ
=
(
(
𝐴𝑛𝐾𝑇
𝑞𝑅𝑠
𝑙𝑜𝑔𝑒 (1 +
1
1000Io
) [1 + 𝑘𝑖(𝑇 − 𝑇𝑟𝑒𝑓)]
𝐺
𝐺𝑟𝑒𝑓
)
− Io [𝑒𝑥𝑝 (
𝑞𝑉
𝑚𝑝𝑝
𝐴𝑛𝐾𝑇
)]
𝑉
𝑚𝑝𝑝
−
𝐼𝑜𝑞
𝐴𝑛𝐾𝑇
exp (
𝑉𝑞
𝐴𝑛𝐾𝑇
)
)
(12)
From equation (12), the right-hand side is the panel
impedance and the left-hand side is the load impedance. The
tracking involves balancing the impedance of the load with
that of the panel by driving the operating point as close as to
the maximum power point.
Form the graph of figure 5b it was observed that the
degree of accuracy of the technique was very high as the
MPP was detected at an exact point along the P-V curve
where the resultant conductance is nearly zero. This show
the degree of accuracy of the technique but some factors
where not considered during analytical development such as
the module saturation current which leads to low power
computation of the technique.
The advantage of OADC is that it accurately detects
the MPP without much delay but it has a major drawback of
low power conversion. This low power conversion has led to
more research in this area to improve the power generated
and transferred to the load by considering the module
saturation current (Io) mathematically not by assigning
constant value to it [30].
3.2.1.10 High Gain DC-DC Converter with Model
Predictive Control (HGCMPC) Technique
In [49], this technique proposed the improvement of
the power delivery to the load by designing a high DC-Dc
converter which will serve as a booster to the Panel. The
contribution of this author in this research paper is the
development of model predictive control maximum power
powering tracking (MPC-MPPT) control algorithm with
optimum number of sensors based on fixed and adaptive
step-size and implementation of a new high step-up without
transformer DC- DC converter. The DC-Dc converter was
designed with two inductors, three diodes, one output
capacitor and two power switches.
Figure 6: Typical diagram of the new high gain DC-DC
under first condition.
Under continuous conduction mode (CCM), the
converter has two modes of operation depending on the
switch status (0 or 1). The new DC-DC converter was
designed to operate successfully under two conditions as
detailed below. The first conditions occur when the two
switches are triggered on with high pulse signal. once the
switches are turned on, diodes D2 and Do are turned off and
inductors L1 and L2 are being charged from the DC source.
The characteristics equations and diagram of this first
condition is as shown in equation (13) and Figure (6).
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𝑉𝐿1(𝑡) = 𝑉𝑃𝑉
𝑖𝑃𝑉(𝑡) = 𝑐𝑃𝑉
𝑑𝑉𝑉𝑃𝑉
𝑑𝑡
+ 2𝑖𝐿1
𝑉𝐿2(𝑡) = 𝑉𝑃𝑉
𝑐𝑜
𝑑𝑉0
𝑑𝑡
= 𝑖𝐶𝑜 =
𝑉𝑜
𝑅
. }
(13)
Second condition occurs when two switches a trigged
off at low pulse signal and that turns D2 and Do on to
provide a path for the inductor currents and diode D1is
turned off. Furthermore, inductors L1 and L2 discharges
energy in series to the output capacitor. These conditions
were repeated every switching cycle for effective operation.
Inductor volt-second balance and capacitor charge balance
are the base criteria where the input-output voltage was
obtained. The characteristic equation and figure of second
condition were shown as in equation (14) and figure (7).
Figure 7: Typical diagram of new high gain DC-DC
under second condition
𝑉𝐿1(𝑡) = 𝑉𝐿2(𝑡) = (
𝑉𝑃𝑉 −𝑉𝑜
2
)
𝑖𝑃𝑉(𝑡) = 𝑐𝑃𝑉
𝑑𝑉𝑉𝑃𝑉
𝑑𝑡
+ 𝑖𝐿1
𝑐𝑜
𝑑𝑉0
𝑑𝑡
= 𝑖𝐶𝑜 = 𝑖𝐿1 −
𝑉𝑜
𝑅 }
(13)
From the deduced equations and techniques, it was
observed that the technique fulfilled its objectives and was
validate in figure (8).
From figure 8 it was deduced by the author that the
DC-DC converter has an outperforming efficiency compared
to other techniques used for the validation
The advantage of this technique is that its output
voltage sensor was replaced by an observer to optimize the
system cost and at the same time maintain the same
performance. Secondly, the developed algorithm work with
fixed and adaptive step-size that makes it to operate within a
specified region.
