Recent advancements in data science and artificial intelligence, as well as the development
of clean and sustainable energy sources, have created numerous opportunities for energy …

The exponential growth of network complexity and data volume in modern digital
ecosystems has underscored the need for innovative approaches to optimize network …

Metaheuristic algorithms are extensively utilized to find solutions and optimize complex
industrial systems' performance. In this paper, metaheuristic algorithms are utilized to predict …

This work introduces a novel methodology for real-time optimization (RTO) of process
systems using reinforcement learning (RL), where optimal decisions in response to external …

Ten established, data-driven dynamic algorithms are surveyed and a practical guide for
understanding these methods generated. Existing Python programming packages for …

Power plant heat rate is a plant level performance parameter that indicates the economy of
power production, equipment's safety, and availability. In this paper, seven operating …

The present work deals with an experimental study of the performance of an evaporative
cooling tower (ECT) with a developed fill pack. The fill pack consists of inclined-corrugated …

This study aimed to experimentally investigate the effects of filled beds on the performance
of a cross-flow cooling tower (CFCT) with the approach of using nanofluids. Multi-walled …

Nonlinear structure, vague loading characteristics and parameter uncertainties of the
interconnected power system (IPS) have recently given birth to various controllers that better …

This review provides a deep analysis of the different methodologies to improve the operation
of solar thermal plants based on mathematical optimization. The various schemes found in …