Abstract The present study is focussed on solving the relay coordination problem. Protection of microgrids performed through placement directional overcurrent relays (DOCR). efficacy microgrid protection depends all DOCRs placed in system. For this purpose, a number optimization techniques have been employed by power system researcher. In paper, Grey Wolf Optimizer (GWO) proposed for different ...

Short-term wind power forecasting plays an important role in generation systems. In order to improve the accuracy of forecasting, many researchers have proposed a large number models. However, traditional models ignore data preprocessing and limitations single model, resulting low accuracy. Aiming at shortcomings existing models, combined model based on secondary decomposition technique grey wo...

Microgrid control in isolated mode is a highly important subject area. In the present paper, a new method is used for controlling the isolated microgrids. This method was used based on the classification of the microgrids into two groups, namely fast-dynamic (battery and flywheel) and slow-dynamic (diesel generator, electrolyzer, fuel cell). For the microgrid components with fast dynamics, a se...

Traffic-flow prediction plays an important role in the construction of intelligent transportation systems (ITS). So, order to improve accuracy short-term traffic flow prediction, a model (GWO-attention-LSTM) based on combination optimized attention mechanism and long memory (LSTM) is proposed. The LSTM uses assign individual weight feature information extracted via LSTM. This can increase model...

Uniaxial compressive strength (UCS) is one of the most important parameters to characterize rock mass in geotechnical engineering design and construction. In this study, a novel kernel extreme learning machine-grey wolf optimizer (KELM-GWO) model was proposed predict UCS 271 samples. Four namely porosity (Pn, %), Schmidt hardness rebound number (SHR), P-wave velocity (Vp, km/s), point load (PLS...

The optimum output power of the proton exchange membrane fuel cell (PEMFC) is dependent on operational conditions such as pressure, oxidant flow rate, and rate. Therefore, aim this paper to enhance performance PEMFC by identifying optimal operating parameters PEMFC. proposed strategy includes both modelling optimization stages. An adaptive network-based fuzzy inference system (ANFIS) utilized i...

Effort estimation is the most critical activity for success of overall solution delivery in software engineering projects. In this context, paper’s main contributions to literature on effort are twofold. First, paper examines application meta-heuristic algorithms have a logical and acceptable parametric model estimation. Secondly, unravel benefits nature-inspired usage optimizing Deep Learning ...

This paper proposes a novel nature-inspired optimization algorithm called the Fox optimizer (FOX) which mimics foraging behavior of foxes in nature when hunting preys. The is based on techniques for measuring distance between fox and its prey to execute an efficient jump. After presenting mathematical models FOX, five classical benchmark functions CEC2019 test are used evaluate it’s performance...

Accurate short-term load forecasting is of great significance to the safe and stable operation power systems development market. Most existing studies apply deep learning models make predictions considering only one feature or temporal relationship in time series. Therefore, obtain an accurate reliable prediction result, a hybrid model combining dual-stage attention mechanism (DA), crisscross g...

A hybrid proportional double derivative and linear quadratic regulator (PD2-LQR) controller is designed for altitude (z) attitude (roll, pitch, yaw) control of a quadrotor vehicle. The derivation mathematical model the formulated based on Newton–Euler approach. An appropriate controller’s parameter must be obtained to obtain superior performance. Therefore, we exploit advantages nature-inspired...