This paper presents a novel optimization model for the flexible-reliable operation (FRO) of energy hubs (EHs) in electricity, natural gas, and district heating networks. To achieve flexible EH presence renewable sources (RESs) combined heat power (CHP) system, storage systems (ESS) incentive-based demand response program (IDRP) are used. The proposed problem minimizes total expected costs operation, reliability, flexibility networks including EHs. scheme is constrained to optimal flow (OPF)...

Abstract The construction of hybrid power plants with renewable resources can bring significant economic benefits if it is evaluated economically and technically. present study uses a novel optimum methodology for designing combined solar/battery/diesel system in Yarkant, Xinjiang Uyghur Autonomous Region China. In the desired system, green energy designed to reduce use diesel generators. generator has been used photovoltaic, diesel, battery support batteries, as well function backup...

Proper analysis of building energy performance requires selecting appropriate models for handling complicated calculations. Machine learning has recently emerged as a promising effective solution solving this problem. The present study proposes novel integrative machine model predicting two parameters residential buildings, namely annual thermal demand (DThE) and weighted average discomfort degree-hours (HDD). is feed-forward neural network (FFNN) that optimized via the electrostatic...

Renewable energy is becoming more popular due to environmental concerns about the previous source. Accurate solar photovoltaic (PV) system model parameters substantially impact efficiency of conversion electricity. In this matter, swarm and evolutionary optimization algorithms have been widely utilized in dealing with practical problems their straightforward concepts, efficacy, flexibility, easy-to-implement procedural frameworks. However, nonlinearity complexity PV parameter identification...

This paper presents a new approach for the coordinated design of power system stabilizer- (PSS-) and static VAR compensator- (SVC-) based stabilizer. For this purpose, problem is considered as an optimization problem, while decision variables are controllers’ parameters. proposes effective algorithm on rat swarm optimizer, namely, adaptive (ARSO), solving complex problems well controllers. In proposed ARSO, instead random initial population, starts search process with fitter solutions using...

Energy has been one of the most important topics political and social discussion in recent decades. A significant proportion country’s revenues is derived from energy resources, making it strategic macro policy sustainable development areas. demand modeling essential strategies for better managing sector developing appropriate policies to increase productivity. With increasing global energy, necessary develop intelligent forecasting methods algorithms. Different economic non-economic...

Abstract Cloud computing is a rapidly evolving computational technology. It distributed system that offers dynamically scaled resources, such as processing power, storage, and applications, delivered service through the Internet. Virtual machines (VMs) allocation known one of most significant problems in cloud computing. aims to find suitable location for VMs on physical (PMs) attain predefined aims. So, main purpose reduce energy consumption improve resource utilization. Because VM issue...

Benefiting from favorable operational efficiencies, photovoltaic-thermal (PVT) technology is considered as a viable alternative for combined heat and power (CHP) distributed generation; however, the realization of full economic profit requires allocation optimization in terms placement size integrated electricity distribution networks. Also, inability dispatching renewable PVT considerations storages. Further, concerns with uncertainties loads associated solar irradiation PVT-CHP must be...

This paper is proposed a modified sperm swarm optimization algorithm (MSSO) for numerical function and optimal design of damping controller in power system. To provide fine balance between the explorative exploitative behavior, MSSO utilizes chaotic velocity factor. In addition, method considers reasonable limitation to avoid explosion divergence movement. The benchmarked with set test functions results are compared standard (SSO) some other robust metaheuristic from literature. demonstrate...

Skin cancer is one of the most common types cancers that sometimes difficult for doctors and experts to diagnose. The noninvasive dermatoscopic method a popular observing diagnosing skin cancer. Because this based on ocular inference, diagnosis by dermatologists difficult, especially in early stages disease. Artificial intelligence proper complementary tool can be used alongside increase accuracy diagnosis. In present study, new computer-aided has been introduced designed combination deep...

The COVID-19 epidemic is spreading day by day. Early diagnosis of this disease essential to provide effective preventive and therapeutic measures. This process can be used a computer-aided methodology improve accuracy. In study, new optimal method has been utilized for the COVID-19. Here, based on fuzzy <math xmlns="http://www.w3.org/1998/Math/MathML" id="M2"> <mi>C</mi> </math> -ordered means (FCOM) along with an improved version enhanced capsule network (ECN) proposed purpose. ECN mayfly...

This study proposes a new metaheuristic optimization algorithm, namely the white-tailed eagle algorithm (WEA), for global and optimum design of retaining structures. Metaheuristic methods are now broadly implemented to address problems in variety scientific domains. These algorithms typically inspired by natural behavior an agent, which can be humans, animals, plants, or any physical agent. However, specific (MA) may not able find optimal solution every situation. As result, researchers will...

In this study, optimal energy management is addressed in the residential building. The building equipped with renewable energies including wind turbines (WT) and photovoltaic (PV) systems. Stochastic programming used to model uncertainty of resources. To manage these uncertainties reduce total daily cost energy, load control program adopted. respect, five different types loads are modeled building, interruptible, uninterruptible, constant-energy, constant-power movable loads. above charges...

Abstract In recent years, zero‐carbon energy resources such as adiabatic compressed air storage with thermal have been interested due to growing concerns over global warming. This study proposes a microenergy grid including heat and power networks connected through storage, which can be considered hybrid supplying for both networks. The network is supplied the main wind turbine systems, provided pumps. objective function minimizes purchased from demand of pumps in network. Since uncertainty...

Due to utilizing electric vehicles, distributed generations and energy storage units in the distribution networks, it is crucial present a robust management minimize total cost of network with associated uncertainties including electrical demand, prices, behavior renewable generations. In this optimization, power flow, technical constraints such as bus voltage limits transmission line limits, equations governing units, are considered optimization constraints. Since problem nonlinear,...