Microgrids are the advanced trend of power networks for the future energy management to have reliable and energy efficient systems. Renewable energy sources, battery storages and consumers are the main components of microgrids with their own limitations that should be taken into account to handle the energy flow in an optimal operation. This dissertation addresses the problem of energy management in a typical microgrid with the main targets of minimizing the cost of whole system and consumers and also maximizing the benefit of the microgrid in selling/buying electricity to/from the utility grid regarding the market price, while preserving users’ comfort. The main contribution of this research is to provide a comprehensive framework, based on a distributed Model Predictive Control (MPC), to minimize/maximize the cost/benefit of the microgrid and also provide a mechanism that makes each consumer be involved in a decision making procedure which is beneficial for both the microgrid and consumers. To reach this goal, the microgrid is divided into two layers and form a quasi-hierarchical control. The high-level microgrid layer is responsible of controlling the battery and energy exchange between the microgrid and utility grid by receiving the load and renewable energy prediction while the low-level microgrid layer deals with consumers and how they respond to the request from the high-level microgrid layer through a consensus-based approach. The optimization problems of the layers are formulated as mixed integer quadratic programing (MIQP) and quadratic programing (QP) and in this research we use MATLAB to solve them to find the optimal solutions. Finally, both simulation and experimental results show the accuracy and economic advantages of the proposed method.
Le microgrid sono il trend più avanzato per la futura gestione energetica di reti di distribuzione dell'energia per avere sistemi affidabili ed efficienti. Fonti di energia rinnovabili, sistemi di stoccaggio di energia elettrica e consumatori sono i componenti principali delle microgrid. Le limitazioni imposte da questi componenti devono essere tenute in considerazione per gestire il flusso di energia durante il funzionamento ottimale. Questo lavoro di tesi affronta il problema della gestione dell'energia di una tipica microgrid. I principali obiettivi discussi sono la minimizzazione del costo del sistema complessivo e dei consumatori, la massimizzazione dei benefici nella vendita (e acquisto) di energia elettrica da (e verso) la rete di distribuzione considerando il prezzo di mercato. Si deve inoltre mantenere il comfort degli utenti. Il principale contributo di questa ricerca è quello di rendere disponibile uno strumento completo basato su controllo distribuito e su un modello predittivo (MPC) che minimizzi i costi (e massimizzi i benefici) e inoltre fornisca un meccanismo di coinvolgimento del consumatore in una procedura decisionale vantaggiosa. Per raggiungere questo obiettivo, il sistema è diviso in due layer che formano un controllo quasi-gerarchico. Il layer di livello superiore è responsabile del controllo della batteria e dello scambio di energia tra microgrid e rete di distribuzione ricevendo i valori dei carichi e le previsioni della produzione di energia rinnovabile. Il layer inferiore si interfaccia con i consumatori e gestisce le richieste dal livello superiore tramite un approccio consensus-based. I problemi di ottimizzazione dei due livelli sono formulati come problemi MIQP (Mixed Integer Quadratic Programming) e QP (Quadratic programming). In questo lavoro è stato utilizzato MATLAB per trovare le soluzioni ottimali. Una serie di attività di simulazione e di attività sperimentali mostrano l'accuratezza e i vantaggi economici dell metodo proposto.
Microgrids energy management with a consensus-based distributed and hierarchical MPC approach
DEHGHANI PILEHVARANI, ALIREZA
2016/2017
Abstract
Microgrids are the advanced trend of power networks for the future energy management to have reliable and energy efficient systems. Renewable energy sources, battery storages and consumers are the main components of microgrids with their own limitations that should be taken into account to handle the energy flow in an optimal operation. This dissertation addresses the problem of energy management in a typical microgrid with the main targets of minimizing the cost of whole system and consumers and also maximizing the benefit of the microgrid in selling/buying electricity to/from the utility grid regarding the market price, while preserving users’ comfort. The main contribution of this research is to provide a comprehensive framework, based on a distributed Model Predictive Control (MPC), to minimize/maximize the cost/benefit of the microgrid and also provide a mechanism that makes each consumer be involved in a decision making procedure which is beneficial for both the microgrid and consumers. To reach this goal, the microgrid is divided into two layers and form a quasi-hierarchical control. The high-level microgrid layer is responsible of controlling the battery and energy exchange between the microgrid and utility grid by receiving the load and renewable energy prediction while the low-level microgrid layer deals with consumers and how they respond to the request from the high-level microgrid layer through a consensus-based approach. The optimization problems of the layers are formulated as mixed integer quadratic programing (MIQP) and quadratic programing (QP) and in this research we use MATLAB to solve them to find the optimal solutions. Finally, both simulation and experimental results show the accuracy and economic advantages of the proposed method.File | Dimensione | Formato | |
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Thesis Report- Alireza Dehghani.pdf
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https://hdl.handle.net/10589/136001