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Computational framework for evaluating the impact of power-to-gas technology on European transmission system with large penetration of renewable sources

Andrea Rogin

Computational framework for evaluating the impact of power-to-gas technology on European transmission system with large penetration of renewable sources.

Rel. Andrea Mazza, Ettore Francesco Bompard, Abouzar Estebsari. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Elettrica, 2018

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Abstract:

In the last years the vertically integrated electrical system (in which a single entity owns the entire chain of electricity supply) has been replaced with a deregulated one, and therefore the electrical system is now managed by different companies. The interaction among these companies is based on a market framework, usually composed of a day-ahead market and an intra-day market. The first market aims to schedule the traditional generators for matching with the forecasted load and intermittent renewable generation. The latter one aims to solve the unbalance derived by the stochastic behavior of both load and renewable generation. The presence of large penetration of renewable sources is one of the key-aspects of the modern electricity system, due to the incentives existing in the past. This large penetration causes an uncontrolled and highly variable power flowing from the distribution network to the transmission one, known in literature as reverse power flow. In order to limit this problem, novel technologies adding new flexibility to the transmission system are needed. Among them, this thesis considers as possible answer the exploitation of the potential of the power-to-gas technology (PtG). PtG allows to absorb the excess of electricity produced by RES by producing, in this study, synthetic natural gas (SNG). A PtG plant therefore behave as a link between electricity system and gas system, with the latter behaving as a storage infrastructure. The interface of PtG plants with the electrical system is the electrolyser, which is electrically characterized as a rapidly variable load, able to counteract the RES effects. In this work a computational framework capable to simulate the day-ahead market and the following intra-day market has been created and it has been applied to three networks: the CIGRE European Configuration network (used as a test network), the UCTE network (representing the continental European transmission network) and a complete European transmission network existing in literature based on the European Network Map provided by ENTSOE. This framework, based on the use of DC Optimal Power Flow, allows to use as inputs different scenarios (current and future ones) both for load and generation. The photovoltaic generation has been modeled through the use of an irradiance simulator existing in literature, while the wind production has been obtained by merging historical European data and a cluster analysis of the power output of a real wind farm. PtG plants have been inserted in the network through the use of a model previously created by Politecnico di Torino, based on real measurements referring to an AEC electrolyser installed in the demo-site of Falkenhagen. The results of a given PtG placement configuration, applied to a current and two future scenarios, are shown: the fast response of PtG units allows definitely to improve the system performance, with a reduction of the RES effect up to ~90% in terms of time duration, and up to ~40% in terms of peak power, demonstrating the positive effect of this technology on the system operation. This computational framework and these encouraging results allow further investigations about the application of PtG in transmission networks, in particular about the optimal PtG units placement and sizing, their economical consequences on the market and their technical consequences on the network management.

Relators: Andrea Mazza, Ettore Francesco Bompard, Abouzar Estebsari
Academic year: 2018/19
Publication type: Electronic
Number of Pages: 99
Subjects:
Corso di laurea: Corso di laurea magistrale in Ingegneria Elettrica
Classe di laurea: New organization > Master science > LM-28 - ELECTRICAL ENGINEERING
Aziende collaboratrici: UNSPECIFIED
URI: http://webthesis.biblio.polito.it/id/eprint/9171
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