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Solar photovoltaic energy is the fastest growing renewable energy in South Africa, and deployment at public universities is critical in order to meet the high energy demand on campuses in a more sustainable manner. To promote and support deployment, it is necessary to know the factors that drive adoption of the technology. Thus, the aim of this study was to identify the factors which engender deployment of photovoltaic energy in public universities in South Africa.

Through an extensive literature review, the factors which drive photovoltaic energy deployment were identified and a three round Delphi survey was conducted for panellists to rate the drivers. The data were analysed using SPSS Version 27, and the mean and inter-quartile range values were used to identify the significant drivers within the public university sector.

The findings suggested that the deployment of photovoltaic energy is engendered by the direct and indirect benefits, social influences and the relative advantage of photovoltaic energy usage. For instance, universities install photovoltaic energy because of the financial gains that are made through reduction of energy cost. The deployment is also motivated by the reduction of energy-related greenhouse gases, enhancement of university sustainability performance, and the contribution to the Sustainable Development Goals.

A significant contribution to the body of knowledge regarding the drivers of photovoltaic energy deployment has been made in the paper from the perspective of a public university. The contribution fills the knowledge gap in South Africa by contributing valuable information to enable decision-makers to gain better understanding of the key issues that call for more attention in promoting and supporting photovoltaic energy deployment in the sector.

This paper addresses the current lack of solar photovoltaic (PV) adoption by Australian apartment dwellers by proposing a conceptual model that identifies and integrates the factors influencing owners' attitudes towards PV adoption.

The conceptual model, which this paper terms the apartment-based solar adoption (ASA) model, is developed by applying motivation–opportunity–ability (MOA) theory to relevant findings in property development, green energy and strata governance literature.

The ASA model demonstrates the process by which an apartment-owning consumer may progress from considering solar PV adoption to recommending the action to their strata property's Owners' Committee (OC). It incorporates three motivational drivers (pragmatic considerations, perceived values and perceived social norms), three conditional mediators (location accessibility, resource availability and decision-making conditions) and three requirements from the consumer (actual and perceived knowledge, the ability to participate in decision-making and social connections and status).

This article contributes originality to research on two counts. Firstly, it provides a conceptual framework of specific relevance to issues concerning solar PV adoption, and secondly, it offers a systematic means for research into strata governance decision-making. Further research is required to develop the means with which to utilise the model prescriptively and measure longitudinal effects, such as ongoing trends in apartment owners' motivations. Further research is also recommended into how the ASA model may be utilised to identify generalisable consumer typologies among apartment owners.

The ASA model may assist building maintenance providers in developing and marketing solar PV services tailored to apartment residents' requirements and enhance strata managers' ability to inform and guide apartment owners. In turn, property developers would be able to review apartment-based solar projects, measure their increased value and decreased energy costs and incorporate this information when planning future developments.

The ASA model may provide a template for apartment owners and owners' corporations considering solar PV for their property. Public policymakers could also refer to the model to incentivise apartment-based solar PV adoption, whether through designing local information campaigns, developing financial incentives or mitigating identified regulatory barriers. By facilitating solar PV adoption in Australian apartment housing, the model may ensure sustainable post-carbon energy consumption for Australia's housing stock and act as an example for high-density housing development internationally.

The ASA model addresses the many drivers and barriers known to affect solar PV adoption by apartment owners, presenting a framework on which to arrange these factors and outline their causal relationships. This framework may inform strata properties' future solar PV adoption initiatives by incorporating their specific physical characteristics, stakeholder dynamics and institutional structure. It also consolidates and provides generalisability to the concepts established in current literature.

The adoption of solar energy by households is an important avenue of protecting the environment and enabling energy access in rural areas, especially in developing countries like Uganda, where energy access is low. Therefore, this study aims to investigate the factors that influence the households’ willingness to adopt solar photovoltaic (PV) energy and how soon the households are willing to adopt solar PV energy for business use in Uganda.

Heckman’s two-step selection model was used to determine the willingness and urgency of adopting solar PV energy for business use in selected districts in Eastern Uganda. The respondents were selected purposively at the household level at a given point in time.

Results show that sex, household head estimated income, mode of acquisition and repayment terms of solar technology positively influence both willingness and urgency to adopt solar energy for business use in households. However, financial disclosure only influences willingness to adopt solar. Then, age and energy need only significantly influence how soon the household is willing to adopt solar PV energy for business use.

This study’s findings essentially apply to the individual factors that determine the willingness and urgency to adopt solar PV energy for business use by households. Hence, further research is needed to understand the external and industrial factors which could strengthen the predictive potential of the elements in this study.

This study underscores the need for regulatory enforcement on the supply and usage of quality, reliable and affordable solar equipment which are suitable for business use. Also, the need to promote and finance the usage of solar PV as a green energy source for household businesses has been emphasized.

The study simultaneously examines the willingness and urgency to adopt solar PV energy for household business purposes using Heckman’s two-step selection model. This has hitherto remained unknown empirically.

This paper aims to explore the process of implementing solar photovoltaic (PV) systems in construction to contribute to the understanding of systemic innovation in construction.

