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Renewable energy infrastructure is an important asset class in the context of reducing global carbon emissions going forward. This includes solar power, wind farms, hydro, battery storage and hydrogen. This paper examines the risk-adjusted performance and diversification benefits of listed renewable energy infrastructure globally over Q1:2009–Q4:2022 to examine the role of renewable energy infrastructure in a global infrastructure portfolio and in a global mixed-asset portfolio. The performance of renewable energy infrastructure is compared with the other major infrastructure sectors and other major asset classes. The strategic investment implications for institutional investors and renewable energy infrastructure in their portfolios going forward are also highlighted. This includes identifying effective pathways for renewable energy infrastructure exposure by institutional investors.

Using quarterly total returns, the risk-adjusted performance and portfolio diversification benefits of global listed renewable energy infrastructure over Q1:2009–Q4:2022 is assessed. Asset allocation diagrams are used to assess the role of renewable energy infrastructure in a global infrastructure portfolio and in a global mixed-asset portfolio.

Listed renewable energy infrastructure was seen to underperform the other infrastructure sectors and other major asset classes over 2009–2022. While delivering portfolio diversification benefits, no renewable energy infrastructure was seen in the optimal infrastructure portfolio or mixed-asset portfolio. More impressive performance characteristics were seen by nonlisted infrastructure funds over this period. Practical reasons for these results are provided as well as effective pathways going forward are identified for the fuller inclusion of renewable energy infrastructure in institutional investor portfolios.

Institutional investors have an important role in supporting reduced global carbon emissions via their investment mandates and asset allocations. Renewable energy infrastructure will be a key asset to assist in the delivery of this important agenda for a greener economy and addressing global warming. Based on this performance analysis, effective pathways are identified for institutional investors of different size assets under management (AUM) to access renewable energy infrastructure. This will see institutional investors embracing critical investment issues as well as environmental and social issues in their investment strategies going forward.

This paper is the first published empirical research analysis on the performance of renewable energy infrastructure at a global level. This research enables empirically validated, more informed and practical decision-making by institutional investors in the renewable energy infrastructure space. The ultimate aim of this paper is to articulate the potential strategic role of renewable energy infrastructure as an important infrastructure sector in the institutional real asset investment space and to identify effective pathways to achieve this renewable energy infrastructure exposure, as institutional investors focus on the strategic issues in reducing global carbon emissions in the context of increased global warming.

The social acceptance of wind energy is increasingly conditioning the Italian Government and regions to authorize the construction of these plants. The proposal of offshore wind farm in the south-west of Sardinia has raised many perplexities both from the marine environmental point of view and from concern about increasing the electricity production in a region that already exports electricity to the peninsula. The purpose of this study is to evaluate what are the factors that most affect the coastal residents’ acceptability of an offshore wind farm.

The data is based on a Sardinia-wide in-person survey with about 512 participants in the period between May and June 2023. Respondents were selected randomly from five different locations in Carloforte region. Multiple regression analysis investigates the factors that influenced acceptability to construction and development of offshore wind power plant. Four independent variables were selected in the regression models such as (i) interest towards wind energy, (ii) attitude towards renewable energy production, (iii) perceived regional energy policy and (iv) attitude towards offshore wind farm. The dependent variables are the rates of coastal local residents’ acceptance of offshore wind farm for respondents in five coastal towns.

Fishermen and summer tourism operators’ respondents expressed significant reluctance to accept the new project because they perceive a strong risk of environmental impact on both tuna fishing and marine recreational activities in the vicinity. The distance between the turbines at sea and local residents along the coast and surrounding small islands does not have an influence to accept wind energy. The energy policy of the Region of Sardinia, which is perceived by respondents as an expansive energy policy in the production of electricity that exceeds their needs, not being accompanied by a scenario of reducing that from fossil fuels, is the variable that led about 70% of respondents to express a negative opinion towards this project.

A potential problem associated with the survey is that local response produced sample selection bias. The proportion of respondents with secondary education and no school certificate is quite high. It is possible that respondents who provided valid questionnaires were more low-educated and therefore, the sample may be biased towards lower-educated people. While this does not invalidate the results of this study, it is important to note that the sample was on average less educated than the overall population in Italy. In addition, people with lower incomes were more likely to complete the questionnaires; the results are more representative of a portion of the population with incomes below the national average.

Results showed how coastal communities are in favour of wind energy within their island, but not within a marine protected area that is considered unique for its beauty and marine ecosystem. Wind energy developers should, before submitting a proposal for an offshore wind farm project, consider among other things the long approval time and understand the activities carried out by local communities and their attachment to those places. Politicians and developers should develop a coherent energy transition policy based on a long-term vision of zero emissions, because according to the findings of this study, it was the regional energy policy that is the most controversial reason for residents to reject the project.

The contribution of this study is to fill a part of the research gap linking to ongoing energy transitions. In particular, this study analysed for the first time in Italy the acceptability level of an offshore renewable energy project considering the environmental implications and risks in the fragile marine ecosystem of Carloforte waters. This study also made it possible to analyse the impact of the regional energy policy on the acceptability of residents towards the development of offshore wind farms, which is scarcely discussed in the literature.

This study aims to improve the offshore wind farm (OWF) site selection evaluation index system and establishes a decision-making model for OWF site selection. It is expected to provide helpful references for the progress of offshore wind power.

Firstly, this paper establishes an evaluation criteria system for OWF site selection, considering six criteria (wind resource, environment, economic, technical, social and risk) and related subcriteria. Then, the Criteria Importance Though Intercrieria Correlation (CRITIC) method is introduced to figure out the weights of evaluation indexes. In addition, the cumulative prospect theory and technique for order preference by similarity to an ideal solution (CPT-TOPSIS) method are employed to construct the OWF site selection decision-making model. Finally, taking the OWF site selection in China as an example, the effectiveness and robustness of the framework are verified by sensitivity analysis and comparative analysis.

This study establishes the OWF site selection evaluation system and constructs a decision-making model under the spherical fuzzy environment. A case of China is employed to verify the effectiveness and feasibility of the model.

In this paper, a new decision-making model is proposed for the first time, considering the ambiguity and uncertainty of information and the risk attitudes of decision-makers (DMs) in the decision-making process.