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
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.

Abstract
This paper proposes a new decentralized framework for distribution system operators (DSO) to evaluate the network feasibility of the aggregators' bids and remunerate them in case of providing network support services. Compared to other state-of-the-art approaches, this framework is characterized as being more efficient in terms of communication and computational requirements, which is a great advantage for real world applications. The new framework includes a novel optimization model to decide if aggregators' bids should be curtailed or not to ensure network security and minimize DSO costs. To evaluate and compare the proposed DSO framework against the current one, we used the IEEE 69-bus network with three aggregators of distributed energy resources (DER) from the Iberian electricity market. Our experiments show that the proposed DSO framework ensures distribution network security, while the current framework in place in the Iberian Peninsula does not. In addition, we also studied three curtailment policies for the new DSO framework. The results show that minimizing curtailment costs is the most cost-effective policy for the DSO, compared to the other two policies focused on minimizing linear and squared curtailments.

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. This proposal is devised to optimise the quantity of hydrogen injected to maintain pressure, gas flows, and gas quality indexes (Wobbe Index (WI) and the Higher Heating Value (HHV)) within admissible limits. The model has been applied to a gas network case study with three distinct scenarios and implemented using Python. The findings from the case study show the maximum permissible volume of hydrogen in the network, quantify the total savings in natural gas, and estimate the reduction in carbon dioxide emissions. © 2023 IEEE.