The Walrus Optimization (WO) algorithm, a metaheuristic inspired by walrus behavior, is known for its competitive convergence speed and effectiveness in solving high-dimensional and practical engineering optimization problems. However, it suffers fro...
This paper demonstrates the effectiveness of Demand Side Response (DSR) with renewable integration by solving the stochastic optimal operation problem (OOP) in the IEEE 118-bus distribution system over 24 h. An Improved Walrus Optimization Algorithm...
Energy storage planning and optimal dispatch in real power grids are restricted by high-dimensional nonlinear constraints. The solution process involves a heavy calculation burden. This paper studies the site selection, capacity sizing and optimal di...
Feature selection (FS) is a significant dimensionality reduction technique in machine learning and data mining that is adept at managing high-dimensional data efficiently and enhancing model performance. Metaheuristic algorithms have become one of th...
This paper proposes an Enhanced Walrus Optimizer (EWO), a novel variant of the recently introduced Walrus Optimizer (WO) for solving global and complex power and energy optimization problems. The original WO, inspired by the cooperative and foraging...
In this study, we propose an architectural model for path optimization in cluster order picking within warehouse robotics, utilizing a hybrid approach that combines symbolic control and metaheuristic techniques. Among the optimization strategies, we...
Non-linear systems of equations play a fundamental role in various engineering and data science models, where accurate solutions are essential for both theoretical research and practical applications. However, solving such systems is highly challengi...
With the large-scale integration of renewable energy sources into power systems, the dynamic characteristics of renewable generators have a critical impact on grid security and stability. However, wind turbine manufacturers usually do not disclose ke...
The increasing adoption of plug-in electric vehicles (PEVs) leads to negative impacts on distribution network efficiency due to the extra load added to the system. To overcome this problem, this manuscript aims to optimally integrate distributed gene...
Microgrids with high renewable energy penetration face critical challenges in frequency stability due to reduced system inertia and the presence of parameter uncertainties. This study introduces a novel adaptive virtual inertia control strategy utili...