Session: 09-02-03 Wave Energy: WEC Arrays

Paper Number: 127258

127258 - Optimization Analysis for Maximizing Power Production of Multiple Heaving-Buoy-Type Wave Energy Converters in Front of a Vertical Wall 

The demand for renewable energy is rapidly increasing as the world seeks to reduce its reliance on fossil fuels and combat climate change. Wave energy is a promising renewable energy source because it is abundant, predictable, and clean. Wave Energy Converters (WECs) are devices that convert the energy of ocean waves into electricity. Point-absorber type WECs are one of the most promising types of WECs. They are relatively simple in design and can be deployed in a variety of ocean environmental conditions. Point-absorber WECs typically have a floating body that moves up and down as the waves pass. This motion is converted into electricity using a Power Take-Off (PTO) system.

The main purpose of the study is to optimize the power production of multiple cylindrical point-absorber WECs deployed in front of a vertical wall. The study uses a meta-heuristic algorithm called advanced Particle Swarm Optimization (Advanced PSO) to optimize the geometric parameters and position of each WEC. The study assumes that each WEC uses a linear PTO system. The WECs also interact with each other, and the movement of one WEC can affect the movement of the other WECs.

To account for the interaction between the WECs, the three-dimensional frequency domain Boundary Element Method (BEM) was used to calculate the hydrodynamic coefficients and motion responses of the WECs. Sommerfeld's radiation boundary condition was applied as a far-field boundary condition of the computational domain. An Artificial Damping Zone (ADZ) was applied to the free surface at a sufficient distance from the WECs to minimize the influence of diffracted and radiated waves on the bodies. An ADZ is a numerical technique that absorbs waves, preventing them from reflecting back into the computational domain.

The validity of the developed numerical analysis program was verified by comparing the heave Response Amplitude Operators (RAOs) of multiple WECs reported in a previous study. The comparison showed that the developed numerical program produced accurate results.

The advanced PSO algorithm was employed for optimization analysis. This algorithm is a meta-heuristic algorithm that is well-suited for solving complex optimization problems. The Opposition-Based Learning (OBL) was applied for determining initial population. A memory mechanism was applied to reduce computational costs by avoiding repetitive calculations.

The geometric parameters and position of each WEC were used as design variables to be optimized. The objective function for optimization was set to maximize the total power production of the WECs. This means that the optimization algorithm will try to find the values of the design variables that produce the maximum amount of power from the WECs. The optimization algorithm repeatedly executes the numerical program until the design variables converge. This means that the algorithm will keep changing the values of the design variables until it finds a set of values that produce the maximum amount of power from the WECs.

Finally, the converged geometric parameters and position of the WECs were determined. Therefore, this optimization analysis can be used to understand how the design variables affect the power production of the WECs and to identify areas for further improvement.

Presenting Author: Sanghwan Heo Inha University

Presenting Author Biography: Ph.D obtained from Inha University, Korea 2021
Currently, Research Associate at Inha University

Authors:

Sanghwan Heo Inha University
Minju Maeng Inha University
Weoncheol Koo Inha University