PREDICTIVE CONTROLLER FOR OPTIMAL RENEWABLE HYDROGEN INJECTION INTO THE NATURAL GAS NETWORK

The energy transition is fostering the penetration of renewable energy sources into existing energy networks.In this context, Power-to-Gas solutions, which can convert renewable electricity into green hydrogen, are becoming prominent, emphasizing the significance of gas and electricity network interoperability.During the transitional phase, the gas network can provide flexibility to the energy system by absorbing hydrogen, thus preventing the curtailment of electricity.However, leveraging existing infrastructures cannot disregard compliance with gas quality standards represented by the Wobbe Index, the specific gravity and the Higher Heating Value of the gas.Given the non-negotiable nature of constraints regarding user safety and the inherent unpredictability of renewable energy availability and user demand, successful integration of energy networks necessitates the deployment of intelligent control strategies.This paper presents a novel control strategy based on Model Predictive Control, for the optimal management of hydrogen generation through an electrolyzer, and its subsequent injection into the existing gas network.The test case represents an integrated energy system that comprises renewable energy generation, the electrical grid, an electrolyzer, and the gas network.It was designed to mirror real-world conditions by including unexpected disturbances in renewable energy generation and user demand.The feasibility of the proposed controller is verified through a Model-in-the-Loop simulation platform.The results underscore its efficacy in maximizing the usage of renewable energy while ensuring gas quality standards, also considering the dynamic operation of the gas network.The results affirm its practical viability in real-world energy transition scenarios, paving the way for further exploration into more complex systems in future research.