Journal
ENERGY CONVERSION AND MANAGEMENT-X
Volume 7, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.ecmx.2020.100053
Keywords
Distribution system; Energy transition; Power-to-Gas; Renewable energy sources; Storage
Categories
Funding
- European Union's Horizon 2020 research and innovation programme [691797]
- H2020 Societal Challenges Programme [691797] Funding Source: H2020 Societal Challenges Programme
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The exploitation of the Power-to-Gas (PtG) technology can properly support the distribution system operation in case of large penetration of Renewable Energy Sources (RES). This paper addresses the impact of the PtG operation on the electrical distribution systems. A novel model of the PtG plant has been created to be representative of the entire process chain, as well as to be compatible with network calculations. The structure of the model with the corresponding parameters has been defined and validated on the basis of measurements gathered on a real plant. The PtG impact on the distribution systems has then been simulated on two network models representing a rural and a semi-urban environment, respectively. The testing has been carried out by defining a set of cases that contain critical situations for the distribution network, caused by RES plant placement. The objectives of the introduction of PtG are the reduction of the reverse power flow, as well as the reduction of the overcurrent and overvoltage issues in the distribution system. The results obtained from annual simulations lead to considerable reduction (from 78 to 100%) of the reverse power flow with respect to the base case, and to alleviating (or even solving) the overcurrent and overvoltage problems of the networks. These results indicate PtG as a possible solution for guaranteeing a smooth transition towards decarbonized energy systems. The capacity factors of the PtG plants largely vary depending on the network topology, the RES penetration, the number of the PtG plants and their sizes. From the test cases, the performance in a rural network (where the minimum capacity factor is about 50%) resulted better than in a semi-urban network (where the capacity factor values range between 21% and 60%).
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