Performance Evaluation of Hybrid System (PV/ Wind/ Battery) Integrated with Smart Grids by Ahmed Yahia Yaseen

“…Although the Perturb and Observe method is suggested for wind turbines and photovoltaic systems to generate maximum power output, the Particle Swarm Optimization strategy may generate powerful efficiencies, as explained in this study. …”
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Combined Allocation of Renewable-Based Distributed Generators and Shunt Capacitor Banks in Distribution Networks with Electric Vehicle Load Penetration by Abhilasha Pawar, Rajkumar Viral, Divya Asija, Mohit Bansal

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Identifying Inefficient Urban Residential Land within Shenzhen City: An Approach Using Gaussian Mixture Model and Multi-Source Big Data by Y. Liu, S. Liang, R. Guo, W. Wang, D. Ma, Y. Zheng, L. Zhang, Q. Liu, X. Li

“…To address these issues, this paper employs the Gaussian Mixture Model (GMM) clustering method and integrates multi-source geographical big data to quantitatively characterize land use efficiency. …”
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Optimizing energy systems of livestock farms with computational intelligence for achieving energy autonomy by Anatoliy Tryhuba, Taras Hutsol, Jonas Čėsna, Inna Tryhuba, Krzysztof Mudryk, Sławomir Francik, Savelii Kukharets, Ivan Mishchenko, Roman Oliinyk

“…The object of research is the energy systems of livestock farms, including traditional and renewable energy sources. The subject of the study is models and methods of optimisation based on computational intelligence used for energy resource management. …”
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A Bi-Level Demand Response Framework Based on Customer Directrix Load for Power Systems with High Renewable Integration by Weimin Xi, Qian Chen, Haihua Xu, Qingshan Xu

“…Conventional demand response (DR) strategies, such as price-based and incentive-driven methods, often encounter challenges that limit their effectiveness. …”
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Optimizing the Cost of Process as a Decision-Making Tool to Determine the Selling Price by Mukti Prasaja, Rufaidho Dwi Lestari, Aan Nurrohman

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Multiobjective Optimization of Irreversible Thermal Engine Using Mutable Smart Bee Algorithm by M. Gorji-Bandpy, A. Mozaffari

“…A new method called mutable smart bee (MSB) algorithm proposed for cooperative optimizing of the maximum power output (MPO) and minimum entropy generation (MEG) of an Atkinson cycle as a multiobjective, multi-modal mechanical problem. …”
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Optimization of the Driving Mode Transformation of Hybrid Electric Bus based on Genetic Algorithm by Zhao Lijun, Li Shoucheng, Wei Guangpu, Zhang Hongsheng

“…The hybrid electrical city bus has two power sources to drive vehicle,so the control of vehicle driving mode transformation is become the core of the vehicle control strategy.It not only influences the vehicle fuel economy and emissions,but also influences the driving comfort of the vehicle.An HEV simulation model is built for performance analysis by interlinking of advanced software AVL CRUISE and Matlab/Simulink.By adjusting threshold of the driving mode transformation,the mode can be transformed smoothly.For achieving minimum equivalent fuel consumption,the genetic algorithm（GA）optimization method is applied to get the optima of control parameters which affect the vehicle driving mode transformation in different city bus cycles including Europe and China.The vehicle fuel economy is further improved.…”
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Optimizing Virtual Power Plants with Parallel Simulated Annealing on High-Performance Computing by Ali Abbasi, Filipe Alves, Rui A. Ribeiro, João L. Sobral, Ricardo Rodrigues

“…Rigorous simulations highlight the method’s ability to reduce optimization time, maintain solution quality, and scale efficiently, facilitating real-time decision making in energy markets. …”
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Evaluation of Land Desertification Sensitivity and Ecological Spatial Network Optimization in Gansu Province by Qiu Shi, Yu Qiang, Yang Linzhe, Ma Jun, Wang Ge, Yue Depeng

“…[Methods] By combining the land desertification sensitivity index with ecological networks, nodes in areas with higher sensitivity were selected and optimized by increasing the edges through degree centrality and betweenees centrality analysis. …”
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Comprehensive Optimization of Emergency Evacuation Route and Departure Time under Traffic Control by Guo Li, Ying Zhou, Mengqi Liu