The disadvantage of this technique is that working
with variable switching frequency uneased the optimum
design of the power converter and it has complex circuitry.
3.2.1.11 Control Strategies for Optimum Utilization
(CSOU) technique
This technique made use of three strategic methods to
achieve high efficiency. The three strategies are extraction
of maximum power from PV system under fast varying
irradiance method, extraction of high voltage gain with DC-
DC converter method and development of efficient power
management scheme between SPV and Energy Storage
System (ESS) for reliable storage. The new MPPT algorithm
developed in this review paper makes use of slope detection
method and variable step perturbation and observation
algorithms to effectively detect the real MPP.
In this technique a variable step size was used to
decreases the step size and modified INC algorithm to
increase the converging speed with fast varying irradiance.
The interception between the load line and I-V curve is used
to determine the MPP as shown in figure 10. The new
algorithm did not consider dp/dv =0 rather considered
dI/dV+I/V<0.06 as a fixed point. The high voltage gain was
configured with Soft Switch Interleaved Boost Converter
and the voltage gain was expressed as in equation (14) and
figure 9 is the Soft Switch Interleaved Boost Converter
(SSIBC) for high voltage gain applications.
Figure 9: Block Diagram of SSIBC for High Voltage
Gain Applications
Figure 9 operates in four modes of operation and the
switches are operated in any one of the three ways as shown
in table 2.
Table 2: Switching Sequence for Proposed SSIBC
S/N 1 2 3
S1 ON ON OFF
S2 ON OFF ON
𝑀 =
𝑉𝑜
𝑉𝑝𝑣
=
2
1 − 𝐷
[1 + 𝑁] (14)
After the node and branch mathematical analysis in
[50], equation (14) was obtained which helped curtail the
leakage currents and improve the duty circle for fast
tracking.
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Figure 9: I-V Curve at Difference Irradiance with Load
Line
Points A, B, C in figure 9 are the intercepting points
between the load line and the current-voltage curve where
the MPP is located. It was all so stated that Vmpp multiply
by Impp gives MPP.
The advantage of this technique is that it reduces the
steady state oscillations which improves the dynamic
performance of the whole system. Secondly at medium duty
ratio a very high voltage gain is obtained. The disadvantage
of this technique is that there are a lot of power loss during
switching and secondly, the system compilation is slow in
action.
3.2.1.12 Enhanced Adaptive Extremum-Seeking Control
(EAESC) Algorithm
This makes use of Tylor expansion to find the
optimum of the extremum and it makes use of two methods
[51] This is the most recent non intelligent based MPPT as
of the compilation of this review paper.
This technique developed a new MPPT algorithm
based on the adaptive Extremum Seeking Control (ESC)
method to track the Global Maximum Power Point (GMPP)
while improving tracking efficiency, convergence time, and
accuracy in a PV system. An adaptive loop is utilized to
yield variable perturbation signal amplitude by using the
measured power of the PV system. This technique overcome
the problem of low computational complexity by using the
quantity of ESC- based MPPT algorithm to add perturbation
adaptation. The perturbation amplitude of this new MPPT
changes only when the power variation of the system is
greater than the reference value. With this new technique,
small change on the amplitude are sufficient to guarantee
that the system does not achieve Local Maximum Power
Point (LMPP) and to avoid large oscillations in the output
response. Hence, convergence time, power oscillations in
steady state, and accuracy in tracking the GMPP considering
partial shading condition was evaluated in this technique.
Figure 10: Schematic Working Diagram of MPPT
Algorithm of Adaptive ESC
This technique was achieved by analyzing the figure
10 by adding a sinusoidal perturbation signal at the plant
input (modulation) and multiplying the output by the same
signal (demodulation) after a high-pass filter (HPF). Using
Taylors expansion rule around θ*, the function (f) within the
loci will be written as in equation (15).
θ – θ* = a sin wt – õ (15)
Therefore, after all the necessary analytical processes
the result signal is given as in equation (16)
𝜉 =
𝑎2
𝑓ʺ
2
õ +
𝑎2
𝑓ʺ
2
õ𝑐𝑜𝑠2𝑤𝑡 +
𝑎𝑓ʺ
2
õ2
𝑠𝑖𝑛𝑤𝑡
+
𝑎3
𝑓ʺ
8
(𝑠𝑖𝑛3𝑤𝑡 − 𝑠𝑖𝑛𝑤𝑡) (16)
The adaptive ESC equation was given as in equation (17) for
effective and efficient tracking
Ppv(t) – Ppv(t-1) ≥F (17)
Where: Ppv(t) = immediate calculated PV power, Ppv(t-1) =
previous calculated power, F=predetermined value of power
variation. The working principle is that, if the power
variation is greater than a predetermined value (F), the
amplitude is increased during a short time to help the ESC
algorithm escape from a local optimum and get close to the
global maxima. The amplitude (a) will be set as in equation
(18).
