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Addressing the volatility of renewable energies like solar and wind is crucial for the energy system’s stability and optimal utilization of renewable energies. Accurate energy forecasts are important to improve scheduling. Electrical demand and ...

Due to the energy crisis and environmental concerns, wind power has seen a considerable increase in use over the past 10 years as a source of renewable energy. Since wind is intermittent and variable, it is obvious that as penetration levels rise,...

In recent years, both fields, AI and VRE, have received increasing attention in scientific research. Thus, this article’s purpose is to investigate the potential of DL-based applications on VRE and as such provide an introduction to and structured ...

The promotion of wind power generation can effectively optimise China's energy structure and promote the sustainable development of economy and society. However, the application and promotion of wind power will bring a new problem, that is, it increases ...

Accurately predicting the state of wind turbines in wind farms helps to improve productivity, perform preventive maintenance, and reduce operation and maintenance costs. Deep learning can handle complex data and automatic feature extraction in ...

With the development of large-scale power systems, wind power has become the mainstream. Wind power is clean energy, but its uncertainty will bring risks to the economic dispatch of the power system. This paper adopts an adjustable robust optimization ...

This paper proposes a novel two layer differential evolutionary algorithm with multi-mutation strategy (TLDE) for solving the economic emission dispatch (EED) problem involving random wind power. In recent years, renewable energy such as wind power is ...

The trend of increasing demand creates a gap between generation and load in the field of electrical power systems. This is one of the significant problems for the science, where it require to add new generating units or use of novel automation technology ...

Among the rapid evolution of modernisation of alternative energy, the electric power system can be made out of a few Renewable Energy Resources (RES). This paper presents a modern and proficient technique for clearing up the ELD issue. To resolve this ...

The aim of the paper is to evaluate the situation with implementation of renewable energy sources (RES) in the Russian energy system, to highlight the positive and negative influence of this process on consumers and suppliers of traditional electric ...

Present scenario power grid has increased penetration of renewable energy sources (RESs). RESs are clean sources of energy and power production from them with minimal emission is a national target. Already, increased carbon footprint has put nations into ...

The Brain Emotional Learning (BEL) is a novel bio-inspired machine learning approach mentioned as a new class of artificial neural network (ANN). The artificial emotional neural network (AENN) is one of the BEL methods which used the genetic algorithm (...

Distributed renewable energy systems (DRESs) and their interconnection network, typically using Internet-based protocols, are susceptible to a wide range of cybersecurity and resilience challenges. These challenges have been shown to cause problems for ...

The unpredictability of renewable sources of energy especially wind power causes large fluctuations in the power output. The fluctuations are smoothened by building large amounts of battery storage and/or power reserve capacity. By improving the ...

A complex wind-energy harvesting wireless sensor network WSN application for subway tunnels is pre-prototyped using the HarvWSNet co-simulation framework. Detailed models of every component, including energy harvester, tunnel propagation channel, train ...

This paper proposes a nonlinear control approach for an electrical network connected variable speed wind energy system VS-WES based on a permanent magnet synchronous generator PMSG. The proposed configuration consists of a wind turbine WT, a direct ...

In this paper, a robust optimal general regression neural network sliding mode GRNNSM controller is designed for a variable speed wind turbine VSWT. The main objective of the controller is to optimise the energy captured from the wind. Sliding mode ...

In this paper, an intelligent energy management is presented for distributed structure such as a smart microgrid MG that can operate in islanded or connected mode with the main grid. To model this MG, a multi-agent is proposed. This system is based on ...

This paper presents a computer algorithm based on fuzzy logic control to manage the flow of energy in a stand-alone PV/wind/battery hybrid system. The system is composed of 16 photovoltaic PV solar panels, one wind turbine and two batteries. The solar ...

An improved control scheme for stand-alone DFIG-based wind energy conversion system is proposed. The intermediate DC-link of back-to-back PWM converter is supported with a battery energy storage system to smooth the fluctuation of power caused by the ...