PORTALE DELLA DIDATTICA

Ricerca CERCA
  KEYWORD

Power System Group

An agent-based model of a Smart Grid: optimisation of Renewable Energy Sources taking into account grid constraints

Parole chiave AGENT BASED SIMULATION, GAME THEORY, E, DEMAND SIDE MANAGEMENT, ICT, SMAR CITY, SMART CITIES, SMART GRID

Riferimenti LORENZO BOTTACCIOLI, EDOARDO PATTI, ENRICO PONS

Gruppi di ricerca DAUIN - GR-06 - ELECTRONIC DESIGN AUTOMATION - EDA, ELECTRONIC DESIGN AUTOMATION - EDA, Energy Center Lab, GR-06 - ELECTRONIC DESIGN AUTOMATION - EDA, GUSEE, ICT4SS - ICT FOR SMART SOCIETIES, Power System Group

Tipo tesi SPERIMENTALE

Descrizione One of the main objectives of the Energy Center LAB initiative consists on designing a Multi-Energy-System (MES) Co-Simulation Platform able to qualitatively and quantitatively solve energetic transition scenarios [1].
Concepts such as Demand Response, Energy Aggregation, Demand Side Management are becoming popular and realistic in a Smart-cities and Smart grid scenario. Residential Demand-Side Management mechanisms (DSM) introduce the need for studying customer response to different DSM programs. Indeed, understand what could affect the user willingness to participate in these programs is crucial to obtain substantial benefits.
Few studies include the distribution power flow in the load management problem. However, to deal with the real world it is fundamental to consider the power flow equations. Their presence could complicate the formulation of the optimisation problem. Thus, proper methods should be adopted. This thesis focuses on the development of an Agent-based model (i.e. market agent, DSO agent, prosumers agent,..) on a real bus (i.e. Torino) taking into account RES and residential loads. Operational research techniques or other methods could be applied for the optimization of cost in the context of the smart grid.

[1] P. Mancarella. MES (Multi-Energy Systems): An overview of concepts and evaluation models. Energy, 65:1–17, 2014.


Scadenza validita proposta 07/02/2025      PROPONI LA TUA CANDIDATURA