Optimal scheduling of residential houses with optimal photovoltaic energy utilization strategy using improved multi-objective equilibrium optimizer algorithm

Yi, Lingzhi; Li, Guanghua; Chen, Kefu; Liu, Qiankun; Liu, Jiankang

doi:10.1016/j.jobe.2022.105102

Cited by 8 publications

(2 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As seen in figure 7, the power enhancement of the PV array is related to the light intensity and roughly maintains an isotropic series of variations [35,36].…”

Section: Reconfiguration Options For Shading Of Rpvpgsmentioning

confidence: 92%

A multivariate reconfiguration method for rooftop PV array based on improved northern goshawk optimization algorithm

Yi,

Cheng,

Wang

et al. 2024

Phys. Scr.

Self Cite

View full text Add to dashboard Cite

Photovoltaic (PV) power has become a crucial solution to the escalating energy crisis. Among the various implementations, Rooftop PV power generation systems (RPVPGS) are predominant in PV buildings. However, RPVPGS will face challenges such as reduced output power due to array fault or shading, leading to fluctuations in Building-Integrated PV (BIPV) power generation. This paper attempts to solve this problem by proposing a novel multivariate reconfiguration method based on the improved northern goshawk optimization algorithm (INGO). The aim is to find the optimal state of RPVPGS under various conditions. In this paper, extensive simulations were conducted on the experimental platform to assess the feasibility and effectiveness of the proposed method. It is worth noting that INGO outperforms existing technologies such as Arrow SoDuku and Zig-zag for the evaluation metrics mentioned in the article. Furthermore, rigorous simulation experiments were conducted on the semi-physical platform to validate the proposed approach. The power enhancement percentage deviation was between +0.1% to +0.2%. These results unequivocally demonstrate that the INGO-based multivariate reconfiguration method accurately reconfigures RPVPGS, ensuring the efficiency and stability of BIPV systems.

show abstract

“…As seen in figure 7, the power enhancement of the PV array is related to the light intensity and roughly maintains an isotropic series of variations [35,36].…”

Section: Reconfiguration Options For Shading Of Rpvpgsmentioning

confidence: 92%

A multivariate reconfiguration method for rooftop PV array based on improved northern goshawk optimization algorithm

Yi,

Cheng,

Wang

et al. 2024

Phys. Scr.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Improved Multi-objective Equilibrium Optimizer (IMOEO), which integrates the techniques of optimal PV energy consumption approach, limited non-dominant mechanism, and TOPSIS to improve the performance of conventional EO, was proposed by Yi et al in the year 2022 [176]. Also, the experimental results clearly reveal that the proposed IMOEO works better than other contemporary state-ofthe-art metaheuristics, demonstrating its effectiveness in residential housing scheduling.…”

Section: Multi-objective Equilibrium Optimizermentioning

confidence: 98%

Recent Developments in Equilibrium Optimizer Algorithm: Its Variants and Applications

Rai

Dhal

2023

Arch Computat Methods Eng

View full text Add to dashboard Cite

There have been many algorithms created and introduced in the literature inspired by various events observable in nature, such as evolutionary phenomena, the actions of social creatures or agents, broad principles based on physical processes, the nature of chemical reactions, human behavior, superiority, and intelligence, intelligent behavior of plants, numerical techniques and mathematics programming procedure and its orientation. Nature-inspired metaheuristic algorithms have dominated the scientific literature and have become a widely used computing paradigm over the past two decades. Equilibrium Optimizer, popularly known as EO, is a population-based, nature-inspired meta-heuristics that belongs to the class of Physics based optimization algorithms, enthused by dynamic source and sink models with a physics foundation that are used to make educated guesses about equilibrium states. EO has achieved massive recognition, and there are quite a few changes made to existing EOs. This article gives a thorough review of EO and its variations. We started with 175 research articles published by several major publishers. Additionally, we discuss the strengths and weaknesses of the algorithms to help researchers find the variant that best suits their needs. The core optimization problems from numerous application areas using EO are also covered in the study, including image classification, scheduling problems, and many others. Lastly, this work recommends a few potential areas for EO research in the future.

show abstract

Real-time implementation of an IoT-based intelligent source allocation system using machine learning technique in a commercial building

Kumar,

Parameswari,

Raja

et al. 2024

Electr Eng

View full text Add to dashboard Cite

Optimal scheduling of residential houses with optimal photovoltaic energy utilization strategy using improved multi-objective equilibrium optimizer algorithm

Cited by 8 publications

References 30 publications

A multivariate reconfiguration method for rooftop PV array based on improved northern goshawk optimization algorithm

A multivariate reconfiguration method for rooftop PV array based on improved northern goshawk optimization algorithm

Recent Developments in Equilibrium Optimizer Algorithm: Its Variants and Applications

Real-time implementation of an IoT-based intelligent source allocation system using machine learning technique in a commercial building

Contact Info

Product

Resources

About