Smart multi-carrier energy system: Optimised energy management and investment analysis

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4 Citazioni (Scopus)

Abstract

This paper proposes an optimised Energy Management System for a multi-carrier hub, which integrates two energy distribution networks, for hydrogen and electricity. The economic sustainability of a real-life instantiation of such a system has been analysed as well. The Energy Management System has been developed by means of a multi-objective optimisation algorithm, the Non-dominated Sorting Genetic Algorithm II, implemented using MATLAB®. The achieved results consist in a series of set-points defining the working conditions of the plant for a chosen time horizon. Data provided by this process also show the effectiveness of the adopted optimisation approach. The financial analysis is performed taking into account costs and revenues of a real demonstration plant. These cash flows have been evaluated by means of Net Present Value index. The proposed analysis shows a possible solution that is profitable for stakeholders and guarantees a short Pay Back Time
Lingua originaleEnglish
Stato di pubblicazionePublished - 2016

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Energy management systems
Sorting
Electric power distribution
MATLAB
Sustainable development
Electricity
Hydrogen
Economics
Costs

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Electrical and Electronic Engineering
  • Energy Engineering and Power Technology

Cita questo

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title = "Smart multi-carrier energy system: Optimised energy management and investment analysis",
abstract = "This paper proposes an optimised Energy Management System for a multi-carrier hub, which integrates two energy distribution networks, for hydrogen and electricity. The economic sustainability of a real-life instantiation of such a system has been analysed as well. The Energy Management System has been developed by means of a multi-objective optimisation algorithm, the Non-dominated Sorting Genetic Algorithm II, implemented using MATLAB{\circledR}. The achieved results consist in a series of set-points defining the working conditions of the plant for a chosen time horizon. Data provided by this process also show the effectiveness of the adopted optimisation approach. The financial analysis is performed taking into account costs and revenues of a real demonstration plant. These cash flows have been evaluated by means of Net Present Value index. The proposed analysis shows a possible solution that is profitable for stakeholders and guarantees a short Pay Back Time",
author = "Ippolito, {Mariano Giuseppe} and {Riva Sanseverino}, Eleonora and Giuseppe Patern{\`o}",
year = "2016",
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TY - CONF

T1 - Smart multi-carrier energy system: Optimised energy management and investment analysis

AU - Ippolito, Mariano Giuseppe

AU - Riva Sanseverino, Eleonora

AU - Paternò, Giuseppe

PY - 2016

Y1 - 2016

N2 - This paper proposes an optimised Energy Management System for a multi-carrier hub, which integrates two energy distribution networks, for hydrogen and electricity. The economic sustainability of a real-life instantiation of such a system has been analysed as well. The Energy Management System has been developed by means of a multi-objective optimisation algorithm, the Non-dominated Sorting Genetic Algorithm II, implemented using MATLAB®. The achieved results consist in a series of set-points defining the working conditions of the plant for a chosen time horizon. Data provided by this process also show the effectiveness of the adopted optimisation approach. The financial analysis is performed taking into account costs and revenues of a real demonstration plant. These cash flows have been evaluated by means of Net Present Value index. The proposed analysis shows a possible solution that is profitable for stakeholders and guarantees a short Pay Back Time

AB - This paper proposes an optimised Energy Management System for a multi-carrier hub, which integrates two energy distribution networks, for hydrogen and electricity. The economic sustainability of a real-life instantiation of such a system has been analysed as well. The Energy Management System has been developed by means of a multi-objective optimisation algorithm, the Non-dominated Sorting Genetic Algorithm II, implemented using MATLAB®. The achieved results consist in a series of set-points defining the working conditions of the plant for a chosen time horizon. Data provided by this process also show the effectiveness of the adopted optimisation approach. The financial analysis is performed taking into account costs and revenues of a real demonstration plant. These cash flows have been evaluated by means of Net Present Value index. The proposed analysis shows a possible solution that is profitable for stakeholders and guarantees a short Pay Back Time

UR - http://hdl.handle.net/10447/193230

UR - https://ieeexplore.ieee.org/document/7513926?arnumber=7513926

M3 - Paper

ER -