𝑎 = 0.15𝑒−
𝑡
𝑟 (18)
Figure 11: Validation Result of the Developed Technique
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This reviewed technique involved both theoretical and
practical work, from the validation it was observed that the
technique is outperforming others used in the validation.
This reviewed paper has advantages over the other
non-intelligent based MPPT technique such as its ability to
locate the global maxima in a very short time and the less
circuit complexity due to the use of already ESC developed
algorithm. As of the time of this review it was observed that
Enhanced MPPT Algorithm Based on Adaptive Extremum-
Seeking Control Applied to Photovoltaic Systems Operating
under Partial Shading has the best MPPT tracking speed,
convergence time and excellent performance based on
MPPT tracking under partial shading conditions.
3.2.2 Intelligent MPPT Techniques
The introduction of intelligence in maximum power
point tracking of a PV systems is very promising and a
lucrative area for researchers. The technique has a very good
MPP tracker with excellent performance in terms of
accuracy and speed during PSC. Examples of intelligence
MPPT techniques are Fuzzy Logic (FL), Particle Swarm
Optimization (PSO), Artificial Neural Network (ANN),
Improved Particle Swarm Optimization (IPSO) [39],
Scanning Particle Swarm Optimization (SPSO).
3.2.2.1 Fuzzy Logic Control (FLC) Technique
Fuzzy Logic (FL) was introduced by L. Zadeh in 1965
and the concept was based on approximate reasoning
technique [52]. FL was used to curtail the unsolved MPP
tracking problem such as inability to track the real MPP and
tracking delay or oscillation within the MPP region.
Microcontroller makes artificial controlling technique so
easily because it allows embedment of complicated
programs, codes and algorithm for a specific target. FLC can
also be applied in biometric and series predictions
applications. The five operational fuzzy rule-based system is
expressed as show below:
A database which defines the membership functions of
fuzzy sets is used in the fuzzy rules.
A fuzzification interface which transforms the crisp
inputs into degrees of match with linguistic values.
A rule base containing a number of fuzzy IF THEN
rules.
A decision-making unit which performs the interference
operations on the rules.
Defuzzification interface which transforms the fuzzy
results of the inference into a crisp output.
Figure 12: Block Diagram of Designed Fuzzy Logic
MPPT System [53]
Figure 12 is a diagrammatic representation of designed
fuzzy logic MPPT with Fuzzy Inference System (FIS)
operational techniques [54]. The three stages of Fuzzy logic
control system are; fuzzification, defuzzification and fuzzy
rule base table [33].
Fuzzification: Fuzzification is the process of converting
crisp inputs to fuzzy memberships, transforming numerical
crisp inputs into linguistic variables for it to be used in fuzzy
interference system [54] [55]. The number of membership
function in use will determine the level of accuracy of the
fuzzy. Therefore, the higher the number of membership
functions, the better the controller accuracy. Membership
function varies between 5 and 7 [8, 16, 20, 47]. Figure 13 is
the five fuzzy functional levels where acronyms were
represented as positive Small (PS), Positive Big (PB),
Negative Big (NB), Negative Small (NS) and Zero (ZE).
The variables a and b are the values covered by each of the
membership function and in some situations made less
symmetric to prioritize and optimize the particular fuzzy
level for better accuracy [33] [55].
Figure 13: Membership Functions of FLC [56].
The fuzzy controller solar MPPT inputs are error (E)
and change in error (∆𝐸). The selection of error input is
dependent on the designer’s professionalism and solar PV
system. Error equation can be chosen as the slope of P-V
curve,
𝑑𝑃
𝑑𝑉
because it is zero at the MPP as expressed in (19).
The error change can be defined as in (20) [33][52].
𝐸(𝑘) =
𝑃(𝑘) − 𝑝 (𝑘 − 1)
𝑉(𝑘) − 𝑉 (𝑘 − 1)
(19)
∆𝐸(𝑘) = 𝐸(𝑘) − 𝐸(𝑘 − 1) (20)
The fuzzy logic controller output is the duty cycle,
which is used to drive the DC-DC converter or change in
reference voltage. Secondly, rule base table is computed
based on the combination of error and change in error
which the outcome depends on the type of converter being
used and the designer’s professionalism [33].
