Abstract

The need to turn to more environmentally friendly sources of energy has led energy systems to focus on renewable sources of energy. Wind power has been a widely used source of green energy. However, the wind’s stochastic and unpredictable behavior has created several challenges to the operation and stability of energy systems. Forecasting models have been developed and excessively used in recent decades in order to deal with these challenges. Deterministic forecasting models have been the main focus of researchers and are still being developed in order to improve their accuracy. Furthermore, in recent years, in order to observe and study the uncertainty of forecasts, probabilistic forecasting models have been developed in order to give a wider view of the possible prediction outcomes. Advanced probabilistic and deterministic forecasting models could be used in order to facilitate the energy systems operation and energy markets management. This paper introduces an overview of state-of-the-art wind power deterministic and probabilistic models, developing a comparative evaluation between the different models reviewed, identifying their advantages and disadvantages, classifying and analyzing current and future research directions in this area.

Highlights

  • Global climatic conditions have changed rapidly over the last decades

  • This paper presents a detailed overview of state-of-the-art wind power deterministic and probabilistic forecasting methodologies

  • It aims to provide a comparative overview through evaluation measures used for these methodologies in order to offer a view of possible expectations and outcomes of similar research

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Summary

Introduction

Global climatic conditions have changed rapidly over the last decades. The continuous increase of energy needs all over the world, as well as the use of limited reserves of traditional energy resources (coal, oil, and natural gas), have turned the interest of researchers towards renewable energy. Because of the wind’s stochastic nature and intermittence, the increased penetration of wind power has created many challenges in the operation and planning of power systems worldwide [1]. To deal with these challenges, it has been necessary to develop wind power forecasting models and methods with increased accuracy. Wind power forecasting has been researched and developed over the past decades in order to deal with the challenges that arose with the rapid increase in the use of wind power in the power systems worldwide. Forecasting models forecast wind power, and help stabilize power systems and organize electricity markets [2]

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