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    Models and enabling IoT technologies for cooperative energy brokerage in smart-grid

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    PhDThesis.pdf (9.524Mb)
    Creato da
    Scarcello, Luigi
    Critelli, Salvatore
    Menniti, Daniele
    Pinnarelli, Anna
    Sorrentino, Nicola
    Metadata
    Mostra tutti i dati dell'item
    URI
    http://hdl.handle.net/10955/1785
    https://doi.org/10.13126/unical.it/dottorati/1785
    Descrizione

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    Ph.D. in Science and Engineering of Environment, Construction and Energy Ciclo XXXI; The strong decentralization of energy production, especially from nonprogrammable renewable sources (nPRS), obtained with the rising and interconnection of small plants, has placed the end user at the centre of the whole energy system management. Nowadays, the end user has taken the role of a “prosumer”, being at the same time producer and consumer of thermal and electrical energy. While this new bivalent role has clear advantages (onsite production, lower transport losses, reduced dependence on fossil fuels, etc.), the distributed generation from nPRS causes additional injections of energy into the grid, which can bring to stability and safety problems for the operations of the grid itself. As consequence, the end-user needs to be involved in the management of the grid adopting appropriate strategies in order to maintain the balance between generation and consumption of energy, and avoid spikes of energy demand or excessive injections of energy produced but not consumed. The best strategy is to join in energy communities able to coordinate local energy flows and favouring a better use of energy. Moreover, end-users have to adopt new IoT technologies and the grid have to become a smart-grid. This Ph.D. thesis develops some cooperative energy brokerage models based on decentralized scheme proposed in the LAboratory of Electrical Systems for Energies and Renewable sources (LASEER), headed by Prof. D. Menniti, of the Department of Mechanical, Energy and Management (DIMEG) of the University of Calabria. In the proposed models, the end-user takes a fundamental role: he can autonomously make decisions based on thermal and electrical energy requirements and collaborate in energy balancing operations of the energy community and of the national electrical grid. In according to this decentralized approach, a new price based-time of use Demand Response program has been designed. The Demand Response program is determined by solving, in a day ahead strategy, a mixed integer linear optimization problem, called “prosumer problem”. In this context, end-user dwellings need to be purposely equipped with home automation systems and micro-grid devices, appropriately designed to act the planned energy management strategy The effectiveness and the feasibility of the proposed work have been assessed through a testbed performed in an academic experimental demonstrator sited in the University of Calabria, where the proposed model have been implemented. Moreover, different prototype versions of home automation and micro-grids devices have been realized during the development and the work carried out in the MIUR project “Sistemi Domotici per il servizio di brokeraggio energetico cooperativo”. Specific contributions of this thesis are in the following areas:  implementing an unified management model of both thermal and electrical energy needs in a price based Demand Response program;  providing an option for end-users to participate in the National Electricity Market through demand side bidding and to manage their electricity usage;  designing home automation systems and micro-grid devices able to monitor, control and collect data on exchanges of electrical energy flows;  customizing cooperative energy brokerage model for supporting the management of Energy Districts;  experimenting the energy management strategy in the academic experimental demonstrator;  designing smart meter for end-user able to measure energy flows exchange as well as to give a view of real-time energy consumption;  collecting representative data about end-user habits to perform statistical analysis and define load forecasting services;  evaluating cost and quantifying the global energy demand to sensitize to more conscious consumption of energy. The experience in developing demand response models has been shared inside Marie Skłodowska-Curie project “Research and Innovation Staff Exchange”, with the project partner Exergy Ltd company.; Università della Calabria
    Soggetto
    Energy conservation; Smart grid
    Relazione
    ING-IND/33;

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