The rule base is also called rule base lookup table or
fuzzy rule algorithm as shown in table 3,this associates the
fuzzy inputs to the fuzzy output based on the converted
power and the designer’s level of expertise [55]. Using table
3 as an example, if the operating point is not close to the
right of the MPP, as in (19), the error E notification symbol
is NB. Furthermore, within a short time change of error, ∆𝐸
notified with PB will occur which means that the system
perturbed further away to the right of the MPP. At this point,
the system will automatically introduce a negative sign to
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re-track back NB (moving the OP to the left) to locate the
maximum power point [33] [53].
Table 3: Fuzzy Rule Base Table [38].
E
ΔE
NB NS ZE PS PB
NB ZE ZE NB NB NB
NS ZE ZE NS NS NS
ZE NS ZE ZE ZE PS
PS PS PS PS ZE ZE
PB PB PB PB ZE ZE
Defuzification: This is a process where fuzzy output is
being converted to crisp values. The fuzzy outputs of the
system are aggregated with union operator before
defuzzifing the output [54]. The most popular
defuzzification technique in use is the Centre of gravity
(COG), which is expressed mathematically in (21).
∆𝐷
=
∑𝑌(𝑘) ∗ 𝐹(𝑘)
∑𝑌(𝑘)
(21)
Where; ∆𝐷 = change of duty cycle;
∑𝑌(𝑘) =Ssummation of weight factor
𝐹(𝑘) = the multiplying coefficient based on membership
function [33]. This technique tracks intelligently and was
programmed and implemented with micro controller chips.
The major advantage of this technique is its fast
convergence and minimal oscillation around the MPP. The
disadvantage of this technique is that its effectiveness
depends on the designer’s skill and its mathematical
complexity [55]. This drawback leads to Takagi–Sugeno (T-
S) fuzzy-model.
3.2.2.2 A Takagi–Sugeno (T-S) Fuzzy-Model
Takagi-Sugeno fuzzy model directly drives the system
to the maximum power point and measure isolation without
searching the maximum power point [57]. According to T-S
fuzzy model representation, nonlinear systems can be
described by IF-THEN fuzzy rules that have local linear
dynamic subsystems in the subsequent part. One of the
advantages of this is that the linear matrix inequality (LMI)
technique can be used to design controller gain. The major
advantage is that it is effective and efficient in controlling
complex nonlinear systems. The main drawback of this
technique is that the operational point of the MPPT must be
defined and known which is not obtainable in the technique
[57].
3.2.2.3 Artificial Neural Network (ANN)
ANN is another intelligent based MPPT technique that
uses microcontroller and digital signal processor for its
implementation [32]. Figure 14 shows the basic structure of
a single neural network which consists of three different
layers known as input layer, hidden layer and output layer.
Figure 14: Neural Network Technique [56].
The characteristics of a neural network such as the
number of input nodes and hidden layers are dependent on
the designer expertise. The higher the number of hidden
layers, the better the accuracy of the system. In using neural
network to detect the MPPT of a PV system, the input of the
neural network can be in any kind of combination depending
on the designer’s choice, such as weather condition
(irradiance and temperature) or photovoltaic parameters
such as open circuit voltage and short circuit current. The
output power of the system can either be driven by duty
cycle or reference voltage in order to draw it closer to the
MPP [33]. The efficiency and effectiveness of the algorithm
used by the hidden layer and how best the neural network
has been trained will determine how close the operating
point gets to the MPP [38]. The links between nodes i and j
is a product of the two nodes (wij) as shown in Figure 14.
The wij’s have to be carefully determined through a training
process that may last for a long time (months or years) to
accurately locate/identify the MPP and the input/output
pattern recorded. Neural network algorithm will be trained
based on the characteristic of a particular PV array. The
change in PV array which occurs as a result of PSC, which
implies that the neural network has to be periodically trained
to guarantee accurate maximum power point tracking
detection [38].
The advantage of ANN technique is that it has high
accuracy and fast convergence speed. The main pitfall of
ANN technique is that it takes time to be achieved and also
prone to error as it has a large data and takes years to be
trained [33].
3.2.2.4 Particle Swamp Optimization (PSO) Technique
Particle Swarm Optimization (PSO) is an evolutionary
computational technique that deals with problem
optimization by iteratively improving a particle solution by
mimicking or imitating the flocking patterns of birds and
fish. Furthermore, during particle swarm optimization
algorithm iteration, each single solution in search of space is
optimized and evaluated based on its fitness function. The
velocity of the Particles gives direction towards the optimal
solution [58]. According to Kennedy and Eberhart in [59],
PSO is an evolutionary computation technique that is used
to optimize a continuous nonlinear function and for multi
PV array structure with partial shading conditions (PSC).
