logo SBA

ETD

Archivio digitale delle tesi discusse presso l’Università di Pisa

Tesi etd-02032020-170255


Tipo di tesi
Tesi di laurea magistrale
Autore
LAVEGLIA, ANTONIO
URN
etd-02032020-170255
Titolo
Peer-to-peer trading and load flexibility solutions impact assessment on a residential micro-grid via convex optimization models
Dipartimento
INGEGNERIA DELL'ENERGIA, DEI SISTEMI, DEL TERRITORIO E DELLE COSTRUZIONI
Corso di studi
INGEGNERIA ENERGETICA
Relatori
relatore Prof. Desideri, Umberto
correlatore Prof. Contreras Sanz, Javier
correlatore Dott. Bischi, Aldo
Parole chiave
  • Convex Optimization
  • Cooperative Game Theory
  • Distributed energy resources
  • Hybrid heating system
  • Micro-grid
  • Multi-modal energy systems
  • Peer-to-peer trading
  • Shapley Value
Data inizio appello
27/02/2020
Consultabilità
Non consultabile
Data di rilascio
27/02/2060
Riassunto
Renewable Energy Sources share will continuously increase in the world energy mix jointly with the electrification of heating and mobility sector in order to reach the ambitious decarbonisation targets set by the international agreements. In this way the distributed and uncertain nature of the RES will change the structure of the electric system leading towards a new configuration made of interconnected electric micro-grids which ideally should consume locally an increasingly large share of the electric energy produced by distributed RES such as photovoltaic. New market models as well as technological solutions will be needed to tackle such challenges. On the market model side, the Peer-to-Peer (P2P) electricity trading seems to be one of the more promising solutions because allows exchanging the excess of electric energy among neighbours fulfilling locally the demands without provoking unbalances at the distribution grid. On the technology side, the more promising options are the distributed electric energy storage solutions and the electrification of thermal requests, leveraging upon the opportunity the thermal inertia offers to differ the electricity consumption. In the thesis a local electric market model has been developed in Julia programming language; it is based on state-of-the-art convex optimization methodologies in order to identify the optimal electric energy flows and suitable prices for the whole local community welfare maximization. Extensive sensitivity analysis has been performed to study the impact of the abovementioned solutions, namely the P2P, the electric energy storage deployment at each user, and the electrification of thermal consumption which includes a simplified model of the buildings and domestic hot water tank; all the solutions have been benchmarked against a base case represented by current scenario with electric grid and gas fired heating and against these ones proposed and results have been analysed and discussed in terms of cost savings and local consumption of renewable energy, for increasing size of installed PV power as well as the different heating solutions. Among the more remarkable results, the role of the thermal consumptions electrification could be highlighted; it increases the cost savings by 23%, local renewable energy consumed by 67% and amplifies the impact of the peer-to-peer trading platform by three times. In addition, a cooperative game theory has been applied to find the “fair” costs allocation among users and the relative P2P transactions prices and scalability tests has been performed to ensure the deployment of such model to tens of users.
File