“…Finally, we propose a heuristic algorithm for the optimization of this comprehensive model. In case analysis, we take some areas in Beijing as the evaluation sources to verify the reliability of our model. …”
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Optimizing Zakat: A Multidisciplinary Analysis of Zakat Utilization for Enhancing Inclusive Education by Ely Fitriani, Ali Mudlofir, Nurisan Doloh

“…The utilization of zakat holds positive value, including the development of inclusive facilities and the enhancement of educational accessibility. The syntax for optimizing zakat for the improvement of inclusive education includes identifying optimal funding sources, strategically allocating funds, implementing transparent and accountable management mechanisms, collaborating with educational institutions and relevant stakeholders, continuous monitoring and evaluation, and educating the community about the philosophy of zakat.…”
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Optimization of Electricity Consumption-Associated Costs in a Medium-Sized Logistics Company by Martins Tisenkopfs, Leo Jansons, Ineta Geipele, Sanda Lapuke, Andris Backurs

“…During the research, mixed-type approaches combining qualitative and quantitative research methods and data analysis were employed, where the quantitative methods helped to analyze the company’s electricity consumption and cost changes in different time periods, while the qualitative methods were used in a literature review. …”
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Optimizing green hydrogen strategies in Tunisia: A combined SWOT-MCDM approach by Sassi Rekik

“…Subsequently, a multi-criteria decision-making approach, employing the gray technique for order preference by similarity to ideal solution (TOPSIS-G) method (validated by gray additive ratio assessment (ARAS-G), gray complex proportional assessment (COPRAS-G), and gray multi-objective optimization by ratio analysis (MOORA-G), was used to rank the identified strategies.The SWOT analysis revealed ''Strengths'' as the most influential factor with a relative weight of 47.3 %, followed by ''Weaknesses'' (26.5 %), ''Threats'' (15.6 %), and ''Opportunities'' (10.6 %). …”
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Optimal Dispatch Strategy of Power and Electricity Balance Based on Multi-Energy Complementation by Zhiyuan SUN, Boya PENG, Yan SUN

“…Finally, case studies are performed to verify the effectiveness of the proposed method on the modified IEEE-RTS 1979 system model. …”
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Optimizing public health management with predictive analytics: leveraging the power of random forest by Hongman Wang, Yifan Song, Yifan Song, Hua Bi

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Optimal scheduling of electrical energy in smart buildings based on peer-to-peer transactions by ZHENG Ying, HUANG Hui, QI Qifeng, ZHANG Youbing, MAO Cui, ZHU Kaixiang, FENG Changsen

“…Finally， case studies are conducted to analyze the proposed method and model. The results demonstrate that the proposed model not only effectively increases the local consumption of WPV but also encourages market participants to actively engage in P2P transactions.…”
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Optimizing agricultural biomass selection for biochar production using multicriteria decision-making by Ayodeji Raphael Ige, Grażyna Łaska, Grzegorz Świderski, Grzegorz Zając

“…Given the increasing demand for eco-friendly soil amendments, water treatment efficiency and renewable energy sources, identifying optimal agricultural biomass feedstocks is crucial. …”
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An Analytical Approach to Power Optimization of Concentrating Solar Power Plants with Thermal Storage by Andrii Cheilytko, Spiros Alexopoulos, Andriy Pozhuyev, Oliver Kaufhold

“…In addition, the use of additional factors and the combination of the proposed method with existing numerical methods allows for more refined optimization, which allows for the more accurate selection of the capacity for specific geographical conditions. …”
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Optimal sizing, techno-economic, and environmental assessment of hybrid renewable energy systems by Mohammad Reza Gharib, Amir Mohammadbeigi

“…Simulation results were derived via the Simulated Annealing meta-heuristic strategy, which demonstrated a lower standard deviation compared to the Imperialist Competitive Algorithm and Artificial Bee Colony methods. The aim was to reduce TACs and ensure demand requirements were satisfied. …”
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