Implementation of Analytical Method and Improved Particle Swarm Optimization Method for Optimal Sizing of a Standalone PV/Wind and Battery Energy Storage Hybrid System

Karve, Gauri M.; Kurundkar, Kalyani; Vaidya, G. A.

doi:10.1109/i2ct45611.2019.9033540

Cited by 5 publications

(2 citation statements)

References 4 publications

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“…This approach views the hybrid system as a numerical model and defines its size as a function of viability [15]. Karve et al [85] used mathematical methods and improved particle swarm optimization (IPSO) to find the best size for a hybrid PVwind-battery system that could work on its own. They performed the study to lower the system's annual costs.…”

Section: Sizing Hpps Using the Classical Approachmentioning

confidence: 99%

Current Status, Sizing Methodologies, Optimization Techniques, and Energy Management and Control Strategies for Co-Located Utility-Scale Wind–Solar-Based Hybrid Power Plants: A Review

Bade,

Meenakshisundaram,

Tomomewo

2024

Eng

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The integration of renewable energy sources, such as wind and solar, into co-located hybrid power plants (HPPs) has gained significant attention as an innovative solution to address the intermittency and variability inherent in renewable systems among plant developers because of advancements in technology, economies of scale, and government policies. However, it is essential to examine different challenges and aspects during the development of a major work on large-scale hybrid plants. This includes the need for optimization, sizing, energy management, and a control strategy. Hence, this research offers a thorough examination of the present state of co-located utility-scale wind–solar-based HPPs, with a specific emphasis on the problems related to their sizing, optimization, and energy management and control strategies. The authors developed a review approach that includes compiling a database of articles, formulating inclusion and exclusion criteria, and conducting comprehensive analyses. This review highlights the limited number of peer-reviewed studies on utility-scale HPPs, indicating the need for further research, particularly in comparative studies. The integration of machine learning, artificial intelligence, and advanced optimization algorithms for real-time decision-making is highlighted as a potential avenue for addressing complex energy management challenges. The insights provided in this manuscript will be valuable for researchers aiming to further explore HPPs, contributing to the development of a cleaner, economically viable, efficient, and reliable power system.

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Section: Sizing Hpps Using the Classical Approachmentioning

confidence: 99%

Current Status, Sizing Methodologies, Optimization Techniques, and Energy Management and Control Strategies for Co-Located Utility-Scale Wind–Solar-Based Hybrid Power Plants: A Review

Bade,

Meenakshisundaram,

Tomomewo

2024

Eng

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“…The researchers in [30] highlight how, in order to combat environmental degradation and the depletion of fossil fuels, there is a growing emphasis worldwide on renewable energy sources (RES), particularly wind and solar. The intermittent nature of electricity generation poses issues for the integration of Renewable Energy Sources (RES) into the grid, which is being driven by efforts such as the Indian Government's objective of 175 GW RES by 2022.…”

Section: Common Topologies Used In Pv Systemsmentioning

confidence: 99%

A Systematic Review of Boost Converter Design Methodologies for Optimizing Photovoltaic Output

Shou Hin,

Mohamad Nor

2023

IJCERT

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This paper offers a systematic review of boost converter design methodologies, a pivotal component in optimizing photovoltaic system outputs. It comprehensively analyzes various converter topologies, focusing on their operational principles and efficiency in solar energy conversion. The study delves into the intricate challenges of maximizing efficiency under diverse environmental conditions, emphasizing the need for adaptive and robust converter designs. It explores recent technological advancements, highlighting how they address these challenges and contribute to improved photovoltaic performance. The review aims to provide a broad understanding of current trends in converter technology and suggests future research directions, particularly in developing more versatile and efficient converters to better harness solar energy. This work serves as a foundational resource for practitioners and researchers in renewable energy, offering insights into enhancing the efficacy of photovoltaic systems. This comprehensive review examines various boost converter designs for optimizing photovoltaic output, revealing key findings. It was found that certain topologies offer significant advantages in terms of efficiency and adaptability to environmental changes. The paper also highlights the evolving nature of converter technology, showing promising directions in handling solar energy fluctuations. These insights are crucial for advancing photovoltaic system efficiency and reliability, offering a roadmap for future research in renewable energy technology.

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Optimum Sizing of Solar/Wind/Battery Storage in Hybrid Energy System Using Improved Particle Swarm Optimization and Firefly Algorithm

Karve,

Thakare,

Vaidya

2023

Lecture Notes in Networks and Systems

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Implementation of Analytical Method and Improved Particle Swarm Optimization Method for Optimal Sizing of a Standalone PV/Wind and Battery Energy Storage Hybrid System

Cited by 5 publications

References 4 publications

Current Status, Sizing Methodologies, Optimization Techniques, and Energy Management and Control Strategies for Co-Located Utility-Scale Wind–Solar-Based Hybrid Power Plants: A Review

Current Status, Sizing Methodologies, Optimization Techniques, and Energy Management and Control Strategies for Co-Located Utility-Scale Wind–Solar-Based Hybrid Power Plants: A Review

A Systematic Review of Boost Converter Design Methodologies for Optimizing Photovoltaic Output

Optimum Sizing of Solar/Wind/Battery Storage in Hybrid Energy System Using Improved Particle Swarm Optimization and Firefly Algorithm

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