Optimal planning of distributed energy resources for sustainable road tunnels under uncertainty

The problem of road tunnel energy consumption and sustainability is considered in this paper. To reduce energy costs and to improve sustainability, a Microgrid (MG) with distributed energy resources including renewable generators and storage systems is proposed to supply the typical loads of road tunnels. The proposed MG is modular in the sense that sets of individual modules for the solar and wind generators, as well as the batteries, are considered for the installation, while the number of modules is obtained from the resolution of a long-term planning optimization problem. A new optimal probabilistic approach that calculates the number of modules maximizing the Net Present Value (NPV) to evaluate the profitability of the MG investment is proposed. The proposed procedure includes an advanced long-term Markov Chain (MC) based methodology to generate scenarios of stochastic processes modeling all the uncertain variables involved in the planning procedure, satisfies technical and contractual constraints selectable by the tunnel owner, and implements the decision criteria most frequently applied for the selection of the optimal solution. In the numerical applications, the results obtained in different case studies show the benefits, the flexibility and the effectiveness of the proposed procedure. In fact, the modular solution allows the application of the proposed approach to a generic road tunnel located in any geographical area optimizing the use of the distributed resources.

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Publication Details

Journal
Sustainable Energy Grids and Networks
Published
2025-07-24
DOI
https://doi.org/10.1016/j.segan.2025.101832
Citations
2
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
1.46

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article

Optimal planning of distributed energy resources for sustainable road tunnels under uncertainty

Enrico Carpaneto, Antonio Bracale, Angela Russo, P. Caramia et al.
2 citations
Sustainable Energy Grids and Networks
Integrated Energy Systems Optimization
1.46
article

Optimal planning of distributed energy resources for sustainable road tunnels under uncertainty

Enrico Carpaneto, Antonio Bracale, Angela Russo, P. Caramia, Stefano d’Ambrosio, Pasquale De Falco, Sebastiano Nicotra
article en
2 citations

Abstract

The problem of road tunnel energy consumption and sustainability is considered in this paper. To reduce energy costs and to improve sustainability, a Microgrid (MG) with distributed energy resources including renewable generators and storage systems is proposed to supply the typical loads of road tunnels. The proposed MG is modular in the sense that sets of individual modules for the solar and wind generators, as well as the batteries, are considered for the installation, while the number of modules is obtained from the resolution of a long-term planning optimization problem. A new optimal probabilistic approach that calculates the number of modules maximizing the Net Present Value (NPV) to evaluate the profitability of the MG investment is proposed. The proposed procedure includes an advanced long-term Markov Chain (MC) based methodology to generate scenarios of stochastic processes modeling all the uncertain variables involved in the planning procedure, satisfies technical and contractual constraints selectable by the tunnel owner, and implements the decision criteria most frequently applied for the selection of the optimal solution. In the numerical applications, the results obtained in different case studies show the benefits, the flexibility and the effectiveness of the proposed procedure. In fact, the modular solution allows the application of the proposed approach to a generic road tunnel located in any geographical area optimizing the use of the distributed resources.

Sustainable Energy Grids and NetworksVol. 43
Politecnico di Torino (IT), Parthenope University of Naples (IT)
Università degli Studi di Napoli Parthenope, European Commission
Openalex Percentile: Top 16%
Integrated Energy Systems Optimization
1.46
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