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Ocean wave renewable energy is fast becoming a key part of renewable energy industries over the recent decades. By developing wave energy converters as the main converter technology in this process, their power take-off (PTO) systems have…
Parameter identification for marine ecosystem models is important for the assessment and validation of marine ecosystem models against observational data. The surrogate-based optimization (SBO) is a computationally efficient method to…
Ocean wave energy is a source of renewable energy that has gained much attention for its potential to contribute significantly to meeting the global energy demand. In this research, we investigate the problem of maximising the energy…
Hand-crafting effective and efficient structures for recurrent neural networks (RNNs) is a difficult, expensive, and time-consuming process. To address this challenge, we propose a novel neuro-evolution algorithm based on ant colony…
This study presents an integrated modeling and optimization framework for a steam methane reforming (SMR) reactor, combining a mathematical model, artificial neural network (ANN)-based hybrid modeling, advanced multi-objective optimization…
A promising direction towards improving the performance of wave energy converter (WEC) farms is to leverage a system-level integrated approach known as control co-design (CCD). A WEC farm CCD problem may entail decision variables associated…
Renewable energy, such as ocean wave energy, plays a pivotal role in addressing the tremendous growth of global energy demand. It is expected that wave energy will be one of the fastest-growing energy resources in the next decade, offering…
Wave energy converters (WECs) are a promising candidate for meeting the increasing energy demands of today's society. It is known that the sizing and power take-off (PTO) control of WEC devices have a major impact on their performance. In…
The growing penetration of renewable energy sources (RESs) in active distribution networks (ADNs) leads to complex and uncertain operation scenarios, resulting in significant deviations and risks for the ADN operation. In this study, a…
In this paper we study the problem of optimal layout of an offshore wind farm to minimize the wake effect impacts. Considering the specific requirements of concerned offshore wind farm, we propose an adaptive genetic algorithm (AGA) which…
In the paper, a multi-objective evolutionary surrogate-assisted approach for the fast and effective generative design of coastal breakwaters is proposed. To approximate the computationally expensive objective functions, the deep…
We propose an optimization algorithm to improve the design and performance of quantum communication networks. When physical architectures become too complex for analytical methods, numerical simulation becomes essential to study quantum…
The global energy landscape is undergoing a transformative shift towards renewable energy and advanced storage solutions, driven by the urgent need for sustainable and resilient power systems. Isolated offshore communities, such as islands…
Multi-Objective Evolutionary Algorithms (MOEAs) have proven effective at solving Multi-Objective Optimisation Problems (MOOPs). However, their performance can be significantly hindered when applied to computationally intensive industrial…
A multi-fidelity surrogate model for highly nonlinear multiscale problems is proposed. It is based on the introduction of two different surrogate models and an adaptive on-the-fly switching. The two concurrent surrogates are built…
The amount of power generated by a wave farm depends on the Wave Energy Converter (WEC) arrangement along with the usual wave conditions. Therefore, forming the appropriate arrangement of WECs in an array is an important factor in…
Design of wave energy converter farms entails multiple domains that are coupled, and thus, their concurrent representation and consideration in early-stage design optimization has the potential to offer new insights and promising solutions…
Ocean wave energy is one of the latest renewable energy resources, projected to be commercialized and competitive with other energy technologies in the near future. However, wave energy technologies are not fully developed, so various…
Decision making and planning have long relied heavily on AI-driven forecasts. The government and the general public are working to minimize the risks while maximizing benefits in the face of potential future public health uncertainties.…
Artificial neural networks (ANNs) have evolved from the 1940s primitive models of brain function to become tools for artificial intelligence. They comprise many units, artificial neurons, interlinked through weighted connections. ANNs are…