PSO model was employed to minimize the problem of
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multivariable with multiple maxima which is caused by PSC
[39] [60]. The algorithm has a number of particles where
each particle can be a candidate solution particle which can
copy the success of nearby particles, and get to their own
success. The position of a particle is dependent on the
nearby best particle and also best solution searched by the
particle. Particle position, 𝑥𝑖, are found using:
𝑥𝑖
𝑘+1
= 𝑥𝑖
𝑘
+ 𝑣𝑖
𝑘+1
(22)
In (22) the velocity component, 𝑣𝑖, represents the step size.
The velocity is calculated as in (23).
𝑣𝑖
𝑘+1
= 𝑤𝑣𝑖
𝑘
+ 𝑐1𝑟1{𝑝𝑏𝑒𝑠𝑡 𝑖 − 𝑥𝑖
𝑘}
+ 𝑐2𝑟2{ 𝐺𝑏𝑒𝑠𝑡 𝑖
− 𝑥𝑖
𝑘} (23)
Where; w = initial weight; K = iteration number; i = 1,
2,…,N, (swarm size).
𝑐1𝑐2 = Acceleration coefficients; 𝑝𝑏𝑒𝑠𝑡 = Personal best
position of particle;
𝐺𝑏𝑒𝑠𝑡 = Global best position of the swarm; 𝑟1𝑟2 = random
variable (0, 1);
𝑥𝑖 = Particle position; 𝑣𝑖 = Velocity of the particle
PSO algorithm can also be used to predict and track
the true maximum power point of a photovoltaic system
[61].
The advantages were ease of implementation and fast
in convergence under PSC. The disadvantage is that it is
highly expensive, complex and not yet implemented. This
complexity and expensive based drawback of PSO leads to
another technique called Improved Particle Swarm
Optimization (IPSO).
3.2.2.5 Improved Particle Swarm Optimization (IPSO)
This technique operates by using two positions known
as updating strategies and a mutation operation which helps
in improving performance and efficiency of the PSO. The
algorithm works sequentially as stated below:
Algorithm Parameters and Problem initialization
The problem is comprehensively defined and
minimized by the algorithm as given in (24)
𝑓(𝑥) = 𝑥𝑑𝑙 ≤ 𝑥𝑑 ≤ 𝑥𝑑𝑢(𝑑 =
1,2, … , 𝐷). (24)
Where;
𝑥𝑑𝑙 = lower decision variable; 𝑥𝑑𝑢 = upper decision
variable; D = problem dimension size.
IPSO parameters are specified in steps such as the
maximum number of iterations (k), decision probability (L)
which determines different position updating strategies, the
mutation probability (𝑃𝑚) and as well as the population size
(PS).
Initialize Swarm
Every initial particle in the swarm is generated
randomly from a uniform distribution that ranges from
[𝑥𝑑𝑙, 𝑥𝑑𝑢](d = 1, 2…, D). Hence the effect of constraints
might not be feasible in some regions because of the
conversion of constraints to penalty function.
Position Updating and Mutation Operation
There are two innovative position updating strategies
that are introduced in position updating. During early
iterations, current position of each particle is adjusted
according to its previous and personal best positions with a
large probability. Furthermore, in late iteration, current
position of each particle is adjusted according to its previous
and global best positions with a large probability, which
indicates that it prefers to mimic its successful companions
at this stage. The two updating strategies based on position
is as shown in equation (25).
𝑥𝑖𝑑
𝑘+1
= {
𝑥𝑖𝑑
𝑘
+ 2 ∗ 𝑟𝑎𝑛1 ∗ (𝑃𝑖𝑑 − 𝑥𝑖𝑑
𝑘
),𝑖𝑓 𝑟𝑎𝑛𝑑() < 𝐿;
𝑥𝑖𝑑
𝑘
+ 2 ∗ 𝑟𝑎𝑛2 ∗ (𝑃𝑔𝑑 − 𝑥𝑖𝑑
𝑘
), 𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒
} (25)
Where, 𝑟𝑎𝑛𝑑(),𝑟𝑎𝑛1, 𝑟𝑎𝑛2 = uniformly randomly generated
numbers [0,1]. Decision probability (L) can be expressed as
in equation (26)
𝐿 = √1 −
𝑘
𝐾
(26)
From the working principle if (26) is satisfied, the
position of current component 𝑥𝑖𝑑
𝑘+1
will be located at a
random position in the region (𝑃𝑖𝑑 − |𝑃𝑖𝑑 − 𝑥𝑖𝑑
𝑘
|, 𝑃𝑖𝑑 +
|𝑃𝑖𝑑 + 𝑥𝑖𝑑
𝑘
|), which is a region near personal best position
component (𝑃𝑖𝑑). Else, the position of current component
𝑥𝑖𝑑
𝑘+1
will then locate a random position in the region(𝑃𝑔𝑑 −
|𝑃𝑔𝑑 − 𝑥𝑖𝑑
𝑘
|, 𝑃𝑔𝑑 + |𝑃𝑔𝑑 + 𝑥𝑖𝑑
𝑘
|), which is an area near the
global best position component ((𝑃𝑔𝑑). From figure 15, it
was observed that when the number of iterations K increases
the decision probability (L) decreases slowly till it gets to
zero.
