Supporting Decarbonization Strategies of Local Energy Systems by De-Risking Investments in Renewables: A Case Study on Pantelleria Island

Novo, Riccardo; Minuto, Francesco Demetrio; Bracco, G.; Mattiazzo, Giuliana; Borchiellini, Romano; Lanzini, Andrea

doi:10.3390/en15031103

Cited by 13 publications

(4 citation statements)

References 42 publications

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“…On the other hand, D. Timmons et al [23] used OSeMOSYS to find the minimum cost renewable energy mix on the island of Mauritius, while Constantinos Taliotis et al [24] utilized OSeMOSYS to assess the impact of electric vehicle deployment on renewable electricity generation on the island of Cyprus. Moreover, Novo et al [25] used OSeMOSYS to explore a decarbonization path of Pantelleria Island by 2050, investigating different adoption trends of distributed photovoltaic systems and electric vehicles in the local population.…”

Section: Literature Reviewmentioning

confidence: 99%

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An Energy Cost Assessment of Future Energy Scenarios: A Case Study on San Pietro Island

et al. 2022

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The need for a clean and affordable energy supply is a major challenge of the current century. The tough shift toward a sustainable energy mix becomes even more problematic when facing realities that lack infrastructures and financing, such as small islands. Energy modeling and planning is crucial at this early stage of the ecological transition. For this reason, this article aims to improve an established long-run energy model framework, known as “OSeMOSYS,” with an add-on tool able to estimate different types of Levelized Cost Of Electricity (LCOE): a real and theoretical LCOE of each technology and a real and theoretical system LCOE. This tool fills a gap in most modeling frameworks characterized by a lack of information when evaluating energy costs and aims at guiding policymakers to the most appropriate solution. The model is then used to predict future energy scenarios for the island of San Pietro, in Sardinia, which was chosen as a case study. Four energy scenarios with a time horizon from 2020 to 2050—the Business-As-Usual (BAU) scenario, the Current Policy Projection (CPP) scenario, the Sustainable Growth (SG) scenario, and the Self-Sufficient-Renewable (SSR) scenario—are explored and ranked according to the efforts made in them to achieve an energy transition. Results demonstrates the validity of the tool, showing that, in the long run, the average LCOE of the system benefits from the installation of RES plants, passing from 49.1 €/MWh in 2050 in the BAU scenario to 48.8 €/MWh in the ambitious SG scenario. On the other hand, achieving carbon neutrality and the island’s energy independence brings the LCOE to 531.5 €/MWh, questioning the convenience of large storage infrastructures in San Pietro and opening up future work on the exploration of different storage systems.

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Section: Literature Reviewmentioning

confidence: 99%

“…ELC_GRID represents the island's power grid. Since no specific data was available, its efficiency is considered to be 90%, a medium value between the Sardinian grid efficiency [49] and the efficiency of Pantelleria's electricity network [25]. To ensure sufficient stability, VRES penetration must not exceed 80% of the total production.…”

Section: Scenario Settingsmentioning

confidence: 99%

An Energy Cost Assessment of Future Energy Scenarios: A Case Study on San Pietro Island

et al. 2022

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“…The third type includes isolated systems that do not have access to PHS and may rely on other types of ESSs. The Italian island of Pantelleria [16] is an example of this type of system. These isolated islands lack a submarine connection and rely heavily on ESS to increase the share of VRES.…”

Section: Introductionmentioning

confidence: 99%

Electricity, Transportation, and Water Provision of 100% Renewable Energy for Remote Areas

2023

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The integration of variable renewable energy sources in islands has become crucial in reducing their dependency on imported fossil fuels. This study aimed to assess the energy transition of an island towards a 100% renewable energy system for power generation, inland transport, and potable water provision. Linking various fossil-fuel-consuming sectors, such as transport and potable water supply systems, may strongly assist in reducing the possible mismatch between renewable energy source production and demand and contribute to fulfilling other system requirements. The use of energy storage technologies is vital and unlike traditional power systems; as the number of components in the system increases, their proper capacity needs to be accurately determined. This work employs a multi-objective optimization assessment using a modified NSGA-II algorithm to depict the energy transition for Porto Santo Island. To evaluate the solutions, we considered the main criteria of energy cost, avoided environmental impacts (CO2-equivalent emissions) of the proposed system, and loss of power supply. The Pareto front contains various solutions under different system configurations. Results indicate that full inland transport electrification (introducing 3000 EVs) can account for 18% of the avoided CO2 emissions of the island while sharing 28–40% of the up-front cost of the system, depending on the proposed system’s components. The EV’s costs incorporate subsidies and their battery replacement. Another interesting finding from the optimization process is that the solution with the highest avoided CO2 emissions involves keeping a diesel generator for supplying 4% of the island’s total demand and using an underwater compressed air energy storage with a capacity of 280 MWh. This suggests that adding more installed wind turbines or PV panels may not necessarily contribute to reducing the emissions of the entire system.

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“…Considering the selection criteria listed above, the Island of Pantelleria was selected as a case study, thanks to its properties of territorial diversity [59]; the numerous data sources at the regional [60], Italian [61], and European levels; [CLC]; the existence of other studies with the same focus [62,63]; and the presence of an established model instance (TEMOA-Pantelleria) [64]. Below, the main features of the island of Pantelleria and the TEMOA-Pantelleria model used for the analysis are described.…”

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Integration of Land Use Potential in Energy System Optimization Models at Regional Scale: The Pantelleria Island Case Study

Mosso,

Rajteri,

Savoldi

2024

Sustainability

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In the context of the energy transition, the integration of land use considerations into energy planning can provide significant improvements. In energy system optimization models (ESOMs), land use aspects can be integrated at the cost of a finer spatial resolution and a more detailed characterization of land, tailored to regional constraints and specificities. Additionally, an assessment of trade-offs with alternative land uses is necessary. Nevertheless, they are commonly neglected. This study addresses the challenge of incorporating land use aspects into ESOMs, with a focus on the unique context of Pantelleria Island. It aims to bridge the gap in methodologies for renewable energy potential assessment and model integration, considering the critical role of land pricing and availability. It combines geospatial data aggregation with model adaptation to include detailed land use aspects. The findings highlight the substantial impact of land costs on renewable energy planning, with land pricing significantly altering model outcomes. This research offers key insights for sustainable energy planning and underscores the importance of considering land use in energy transition strategies.

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Supporting Decarbonization Strategies of Local Energy Systems by De-Risking Investments in Renewables: A Case Study on Pantelleria Island

Cited by 13 publications

References 42 publications

An Energy Cost Assessment of Future Energy Scenarios: A Case Study on San Pietro Island

An Energy Cost Assessment of Future Energy Scenarios: A Case Study on San Pietro Island

Electricity, Transportation, and Water Provision of 100% Renewable Energy for Remote Areas

Integration of Land Use Potential in Energy System Optimization Models at Regional Scale: The Pantelleria Island Case Study

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