Real-time stochastic power management strategies in hybrid renewable energy systems: A review of key applications and perspectives

Abstract

Given their highly stochastic features, the hasten increase of renewable energy sources contribution in the global energy balance issues a strong impact on power systems operating conditions. In order to overcome drawbacks related to supply reliability and systems stability, real-time power management strategies able to achieve optimal targets in uncertain frameworks are currently of great interest. This paper aims to overview for the first time the latest progresses in the field of real-time power management algorithms designed for hybrid renewable energy systems. The findings of this research provide a comprehensive review of the state-of-the-art, individuating specific fields of application and focusing on the gaps that should be further investigated. Several approaches for real-time stochastic power management are presented from both theoretical and applicative points of view. A wide range of applications in terms of installed power, multi-objective optimization formulation and energy storage technologies hybridization result as the main challenges for real-time power management. To this regard, gradient-based optimization algorithms show the highest potential for real-time power management strategies implementation. In particular, their reduced computational cost if compared to other approaches, as well as the high adaptability to various configurations, make this kind of algorithms worthy of further investigation.