Hybrid solar, wind, and energy storage system for a sustainable campus: A simulation study

Muller, Donovan Herbert; Selvanathan, Shanmuga Priya; Cüce, Erdem; Sudhakar, K.

doi:10.2516/stet/2023008

Cited by 13 publications

(3 citation statements)

References 43 publications

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“…To selectively control the solar PV systems [48,49]. The suggested bio-inspired optimization strategy establishes each control device's ideal parameters and configurations, making device control more comprehensive and efficient for varied scenarios.…”

Section: Proposed Design Of An Ensemble Predictive Control Model For ...mentioning

confidence: 99%

EPCMSDB: Design of an ensemble predictive control model for solar PV MPPT deployments via dual bioinspired optimizations

Hole,

Das Goswami

2024

Sci. Tech. Energ. Transition

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With the increasing demand for renewable energy, solar power has emerged as a promising option for sustainable power generation. However, the effectiveness and efficiency of solar power systems rely on the ability to effectively manage their performance, making it essential to develop efficient control models. This paper proposes a novel ensemble predictive control model for solar deployments using bio-inspired optimizations to improve load-connected solar deployments’ performance. The proposed model integrates multiple control devices, including Maximum Power Point Tracker, Proportional-Integral-Derivative, Proportional-Integral, and Fuzzy Logic Controllers, to selectively control the solar Photovoltaic systems. The proposed model incorporates a predictive control operation utilizing an LSTM-GRU (Long Short-Term Memory-Gated Recurrent Unit) with the VARMA (Vector Auto-Regressive Moving Average) model, which can accurately predict the future power generation of the solar system. This feature can facilitate efficient energy management and increase the system’s performance for different use cases. Implement a SEPIC (Single Ended Primary Inductor Capacitor) converter design to improve the system’s overall efficiency levels. To validate the effectiveness of the proposed approach, the author conducted experiments using real-world data and compared the proposed results with other control strategies. The results demonstrate that the ensemble predictive control model based on bio-inspired optimizations outperforms the existing control models regarding accuracy, efficiency, and stability levels. The proposed model has the potential to significantly improve the performance of load-connected solar deployments, offering a more practical approach to solar power generation. The combination of predictive control operations with bio-inspired optimizations can facilitate the design of sustainable energy systems with higher efficiency and accuracy.

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Section: Proposed Design Of An Ensemble Predictive Control Model For ...mentioning

confidence: 99%

EPCMSDB: Design of an ensemble predictive control model for solar PV MPPT deployments via dual bioinspired optimizations

Hole,

Das Goswami

2024

Sci. Tech. Energ. Transition

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“…Eng 2024, 5 developed HOMER to evaluate energy based on resource costs and availability. Several studies [92][93][94][95][96] have used HOMER software (Homer Pro) to determine the most costeffective configuration for hybrid systems, with some finding a combination of solar panels and wind turbines as the optimal approach. Other software tools used for sizing include IHOGA, HYBRIDS2, TRNSYS, and RETScreen.…”

Section: Sizing Hpps Using Software Toolsmentioning

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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“…Sustainable buildings also focus on water conservation through low-flow fixtures, greywater recycling, and rainwater harvesting [19]. Continuous monitoring and management systems help building owners and operators track energy usage, identify inefficiencies, and make necessary adjustments to maintain a net-zero energy balance [20].…”

mentioning

confidence: 99%

Pathway to Sustainability: An Overview of Renewable Energy Integration in Building Systems

Reddy,

Hariram,

Ghazali

et al. 2024

Sustainability

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Decarbonizing the building sector is crucial for mitigating climate change, reducing carbon emissions, and achieving an energy production–consumption balance. This research aims to identify key design principles and strategies to enhance energy savings and analyze the integration potential of renewable energy sources (RES) such as solar, wind, geothermal, and biomass, providing in-depth technical exploration and evaluating current building developments. Moreover, the study also examines recent developments, explicitly focusing on integrating hybrid renewable energy systems, energy storage solutions, and AI-based technological innovations. Through comprehensive analysis and critical evaluation, this research provides valuable insights and practical recommendations for achieving building sustainability and advancing the transition towards a low-carbon built environment.

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Hybrid solar, wind, and energy storage system for a sustainable campus: A simulation study

Cited by 13 publications

References 43 publications

EPCMSDB: Design of an ensemble predictive control model for solar PV MPPT deployments via dual bioinspired optimizations

EPCMSDB: Design of an ensemble predictive control model for solar PV MPPT deployments via dual bioinspired optimizations

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

Pathway to Sustainability: An Overview of Renewable Energy Integration in Building Systems

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