Abstract
This paper introduces a mathematical model designed to optimise the operation of natural gas distribution networks, considering the injection of hydrogen in multiple nodes. The model is designed to optimise the quantity of hydrogen injected to maintain pressure, gas flows, and gas quality indexes (Wobbe index (WI) and higher heating value (HHV)) within admissible limits. This study also presents the maximum injection allowable of hydrogen correlated with the gas quality index variation. The model has been applied to a case study of a gas network with four distinct scenarios and implemented using Python. The findings of the case study quantify the maximum permitted volume of hydrogen in the network, the total savings in natural gas, and the reduction in carbon dioxide emissions. Lastly, a sensitivity analysis of injected hydrogen as a function of the Wobbe index (WI) and Higher Heating Value (HHV) limits relaxation.

Abstract
As the global community transitions towards decarbonization and sustainable energy, green hydrogen is emerging as a key clean energy carrier. This paper addresses the role of hydrogen in transportation, emphasizing the European Union's additionality principle for renewable energy sources in green hydrogen production. It introduces a model for optimally designing hydrogen fueling stations, considering electrolyzers, hydrogen storage, fuel cells, PV systems, and batteries. This model also considers the participation in electricity (energy and secondary reserve), hydrogen, and oxygen markets, and it is evaluated under different additionality policy scenarios. Results indicate that stricter additionality policies reduce the internal rate of return. However, participation in secondary reserve markets significantly boosts operational revenues and compensates for higher investment costs. © 2024 IEEE.

Abstract
Green ammonia production stands as a pivotal component in the transition towards sustainable energy and agriculture, poised to revolutionize numerous industries. This paper presents an optimization control framework for industrial green ammonia fuel hubs to engage in electricity, hydrogen, and oxygen markets, addressing both economic and technical considerations. By evaluating scenarios with and without battery storage, this study demonstrates the potential for increased profitability and energy independence through secondary reserve market participation, alongside insights into the economic viability of photovoltaic investments. These findings underscore the importance of considering market dynamics and technological integration in the sustainable operation of green ammonia production hubs.

Abstract
The replacement of fossil fuel power plants by variable renewable energy sources is reducing the flexibility of the energy system, which puts at risk its security. Exploiting the flexibility of distributed multi-energy resources through aggregators presents a solution for this problem. In this context, this paper presents a new hierarchical model predictive control framework to assist multi-energy aggregators in the network-secure delivery of multi-energy services traded in electricity, natural gas, green hydrogen, and carbon markets. This work builds upon and complements a previous work from the same authors related to bidding strategies for day-ahead markets - it closes the cycle of aggregators' participation in multi-energy markets, i.e., day-ahead bidding and real-time activation of flexibility services. This new model predictive control framework uses the alternating direction method of multipliers on a rolling horizon to negotiate the network-secure delivery of multi-energy services between aggregators and distribution system operators of electricity, gas, and heat networks. We used the new model predictive control framework to conduct two studies. In the first study, we found that considering multi-energy network constraints at both day-ahead and real-time optimization stages produces the most cost-effective and reliable solution to aggregators, outperforming state-of-the-art approaches in terms of cost and network security. In the second study, we found that the adoption of a green hydrogen policy by multi-energy aggregators can reduce their consumption of natural gas and respective CO2 emissions significantly if carbon and green hydrogen prices are competitive.& COPY; 2023 Elsevier Ltd. All rights reserved.

Abstract
This paper presents a general comparison between network-secure and network-free optimization frameworks to manage flexible multi-energy resources. Both frameworks were implemented in a test case that includes electricity, gas, and heat distribution networks. Several potential scenarios for the decarbonization of the multi-energy system were simulated. The economic, technical, and environmental impacts were compiled. The network-secure framework is highly recommended to avoid service disruptions due to network violations, but its implementation comes with a price - overall operational costs increase, sometimes substantially.