As global wind energy capacity continues to expand, the need to site commercial wind farms in productive, affordable, and technically feasible locations has become increasingly important. The use of wind farm site suitability models to identify these locations has grown consequently, thus increasing interest in standardizing certain aspects of these models' development. This systematic review of wind farm site suitability studies seeks to identify similarities and differences in the selection and representation of their enlisted siting factors. The review focuses on how subjective modeling decisions, such as vocabulary choices and dataset selection, occur in the literature, based on five identified themes: 1) Deciding Upon Siting Factors, which explains how a study's geographical context, selected modeling approach, and modeler decisions can influence siting factor selection; 2) Classifying Data and Siting Factor Terminology, which addresses the extent and the advantages of consistent siting factor vocabulary; 3) Implementing Siting Factors as Constraints or as Evaluation Criteria, which covers the importance of consistent implementation and of specifying logic when enlisting siting factors to assess potential wind farm sites; 4) Utilizing Primary and Secondary Data, which details how a study's reliance on external or self-collected datasets influences siting factor representation; and 5) Data Source and Accessibility, which highlights the inconsistent provision of citations and dataset sources, and the availability of datasets for siting factors to the broader scientific community. Standardizing the selection and representation of siting factors would benefit comparisons between wind farm site suitability studies and communication of model outputs to a wider audience.

The major challenge facing renewable energy systems in Nigeria is the lack of appropriate, affordable, and available meteorological stations that can accurately provide present and future trends in weather data and solar PV performance. It is crucial to find a solution to this because information on present and future solar PV performance is important to renewable energy investors so that they can assess the potential of renewable energy systems in various locations across the country. Although Nigerian weather provides favorable weather conditions for clean power generation, there is little penetration of renewable energy systems in the region, since over 95% of the power is fossil-fuel-generated. This is because there has been no detailed report showing the potential of clean power generation systems due to the dysfunctional meteorological stations in the country. This paper sought to fill this knowledge gap by providing a machine-learning-inspired forecasting of environmental weather parameters that can be used by manufacturing companies in evaluating the profitability of siting renewable energy systems in the region. Crucial weather parameters such as daily air temperature, relative humidity, atmospheric pressure, wind speed, and rainfall were obtained from NASA for a period of 19 years (viz. 2004–2022), resulting in the collection of 6664 high-resolution data points. These data were used to build diverse regressive neural networks with varying hyperparameters to find the best network arrangement. In summary, a low mean-squared error of 7 $\times$ 10⁻³ and high regression correlations of 96% were obtained during the training.

Fuel subsidies have been a central topic of discussion for decades in the Global South, including Nigeria, often implemented to enhance energy affordability for the population. However, on 29 May 2023, the President of Nigeria announced the elimination of the fuel subsidy, resulting in an increase in energy and electricity costs exceeding 300%. This resulted in widespread protests nationwide, significantly affecting all sectors, particularly enterprises. Thus, this study examines the impact of fuel subsidy removal on micro, small, and medium enterprises (MSMEs), as well as their level of awareness and correlation with willingness to transition to renewable energy technologies (RETs), utilizing original survey data from 1461 MSMEs across Nigeria. Results indicate that the removal of fuel subsidies impacted 90% of MSMEs surveyed. Regarding the willingness to transition to RETs, 77.2% of MSMEs expressed a positive inclination, whereas 11.7% were unwilling to undertake this transition. The willingness of MSMEs to transition is influenced by several factors, including state of residence, geographical area (settlement), level of education, enterprise category, the role of the respondents, energy type utilized by the enterprise, and the level of awareness of various RETs. The study’s findings enhance understanding of the factors influencing the adoption of RETs among MSMEs in Nigeria and the potential to inform strategies for sustainable energy development. Furthermore, the identification of specific factors influencing the transition decision provides valuable insights for targeted interventions and policymaking.

Renewable energy is central to climate strategies in Nigeria, yet the policy architecture guiding this transition continues to prioritise technical and economic metrics while giving limited attention to social and ecological safeguards. This paper conducts a structured qualitative content analysis of eight national renewable energy and energy transition policy documents to evaluate the extent to which energy justice principles are embedded in Nigeria’s transition framework. Using a theory-driven coding schema spanning procedural, recognitional, distributional, and reparative justice, each document was assessed across eighteen parameters using a five-point explicitness-enforceability scale distinguishing between provisions that are explicit and enforceable, explicit but non-enforceable, general but enforceable, general and non-enforceable, and not addressed. Findings show that justice considerations are widely referenced but unevenly operationalised across the instrument set. When scores are normalised against the maximum available within each dimension, procedural justice achieves the highest proportional integration at 53.4% of its possible maximum, followed by distributional justice at 50.5%, recognitional justice at 34.4%, and reparative justice at 26.0%. This rank order holds independently of differential parameter weighting and indicates that access-oriented and process-focused provisions are more consistently embedded than those addressing identity, historical harm, and compensatory obligation. Enforcement mechanisms, community feedback and grievance pathways, cultural safeguards, and compensation frameworks for historically affected communities are the most consistently absent or under-specified provisions across the corpus. The findings demonstrate that the barrier to stronger justice integration is not the absence of legal authority within Nigeria’s existing statutory architecture but the selective application of that authority to community-facing and reparative provisions. The paper provides a replicable analytical framework applicable to comparable fossil fuel-dependent, climate-vulnerable transition contexts beyond Nigeria.