Enhanced Genetic Algorithm for Optimal Demand-Side Control of Time-of-Use Pricing in the Live Central University Building DOI Creative Commons

J. P. Praveena,

I. Jacob Raglend

International Journal of Electrical and Electronics Engineering, Год журнала: 2024, Номер 11(11), С. 1 - 11

Опубликована: Ноя. 30, 2024

The energy auditing process collects data on the type and quantity of connected loads, their ratings, consumption, amount money spent power. Identifying sites with high demand waste in academic buildings, hostels, food courts, other facilities. Solutions for energy-efficient cost-effective ways to conserve reduce electricity prices. response based, balancing supply demand, creates a grid greater economic environmental advantages. This was made possible by an building that reduced costs optimized An audit includes observations, measurements, system surveys, collection, analysis. Demand-side management is used balance demand. We then determine create program emphasizes potential lower increase efficiency employing methodical measuring current use. early convergence problem resolved suggested Enhanced Genetic Algorithm, which employs Fitness Distance Balance selection (FDB). When weather changes or there power outage, met renewable energy. best time use when it most economical. three objective functions optimization are efficiency, overall cost per hour electrical (computer, water, lights, fans), motors' carbon dioxide emissions. By using enhanced genetic algorithm optimize bills, institution backed this. Reduce peak managing consumer usage patterns preserve customer comfort maximize sources.

Язык: Английский

Deep Low-Carbon Economic Optimization Using CCUS and Two-Stage P2G with Multiple Hydrogen Utilizations for an Integrated Energy System with a High Penetration Level of Renewables DOI Open Access

Junqiu Fan,

Jing Zhang,

Long Yuan

и другие.

Sustainability, Год журнала: 2024, Номер 16(13), С. 5722 - 5722

Опубликована: Июль 4, 2024

Integrating carbon capture and storage (CCS) technology into an integrated energy system (IES) can reduce its emissions enhance low-carbon performance. However, the full CCS of flue gas displays a strong coupling between lean rich liquor as dioxide liquid absorbents. Its integration IESs with high penetration level renewables results in insufficient flexibility renewable curtailment. In addition, integrating split-flow facilitates short time, giving priority to energy. To address these limitations, this paper develops capture, utilization, (CCUS) method, which tanks for two-stage power-to-gas (P2G) multiple utilizations hydrogen including fuel cell hydrogen-blended CHP unit are introduced. The CCUS is IES build electricity–heat–hydrogen–gas IES. Accordingly, deep economic optimization strategy IES, considers stepwise trading, coal consumption, curtailment penalties, purchasing costs, proposed. effects CCUS, P2G system, trading on performance analyzed through case-comparative analysis. show that proposed method allows significant reduction both total operational costs. It outperforms without 8.8% cost 70.11% emissions. Compared CCS, yields reductions 6.5% costs 24.7% Furthermore, addition further amplifies benefits, cutting by 13.97% 12.32%. enables consumption expands proportion reach 69.23%.

Язык: Английский

Процитировано

4
Drilling Characteristics Optimization of Polymer Composite Fortified with Eggshells using Box-Behnken Design and Zebra Optimization Algorithm DOI Creative Commons
B. Deepanraj,

A. Saravanan,

N. Senthilkumar

и другие.

Results in Engineering, Год журнала: 2025, Номер unknown, С. 104102 - 104102

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0
Rock blasting crack network recognition based on faster RCNN-ZOA-DELM model DOI
Yu Lei, Shengtao Zhou,

Shuaishuai Niu

и другие.

Bulletin of Engineering Geology and the Environment, Год журнала: 2025, Номер 84(3)

Опубликована: Фев. 11, 2025

Язык: Английский

Процитировано

0
FTDZOA: An Efficient and Robust FS Method with Multi-Strategy Assistance DOI Creative Commons

Fuqiang Chen,

Shitong Ye, Lijuan Xu

и другие.

