Uncertainty Cost Functions for Wave Energy

Abstract

Wave energy is considered as an important energy source for people living near coastal areas to meet their basic energy needs. Innovative and new technologies can be used for this energy utilization to run the loads from sea waves. Due to its uncertain power availability, we can use uncertainty cost functions based on probability distributions for the availability of the operation of the wave energy microgrid. These probability distributions are based on several mapping models designed for the wave energy, wave height, and wave speed mapping to make the energy more stable and reliable. In contrast to other renewable energy sources, wave energy is inherently unpredictable, making it impossible to model with a single, globally applicable probability distribution function (PDF). The prediction of the behavior of primary wave energy for this purpose is completely based on several probability distribution functions (PDFs) which can be considered as the best for all conditions. In this paper, we have used the Weibull-Rayleigh probability distribution model to develop the uncertainty cost function for wave energy. The Monte-Carlo process is carried out to get the results supported by the Rayleigh probability distribution model consisting of wave height, and uncertain cost histograms. Cost is minimized by using the Weibull Rayleigh model for both overestimation and underestimation costs of wave energy. Monte-Carlo simulation results are further compared with analytical calculation and error between them.