Designing of an optimal standalone hybrid renewable energy micro‐grid model through different algorithms

Muleta, Negasa; Badar, Altaf Q. H.

doi:10.1016/j.jer.2023.100011

Cited by 21 publications

(8 citation statements)

References 14 publications

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“…PSO is an optimization search algorithm that minimizes LCOE while maintaining a suitable production range. It has been used for many things, like lowering the cost of energy storage [64] in HPPs, lowering the cost of energy (COE) [65], LPSP, total annual cost (TAC), and emissions [66], solving multi-objective optimization problems, making sure the system works reliably, and lowering the total cost, unmet load, and fuel emissions [67].…”

Section: Optimization Techniquesmentioning

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: Optimization Techniquesmentioning

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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“…[ [12][13][14]16,17,[19][20][21]23,28,30,[32][33][34][50][51][52][53]55,56,60,62] Levelized cost of energy (LCOE) Economic…”

Section: Not Foundmentioning

confidence: 99%

A Review of Hybrid Renewable Energy Systems: Architectures, Battery Systems, and Optimization Techniques

Gómez

León-Aldaco

Aguayo

2023

Eng

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This paper aims to perform a literature review and statistical analysis based on data extracted from 38 articles published between 2018 and 2023 that address hybrid renewable energy systems. The main objective of this review has been to create a bibliographic database that organizes the content of the articles in different categories, such as system architecture, energy storage systems, auxiliary generation components used, and software employed, in addition to showing the algorithms and economic and reliability criteria for the optimization of these systems. In total, 38 articles have been analyzed, compared, and classified to provide an overview of the current status of simulation and optimization projects for hybrid renewable energy systems, highlighting clearly and appropriately the relevant trends and conclusions. A list of review articles has also been provided, which cover the aspects required for understanding HRESs.

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“…The objectives of the problem are to minimize the LCC and CO 2 emissions which is solved using genetic algorithm. Similarly, the optimal sizing of real‐world MGs is studied in References 13,14.…”

Section: Introductionmentioning

confidence: 99%

Optimal sizing of RES and BESS in networked microgrids based on proportional peer‐to‐peer and peer‐to‐grid energy trading

Vankudoth

Badar

2023

Energy Storage

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Networked microgrids emerged from the growing deployment of microgrids in the distribution network. The coordinated operation of networked microgrids offers technical and economical benefits to microgrid owners, customers, grid/utility, and other stakeholders. The optimal capacity sizing of renewable energy sources and battery energy storage systems allows microgrids to minimize costs and maximize reliability. A multi‐objective optimization problem is developed for optimal sizing in a networked microgrid consisting of four different microgrids. The annual energy costs and loss of power supply probability index are taken as objectives. Peer‐to‐peer and peer‐to‐grid energy trading approaches are employed. The peer‐to‐peer energy trading among microgrids employs the proposed “proportional trading method” via a networked microgrid manager or aggregator. The multi‐objective optimization problem formulated is solved using Multi‐Objective Particle Swarm Optimization. The individual objective optimization results for annual energy cost and loss of power supply probability are also analyzed. The proposed method decreases the interaction between the grid and the MGs, and the usage of renewable energy sources is enhanced. The capacity of battery energy storage systems is lowered by 96%, 53.2%, 48.86%, 21% for respective microgrids in networked microgrids. The results of proportional peer‐to‐peer energy trading‐based multi‐objective optimization show that trading energy among microgrids minimizes annual energy cost by 0.75% while maintaining system reliability.

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Designing of an optimal standalone hybrid renewable energy micro‐grid model through different algorithms

Cited by 21 publications

References 14 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 Review of Hybrid Renewable Energy Systems: Architectures, Battery Systems, and Optimization Techniques

Optimal sizing of RES and BESS in networked microgrids based on proportional peer‐to‐peer and peer‐to‐grid energy trading

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