相关论文: An optimization framework for wind farm layout des…

This paper introduces a Multi-Strategy Improved Black Widow Optimization Algorithm (MSBWOA), designed to enhance the performance of the standard Black Widow Algorithm (BW) in solving complex optimization problems. The proposed algorithm…

Wave energy is a fast-developing and promising renewable energy resource. The primary goal of this research is to maximise the total harnessed power of a large wave farm consisting of fully-submerged three-tether wave energy converters…

Reducing the intensity of wind excitation via aerodynamic shape modification is a major strategy to mitigate the reaction forces on supertall buildings, reduce construction and maintenance costs, and improve the comfort of future occupants.…

In this paper, a multi-stage model for expansion co-planning of transmission lines, Battery Energy Storages (BESs), and Wind Farms (WFs) is presented considering resilience against extreme weather events. In addition to High Voltage…

Federated learning (FL) is capable of performing large distributed machine learning tasks across multiple edge users by periodically aggregating trained local parameters. To address key challenges of enabling FL over a wireless fog-cloud…

Cloud computing environments demand dynamic and efficient resource management to ensure optimal performance, reduced energy consumption, and adherence to Service Level Agreements (SLAs). This paper presents a Genetic Algorithm (GA)-based…

Federated learning (FL) has emerged as a widely adopted training paradigm for privacy-preserving machine learning. While the SGD-based FL algorithms have demonstrated considerable success in the past, there is a growing trend towards…

The proper planning of different types of public transportation such as metro, highway, waterways, and so on, can increase the efficiency, reduce the congestion and improve the safety of the country. There are certain challenges associated…

Wind energy significantly contributes to the global shift towards renewable energy, yet operational challenges, such as Leading-Edge Erosion on wind turbine blades, notably reduce energy output. This study introduces an advanced, scalable…

This paper proposes a new optimization model and solution method for determining optimal locations and sizing of renewable energy sources and hydrogen storage in a power network. We obtain these strategic decisions based on the multi-period…

This paper proposes a new method for optimizing frequency-hopping ad hoc networks in the presence of Rayleigh fading. It is assumed that the system uses a capacity-approaching code (e.g., turbo or LDPC) and noncoherent binary…

Real-time rooftop wind-speed distribution is important for the safe operation of drones and urban air mobility systems, wind control systems, and rooftop utilization. However, rooftop flows show strong nonlinearity, separation, and…

In this paper, we propose a combined Online Feedback Optimization (OFO) and dynamic estimation approach for a real-time power grid operation under time-varying conditions. A dynamic estimation uses grid measurements to generate the…

Cross-silo Federated Learning (FL) enables multiple institutions to collaboratively train machine learning models while preserving data privacy. In such settings, clients repeatedly exchange model weights with a central server, making the…

Accurate short-term wind speed forecasting is essential for large-scale integration of wind power generation. However, the seasonal and stochastic characteristics of wind speed make forecasting a challenging task. This study uses a new…

Limiting failures of machine learning systems is of paramount importance for safety-critical applications. In order to improve the robustness of machine learning systems, Distributionally Robust Optimization (DRO) has been proposed as a…

This paper develops a new genetic algorithm based resource allocation (GA-RA) technique for energy-efficient throughout maximization in multi-user massive multiple-input multiple-output (MU-mMIMO) systems using orthogonal frequency division…

This work proposes the adoption of Enhanced Gradient-Based Optimizer (EGBO) as a new approach to the Load Frequency Control (LFC) problem in a two-area interconnected power system. The importance of determining the optimal parameters for…

In wind farms, wake interaction leads to losses in power capture and accelerated structural degradation when compared to freestanding turbines. One method to reduce wake losses is by misaligning the rotor with the incoming flow using its…

In recent years, there is a growing interest in using quantum computers for solving combinatorial optimization problems. In this work, we developed a generic, machine learning-based framework for mapping continuous-space inverse design…