3.2.2.6 Modified Adaptive Particle Swarm Optimization
(MAPSO)
In PSO, the setting of weighting factors and inertia
weights as a constant are meant to be done by experts. These
parameters are performing very low in terms of searching
speed when set with high or low value. However, with a
smaller parameters, the diversity of population will be
drawn to lower levels [62]. These are the Major drawbacks
of APSO. Due to these pitfalls an improved PSO was
introduced which proposed two major solutions such as: An
adaptive inertia weights (w’) is expressed in equation (25)
𝑤′
=
√
𝑓(𝑥𝑖
(𝑡)
)
𝑓(𝑃𝑏𝑒𝑠𝑡𝑖
𝑡)
, 𝑖𝑓 (𝑥𝑖
(𝑡)
) > 𝑓𝑚𝑎𝑥
1−3
√
𝑓(𝑃𝑏𝑒𝑠𝑡𝑖
𝑡)
𝑓(𝑥𝑖
(𝑡)
)
, 𝑖𝑓 (𝑥𝑖
(𝑡)
) < 𝑓𝑚𝑖𝑛
1−3
}
(25)
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Where;
𝑓(𝑃𝑏𝑒𝑠𝑡𝑖
𝑡) = function value of best position of ith agent,
𝑓(𝑥𝑖
(𝑡)
)= function value of ith agent
fmin = minimum function; fmax = maximum function
The current adaptive function value changed the new
initial weight of the system because at initial operation, the
initial weight is bigger and increases convergence rate which
will continue till the global optimum is found. In the
operation process of PSO, there will be a reduction in
disturbing particles as a result of decrease in mutation rate
[63].
Secondly, the rate of convergence is being improved
by introducing a new competition operator which is
evolutionarily populated to compete with a random
population. Furthermore, by effectively and efficiently
applying this technique, the object function value will
converge to the global optimum and reduces the degree of
the MPP settling at the local maxima.
In [64] Four benchmark functions Rastrigin,
Rosenbrock, Grievank and Sphere are used to test the
optimization performance of APSO technique for solving
complex optimization problems. The advantage of APSO is
its ability to effectively overcome the stagnation
phenomenon and also enhance global search. The drawbacks
are delay, complexity in circuitry design and cost
effectiveness.
3.2.2.7 Scanning Particle Swarm Optimization (SPSO)
Technique
Scanning Particle Swarm Optimization (SPSO) is one
of the most recent metaheuristic techniques that has shown
its accuracy and excellent performance in detecting the
Global Peak (GP) and avoidance of being trapped at Local
Peak (LP) as compared to conventional PSO techniques as
of the time of this review. During PSC, the Global Peak
point varies which affects it position in the P–V curve and
makes it difficult for the PSO technique to capture the new
GP unless it reinitializes. There is always delay in tacking
during reinitialization which may led to premature
convergence. In [31], an SPSO technique which tracks the
new GP position without reinitialization was introduced.
The design approach of SPSO is to be sending a particle to
the anticipated places of peaks to search for any peak with
power greater than the current Global Peak and when it
locates a new Global Peak greater than the current global
peak, it will move the PSO operating point directly to the
new Global Peak. But when the current GP is less than the
previous GP it discards it and maintain the old GP. The
advantage of this technique is that it avoided premature
convergence associated with conventional PSO techniques
but never solved the problem of delay in convergence speed.
The main pitfall of this technique is that the convergence
speed is delayed and also programming complexity.
3.2.3 Hybridized MPPT techniques
This is a new technique that was adopted to ensure that
this problem of inability to detect real MPP of a solar
photovoltaic module during PSC. It involves the
combination of two techniques to ensure better harness of
power from the PV panel and this combination may be
intelligent technique and non-intelligent technique, two non-
intelligent technique or two intelligent techniques for better
and effective tracking. The hybridizations techniques are as
detailed below.
Hybridization of PSO and other techniques simply
means the technical know-how of combining PSO and other
MPPT techniques in a sequential and chronological order
following the technical rule that guides the MPPT tracking
techniques. This involves the integration of other MPPT
technique into PSO for efficient and effective tracking and
reliable power output.
3.2.3.1 Hybridization of PSO and P&O
In [65] Particle Swarm Optimization and Perturb and
Observe techniques were hybridized for better performance.
