A Distributed Model Predictive Control approach for the integration of flexible loads, storage and renewables

Luca Ferrarini; Giancarlo Mantovani; Giuseppe Tommaso Costanzo

doi:10.1109/ISIE.2014.6864871

A Distributed Model Predictive Control approach for the integration of flexible loads, storage and renewables

Luca Ferrarini, Giancarlo Mantovani, Giuseppe Tommaso Costanzo

Polytechnic University of Milan

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Abstract

This paper presents an innovative solution based on distributed model predictive controllers to integrate the control and management of energy consumption, energy storage, PV and wind generation at customer side. The overall goal is to enable an advanced prosumer to autoproduce part of the energy he needs with renewable sources and, at the same time, to optimally exploit the thermal and electrical storages, to trade off its comfort requirements with different pricing schemes (including real-time pricing), and apply optimal control techniques rather than sub-optimal heuristics.

Original language	English
Title of host publication	IEEE International Symposium on Industrial Electronics
Publisher	IEEE
Publication date	2014
Pages	1700-1705
ISBN (Print)	978-1-4799-2399-1
DOIs	https://doi.org/10.1109/ISIE.2014.6864871
Publication status	Published - 2014
Event	2014 IEEE 23rd International Symposium on Industrial Electronics - Istanbul , Turkey Duration: 1 Jun 2014 → 4 Jun 2014 Conference number: 23 https://ieeexplore.ieee.org/xpl/conhome/6851787/proceeding

Conference

Conference	2014 IEEE 23rd International Symposium on Industrial Electronics
Number	23
Country/Territory	Turkey
City	Istanbul
Period	01/06/2014 → 04/06/2014
Internet address	https://ieeexplore.ieee.org/xpl/conhome/6851787/proceeding

Keywords

Smart Grids
Model Predictive Control
Smart Buildings
Renewable Energy Integration

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/ISIE.2014.6864871

Distributed MPC for smart micro grid V5 2014 04 01Submitted manuscript, 667 KB

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Cite this

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title = "A Distributed Model Predictive Control approach for the integration of flexible loads, storage and renewables",

abstract = "This paper presents an innovative solution based on distributed model predictive controllers to integrate the control and management of energy consumption, energy storage, PV and wind generation at customer side. The overall goal is to enable an advanced prosumer to autoproduce part of the energy he needs with renewable sources and, at the same time, to optimally exploit the thermal and electrical storages, to trade off its comfort requirements with different pricing schemes (including real-time pricing), and apply optimal control techniques rather than sub-optimal heuristics.",

keywords = "Smart Grids, Model Predictive Control, Smart Buildings, Renewable Energy Integration",

author = "Luca Ferrarini and Giancarlo Mantovani and Costanzo, {Giuseppe Tommaso}",

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publisher = "IEEE",

address = "United States",

note = "2014 IEEE 23rd International Symposium on Industrial Electronics, ISIE 2014 ; Conference date: 01-06-2014 Through 04-06-2014",

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}

Ferrarini, L, Mantovani, G & Costanzo, GT 2014, A Distributed Model Predictive Control approach for the integration of flexible loads, storage and renewables. in IEEE International Symposium on Industrial Electronics. IEEE, pp. 1700-1705, 2014 IEEE 23rd International Symposium on Industrial Electronics, Istanbul , Turkey, 01/06/2014. https://doi.org/10.1109/ISIE.2014.6864871

A Distributed Model Predictive Control approach for the integration of flexible loads, storage and renewables. / Ferrarini, Luca; Mantovani, Giancarlo; Costanzo, Giuseppe Tommaso.
IEEE International Symposium on Industrial Electronics. IEEE, 2014. p. 1700-1705.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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AB - This paper presents an innovative solution based on distributed model predictive controllers to integrate the control and management of energy consumption, energy storage, PV and wind generation at customer side. The overall goal is to enable an advanced prosumer to autoproduce part of the energy he needs with renewable sources and, at the same time, to optimally exploit the thermal and electrical storages, to trade off its comfort requirements with different pricing schemes (including real-time pricing), and apply optimal control techniques rather than sub-optimal heuristics.

KW - Smart Grids

KW - Model Predictive Control

KW - Smart Buildings

KW - Renewable Energy Integration

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A Distributed Model Predictive Control approach for the integration of flexible loads, storage and renewables

Abstract

Conference

Keywords

UN SDGs

Access to Document

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