Offshore wind farms, critical for sustainable energy production, face the challenge of optimization among many parameters influencing key performance indicators in competitive ways. This research introduces the novel Integrative Maximized Aggregated Preference Wind Farm Optimization (IMAP-WFO) framework – a comprehensive tool designed to enhance flexibility, accuracy, and uncertainty quantification in offshore wind farm design and operation. Existing methods often fall short due to limitations in adaptability and precision, especially when modeling complex multi-physical behaviors under uncertain conditions. IMAP-WFO overcomes these limitations by combining advanced statistical techniques and simulation methods. At its core are parametric design performance functions, capturing critical aspects of wind farm behavior, including energy production, material usage, and structural fatigue. These functions rely on Kriging meta-models. To address inherent uncertainty, Monte Carlo simulations provide a probabilistic assessment of outcomes. IMAP-WFO's true innovation lies in translating technical functions into socio-economic objectives, including sustainability metrics, annual energy production, capital expenditure, operational expenditure, model uncertainty, and lifetime fatigue. Stakeholders can dynamically weigh these objectives based on their preferences. A validation process ensures the accuracy of design performance functions, comparing simulated results with real-world data. IMAP-WFO's application is demonstrated through case studies: optimizing the levelized cost of energy and exploring wind farm control strategies.@en

The hydrofoil harnesses wave energy and converts it into thrust. In this paper, we present the results of the first experimental study investigating the dynamic behavior of a fully passive foil with spring-loaded pitch and heave in regular waves. Our study shows that the real-time load signal is multi-harmonic with strong superposition, directly proving the robust energy harvesting performance due to the restoring springs. By interpreting the hydrofoil's pose and path from an image sequence captured underwater, we conclude the dynamic evolution of the fully passive hydrofoil interacting with regular waves. The hydrofoil's dynamics exhibit asymmetric surge, pitch, and heave in a motion cycle. Furthermore, we employ a pixel capturing algorithm with self-correction utility to quantify the hydrofoil's forward displacement from the image sequence of the moving carriage. These findings provide valuable insight into the performance and potential of hydrofoils for marine propulsion.

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