This technique works by first calculating the range of
possible duty cycles and several duty cycles that will be
tested and the power corresponding to each point will be
calculated by the converter. In the absences of shading, the
algorithm sets the duty cycle constant at optimum point, and
then switches to non-intelligent mode (P&O) waiting for
atmospheric change [66]. This will continue till shading is
detected, then the algorithm switches to intelligent mode
(PSO) to find the Global MPP. When the PSO technique
detects the MPP it will settle there but at small changes in P-
V curve it will switch to non-intelligent mode and maintain
the MPP at that point. The algorithm restarts and PSO is
employed to detect the P-V curve maxima when large
changes are detected. This algorithm tests the power output
at the location of each particle and the particles
communicate with each other to know which of the location
has the best power output. The previous location of the
swarm was determined by the particle’s movement along the
power curve. Every time a system found an MPP, the
tracked point will be noted and installed in the memory for
feature use. The system will take cognizant of the specific
operating or irradiance condition at which the MPP was
recorded. As a result of this awesome observation by the
tracker, this technique builds up a database and uses it to
predict the location of the MPP.
Moreover, one of the major problems with P&O
algorithm is that it oscillates within MPP region and takes
time to locate the exact MPP during rapid change in
irradiance. The advantage of this technique is that the time
taken to locate the MPP is drastically reduced by decreasing
the duty cycle increment or decrement step size. The
disadvantage(s) of this technique is that the speed of
convergence reduced drastically because of the time it takes
it to switch from PSO to P&O and vice versa. This technical
design is complex and expensive.
3.2.3.2 Hybridization of PSO with Adaptive Genetic
Operator (AGO)
In [67] Hybridization of Particle Swarm Optimization
with adaptive Genetic Algorithm operators are introduced.
This is one of the PSO hybridization techniques that deal
with the adoption of exploration of the strengths of
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hybridization and adaptive strategies in improving Particle
swarm optimization performance. It also focuses on
combining inertia weight PSO with adaptive crossover and
the rate of mutation that may eventually occur during the
test for an effective adaptive approach to be employed
during PSO hybridization. This research technique was
meant to serve two important purposes which involves the
identification of the most effective adaptive PSO
hybridization approaches and to also compare the
performance of the hybridized adaptive PSO and the
adaptive inertia weight PSOs [68][62].
This technique compares four possible combinable sets
of adaptive algorithms which are adaptive mutation rate
(AMR), adaptive crossover rate (ACR), adaptive inertia
weight without hybridization (AIW) and adaptive crossover
and mutation rate (ACMR). These algorithms were
combined one after the other and the most successful
combination is subsequently used for a comparison between
ACR, AMR and ACMR. In [69][70], analyses have proven
that adaptive parameterization and hybridization algorithms
have a significant improvement and a good performance.
Regardless of the type of hybridization, the most effective
adaptive parameterization method is ascertained based on
pbest and gbest not based on their fitness.
The advantage is that it exploits different algorithm
and selected the best combination among all, thereby
serving as gang chart for designers who wants to use
different algorithms. The drawback of this research is that it
didn’t put in consideration the exploitation of position (pbest
and gbest) in adaptive parameterization which leads to
inaccuracy in detecting GMPP.
3.2.3.3 Adaptive PSO with Artificial Neural Network
(ANN)
In this technique the weights and biases of the Neural
network neurons are joined together to create a single
vector. A particular set of vectors can be identified as the
best optimized solution among other sets of singly formed
vectors. One of these vectors is found to have the best
operating point using an Adaptive Particle Swarm
Optimization (APSO) technique [71].
Artificial neural networks are mainly used for different
kind of complicated problems because of its powerfulness,
flexibility and ability of learning from examples [72][70]. A
Neural Network Adaptive Particle Swarm Optimization
(NNAPSO) input for a particular experiment is Velocity,
Speed, and Displacement of air blower, the first network is
trained by using training samples. The impact of textual
indication of the learning process is presented on the
standard output during the learning. A database that
gathered from industry was used in the research and the data
recorded and trained with NNAPSO. This technique through
the application of all the necessary principle as in [72],
yielded an excellent performance in terms of tracking speed
and convergence.
The major advantage of artificial neural networks is
that there is no need to prepare any algorithms to perform
any task or to understand the structure or mechanism of the
network before being applied that is its ease of use. The
adaptive particle swarm optimization (APSO) approach was
used to solve the complex condition monitoring problems
[73]. The drawback of this technique is that it has complex
program and mechanism.
