Abstract:

The green energy transition assumes challenges for power transmission and distribution system operators in terms of maintaining grid stability, security and reliability with the condition of decommissioning large conventional thermal generation units (e.g. gas-fired power plants, nuclear power plants), and increasing the number of distributed renewable power generators connected to transmission and distribution grids by power electronic converters. In this context, wind generators are an established technology and widely accepted as one of the most important technologies for achieving sustainable energy production in European power systems. However, the ongoing integration of distributed renewable power generators requires significant re-evaluation of the traditional strategies currently adopted for power system planning, operation, and regulation. The importance of this revision process cannot be underestimated: there is empirical evidence from several countries where the exponential growth of wind generators has led to issues with power stability and security due to the lack of properly defined regulations to support wind generator efficiency and flexibility. One of the biggest impacts of integrating large volumes of wind power generation is the uncertainty inherent in the technology: the impact of the randomness of the wind resource and power output on grid and electricity market dynamics are crucial issues to be addressed by wind generators and network operators. These complex and correlated uncertainties have a direct impact at the interface between wind generators and the electrical grids. One of the most pressing concerns is the reduction of power system inertia caused by the replacement of large rotating generators with small and distributed units, which is manifest as an increasing vulnerability to dynamic perturbations.
All these critical issues reduce the exploitation of wind generators, hindering their hosting capacity in existing power systems.
In this context, digitization of the electric power sector, which means finding advanced and adaptive IT-based solutions for monitoring, protection and control of the power system, could play a strategic role by enabling a green energy transition while preserving the power system stability and enhancing the grid flexibility in the presence of massive penetrations of wind generators.
Clearly, accurate mathematical models for wind data streaming analysis will always play the central role wind power plant management. Digital twin technology has become of importance during pandemic period and the obtained results achieved in various fields confirmed it as a proven tool especially in the power engineering field.
This paper describes academic research project which proposes a platform that should provide unified and synchronized data for adaptive wind farm control and management. The platform is applicable for any type of wind farm, no matter of technology, the size nor voltage level, to provide optimal operation in real time focused on stable, resilient, secure, reliable and maximized energy output by always using dynamic, real-time fine-tuned wind farm digital twin model as a basis. The goal of the platform is to become a complete unified executable product consisting of a hardware with associated applications, continuously fine-tuning digital twin wind farm model which enable optimal management and control of the wind farms in real time.

Keywords:

academic project, STEM, artificial intelligence, synchronized measurements, renewable energy, wind farm control, digital twins, internet of things.