Optimizing energy and water consumption in smart buildings is a critical challenge for enhancing sustainability and reducing operational costs. This paper presents a Cyber-Physical System (CPS) framework that integrates Deep Reinforcement Learning (DRL) and Genetic Algorithms (GA) for real-time...

This study explores the integration of Variational Autoencoders (VAEs) and Genetic Programming (GP) to address key challenges in the development of smart cities as cyber-physical systems (CPS). The primary objective is to enhance decision-making processes, optimize resource allocation, and...

CHP (Combined heat and power) generation or cogeneration has been considered worldwide as the major alternative to traditional systems in terms of significant energy saving and environmental conservation. Furthermore, the wind power generators and photovoltaic units have vastly speared over the...

Renewable energy is energy that is in continuous supply over time. These kinds of energy sources are divided into five principal renewable sources of energy: the sun, the wind, flowing water, biomass and heat from within the earth. According to some studies carried out by the research...

Fuel cell power plants (FCPPs) have been taken into a great deal of consideration in recent years. The continuing growth of the power demand together with environmental constraints is increasing interest to use FCPPs in power system. Since FCPPs are usually connected to distribution network, the...

In this paper, a novel control strategy for frequency control in stand-alone application based on coordination control of fuel cells (FCs) and double-layer capacitor (DLC) bank in an autonomous hybrid renewable energy power generation system is implemented. The proposed renewable energy power...

Deregulation and restructuring in power systems, the ever-increasing demand for electricity, and concerns about the environment are the major driving forces for using Renewable Energy Sources (RES). Recently, Wind Farms (WFs) and Fuel Cell Power Plants (FCPPs) have gained great interest by...

In this paper a novel Multi-objective fuzzy self adaptive hybrid particle swarm optimization (MFSAHPSO) evolutionary algorithm to solve the Multi-objective optimal operation management (MOOM) is presented. The purposes of the MOOM problem are to decrease the total electrical energy losses, the...

In this paper a new method based on multi-objective modified Honey Bee Mating Optimization (MHBMO) algorithm is presented to investigate the DFR problem with the consideration effect of the renewable energy sources (RESs). In the proposed algorithm, a new mating process is suggested to overcome...

This paper proposes a new method called the enhanced charged system search algorithm in order to solve the reserve constrained dynamic optimal power flow. The optimal power flow (OPF) is applied to develop the corrective strategies and to make the least cost dispatches. The static OPF solutions...