3.2.4 Comparison of the Existing MPPT Techniques
The reviewed MPPT techniques will be compared
based on reliability/accuracy, efficiency, advantages and
drawbacks. The drawback of the conventional MPPT leads
to the development of new MPPT technique. The new
technique solves the problem of the old MPPT techniques
and as time goes on the new MPPT needs to be
improvement based on the observed pitfalls. The tables
below show the comparison of different MPPT techniques
reviewed in this paper. table 5 is the summary of all the
reviewed techniques based on all the mentioned
characteristics[38][32][33][34][74][64][75][76][27]. Table
4 summarized the MPPT techniques and also showed their
evolutionary trend. The trend of evolves from the up to
down. The problem reduces down the trend and increases up
the table. The evolvement of the techniques was established
in order to solve the problem that the old technique couldn’t
solve. However, sometimes the new techniques may curb
the problem(s) of the old technique but t at the same time
have one of the problems that the old technique that it
improved on has solved.
Figure 4: Area Partitioning of the P-V Characteristics [46]
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Figure 5b: The P-V and Conductance Characteristics of OADC Algorithm.
Figure 8: Validation using other MPPT Techniques under partial irradiance conditions
Figure 15: Decision Probability L and Iteration K [59]
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Table 4: Summary of the Characteristics of MPPT Techniques Reviewed in this paper
MPP
Technique
Efficiency Convergence
speed
Oscillation Cost Implementation
complexity
Sensed
parameters
Track
real
MPP
Reliability
FSCC Poor Medium Yes Inexpensive Medium Current No Low
FOCV Poor Medium Yes Inexpensive Low Voltage No Low
P&O Medium Varies No Relatively
lower
Low Voltage Yes Low
AP&O Medium Fast No Expensive High (Digital) Current Yes High
INC Max Varies No Expensive Medium Voltage,
Current
Yes Medium
IINC Max Varies No Expensive Medium
(Digital)
Voltage,
Current
Yes High
RSM Medium Varies No Inexpensive Digital Multi-
variable
Yes Medium
DIRECT
SA
Medium fast yes moderate Medium
(digital)
Multi-
variable
Yes High
OADC max Very fast No Moderate Digital Vmpp,
Impp
Yes High
HGCMPC Max Fast No Expensive Digital Current
Voltage
Yes Medium
SCOU Max Varies Yes Inexpensive Digital Multi-
variable
Yes High
EAESC Max Very fast No Expensive Digital Multi-
variable
Yes High
FLC Max Fast Yes Expensive High (Digital) Varies Yes Medium
T-S fuzzy Max Fast Yes Expensive High (Digital) Varies Yes Low
ANN Max Fast Yes Expensive High (Digital) Varies Yes Medium
PSO Max Fast No Expensive Medium
(Digital)
Multi-
variable
Yes High
IPSO Max Fast No Expensive High (Digital) Multi-
variable
Yes Medium
MAPSO Max Fast No Expensive High (Digital) Multi-
variable
Yes Low
SPSO max fast No Expensive High (Digital) Multi-
variable
Yes Medium
PSO & PO Max Fast No Expensive Digital Multi-
variable
Yes High
PSO &
AGO
Medium Fast Yes Expensive Digital Multi-
variable
Yes Medium
APSO &
ANN
Max Medium No Moderate Digital Multi-
variable
Yes Low
IV. CONCLUSION
The comprehensive review above, showed and
elaborated that MPPT is classified basically into intelligent
and non-intelligent MPPT techniques. The review also
showed that two algorithms can be combined to form MPPT
techniques in hybridized form which also curtail some of the
problems of MPPT with high performance. However, for
non-intelligence based MPPT techniques reviewed in this
paper it was discovered that Enhanced Adaptive Extremum-
Seeking Control (EAESC) has the best performance as it is
easily implemented and involves less programming
language with high degree of accuracy. EAESC tracks the
real MPP at a very recommendable speed with high degree
of accuracy. Hybridized techniques also have an excellent
tracking accuracy of which among the reviewed hybridized
technique APSO & ANN has the best performance because
of its ability to detect real Global Maximum of a panel under
partial shading condition. It was also discovered that among
all the MPPT techniques in existence as at the time of this
review, intelligent based technique is the best of all the
MPPT technique. Then, within the intelligent based MPPT
technique reviewed in this paper, scanning particle swarm
optimization (SPSO) technique is the best because of its
ability to dissipate real tracking with excellent accuracy as
well as its ease of implementation under rapidly PSC.
Finally, SPSO, APSO & ANN and EAESC has the best
performance in tracking the MPP of a panel under shaded
condition with high accuracy and good convergence speed
respectively. This reviewed paper will serve as a guide for
researcher with respect to prone and cons of the recent
twenty-two MPPT techniques.
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