Application оf Artificial Intelligence Methods in Renewable Energy Systems and Energy Efficiency

Abstract

The development of renewable energy systems requires the use of sophisticated techniques for an accurate estimation of the available energy potential and for effective control and optimization of systems operation. The common feature of Artificial intelligence (AI) methods is that they employ computer systems to perform tasks which require intelligent behavior, such as learning, reasoning, problem solving and decision making under uncertainty. This can be particularly beneficial in modeling, analysis, optimization and prediction of the performance and control of renewable energy systems and more efficient energy use. These systems are highly nonlinear, complex and dynamic, where the underlying physical relationships are not fully understood and the available data are often noisy and/or incomplete. Multi-parameter and multi-criteria aspects of the design of these systems are not easily handled using analytical methods, physical models or numerical methods. AI techniques may provide a promising and reliable alternative, or a complement, to the traditional process-based or statistical approaches used in the energy efficiency and renewable energy systems. They enable to study these systems without any knowledge of the exact relations governing their operation, and once trained, allow performing as complex tasks as prediction, modeling, identification, optimization, forecasting and control. Artificial neural networks, as commonly used AI methodologies, and their application in the energy efficiency and renewable energy systems are presented.