Biomimetics, Год журнала: 2024, Номер 9(10), С. 632 - 632

Опубликована: Окт. 17, 2024

Feature selection (FS) is a pivotal technique in big data analytics, aimed at mitigating redundant information within datasets and optimizing computational resource utilization. This study introduces an enhanced zebra optimization algorithm (ZOA), termed FTDZOA, for superior feature dimensionality reduction. To address the challenges of ZOA, such as susceptibility to local optimal subsets, limited global search capabilities, sluggish convergence when tackling FS problems, three strategies are integrated into original ZOA bolster its performance. Firstly, fractional order strategy incorporated preserve from preceding generations, thereby enhancing ZOA's exploitation capabilities. Secondly, triple mean point guidance introduced, amalgamating point, random current effectively augment exploration prowess. Lastly, capacity further elevated through introduction differential strategy, which integrates disparities among different individuals. Subsequently, FTDZOA-based method was applied solve 23 problems spanning low, medium, high dimensions. A comparative analysis with nine advanced methods revealed that FTDZOA achieved higher classification accuracy on over 90% secured winning rate exceeding 83% terms execution time. These findings confirm reliable, high-performance, practical, robust method.

Язык: Английский

Процитировано

3
Novel Multi-Classification Dynamic Detection Model for Android Malware Based on Improved Zebra Optimization Algorithm and LightGBM DOI Creative Commons

Shuncheng Zhou,

Honghui Li,

Xueliang Fu

и другие.

Sensors, Год журнала: 2024, Номер 24(18), С. 5975 - 5975

Опубликована: Сен. 14, 2024

With the increasing popularity of Android smartphones, malware targeting platform is showing explosive growth. Currently, mainstream detection methods use static analysis to extract features software and apply machine learning algorithms for detection. However, can be less effective when faced with that employs sophisticated obfuscation techniques such as altering code structure. In order effectively detect improve accuracy, this paper proposes a dynamic model based on combination an Improved Zebra Optimization Algorithm (IZOA) Light Gradient Boosting Machine (LightGBM) model, called IZOA-LightGBM. By introducing elite opposition-based firefly perturbation strategies, IZOA enhances convergence speed search capability traditional zebra optimization algorithm. Then, employed optimize LightGBM hyperparameters multi-classification. The results from experiments indicate overall accuracy proposed IZOA-LightGBM CICMalDroid-2020, CCCS-CIC-AndMal-2020, CIC-AAGM-2017 datasets 99.75%, 98.86%, 97.95%, respectively, which are higher than other comparative models.

Язык: Английский

Процитировано

0
Enhanced Genetic Algorithm for Optimal Demand-Side Control of Time-of-Use Pricing in the Live Central University Building DOI Creative Commons

J. P. Praveena,

I. Jacob Raglend

International Journal of Electrical and Electronics Engineering, Год журнала: 2024, Номер 11(11), С. 1 - 11

Опубликована: Ноя. 30, 2024

The energy auditing process collects data on the type and quantity of connected loads, their ratings, consumption, amount money spent power. Identifying sites with high demand waste in academic buildings, hostels, food courts, other facilities. Solutions for energy-efficient cost-effective ways to conserve reduce electricity prices. response based, balancing supply demand, creates a grid greater economic environmental advantages. This was made possible by an building that reduced costs optimized An audit includes observations, measurements, system surveys, collection, analysis. Demand-side management is used balance demand. We then determine create program emphasizes potential lower increase efficiency employing methodical measuring current use. early convergence problem resolved suggested Enhanced Genetic Algorithm, which employs Fitness Distance Balance selection (FDB). When weather changes or there power outage, met renewable energy. best time use when it most economical. three objective functions optimization are efficiency, overall cost per hour electrical (computer, water, lights, fans), motors' carbon dioxide emissions. By using enhanced genetic algorithm optimize bills, institution backed this. Reduce peak managing consumer usage patterns preserve customer comfort maximize sources.

Язык: Английский

Процитировано

0