The exploratory research presented is based on qualitative data collected in workshops and interviews with 76 construction- and solar-industry actors experienced in solar PV projects. Actor-specific barriers were identified and analysed using an abductive approach.

In light of established definitions of systemic innovation, the process of implementing solar PV systems in construction involves challenges regarding technical and material issues, competencies, and informal and formal institutions. The specificities of this case highlight the necessity of paying attention to details in the process and to develop knowledge of systemic innovation in construction since the industry’s involvement in addressing societal challenges related to the energy transition will require implementing such innovations much more in the future.

New knowledge of solar PV systems as an innovation in professional construction is collected, enabling the adaptation of management strategies for its implementation. This knowledge can also be applied generally to other challenges encountered in highly systemic innovation implementation. Solar industry actors can gain an understanding of solar-specific challenges for the construction industry, challenges for which they must adapt their activities.

The exploration of actor-specific experiences of solar PV projects has resulted in a novel understanding of this specific innovation and its implementation. The findings illustrate a case of a high level of systemic innovation and the need to use a finer-grained scale for classification when studying innovation in construction.

The energy generation process through photovoltaic (PV) panels is contingent upon uncontrollable variables such as wind patterns, cloud cover, temperatures, solar irradiance intensity and duration of exposure. Fluctuations in these variables can lead to interruptions in power generation and losses in output. This study aims to establish a measurement setup that enables monitoring, tracking and prediction of the generated energy in a PV energy system to ensure overall system security and stability. Toward this goal, data pertaining to the PV energy system is measured and recorded in real-time independently of location. Subsequently, the recorded data is used for power prediction.

Data obtained from the experimental setup include voltage and current values of the PV panel, battery and load; temperature readings of the solar panel surface, environment and the battery; and measurements of humidity, pressure and radiation values in the panel’s environment. These data were monitored and recorded in real-time through a computer interface and mobile interface enabling remote access. For prediction purposes, machine learning methods, including the gradient boosting regressor (GBR), support vector machine (SVM) and k-nearest neighbors (k-NN) algorithms, have been selected. The resulting outputs have been interpreted through graphical representations. For the numerical interpretation of the obtained predictive data, performance measurement criteria such as mean absolute error (MAE), mean squared error (MSE), root mean squared error (RMSE) and R-squared (R²) have been used.

It has been determined that the most successful prediction model is k-NN, whereas the prediction model with the lowest performance is SVM. According to the accuracy performance comparison conducted on the test data, k-NN exhibits the highest accuracy rate of 82%, whereas the accuracy rate for the GBR algorithm is 80%, and the accuracy rate for the SVM algorithm is 72%.

The experimental setup used in this study, including the measurement and monitoring apparatus, has been specifically designed for this research. The system is capable of remote monitoring both through a computer interface and a custom-developed mobile application. Measurements were conducted on the Karabük University campus, thereby revealing the energy potential of the Karabük province. This system serves as an exemplary study and can be deployed to any desired location for remote monitoring. Numerous methods and techniques exist for power prediction. In this study, contemporary machine learning techniques, which are pertinent to power prediction, have been used, and their performances are presented comparatively.

The purpose of this paper is to examine the feasibility and design of zero-energy buildings (ZEBs) in cold and semi-arid climates. In this study, to maximize the use of renewable energy, energy consumption is diminished using passive solar architecture systems and techniques.

The case study is a residential building with a floor area of 100 m² and four inhabitants in the cold and semi-arid climate, northeast of Iran. For thermal simulation, the climate data such as air temperature, sunshine hours, wind, precipitation and hourly sunlight, are provided from the meteorological station and weather databases of the region. DesignBuilder software is applied for simulation and dynamic analysis of the building, as well as PVsyst software to design and evaluate renewable energy performance.

The simulation results show a 30% decrease in annual energy consumption of the building by complying with the principles of passive design (optimal selection of direction, Trombe wall, shade, proper insulation selection) from 25,443 kWh to 17,767 kWh. Then, the solar energy photovoltaic (PV) system is designed using PVsyst software, taking into account the annual energy requirement and the system’s annual energy yield is estimated to be 26,291 kWh.

The adaptive comparison of the values obtained from the energy analysis indicated that constructing a ZEB is feasible in cold and semi-arid conditions and is considered an effective step to achieve sustainable and environmentally friendly construction.

The reliability prediction is among the most important objectives for achieving overall system performance, and this prediction carried out by anticipating system performance degradation. In this context, the purpose of this research paper is to development of methodology for the photovoltaic (PV) modules' reliability prediction taking into account their future operating context.

The proposed methodology is framed by dependability methods, in this regard, two methods of dysfunctional analysis were used, the Failure Mode and Effects Criticality Analysis (FMECA) method is carried out for identification of the degradation modes, and the Fault Tree Analysis (FTA) method is used for identification the causes of PV modules degradation and the parameters influencing its degradation. Then, based on these parameters, accelerated tests have been used to predict the reliability of PV modules.

The application of the proposed methodology on PWX 500 PV modules' in different regions of Algeria makes it possible to predict its reliability, taking into account the future constraints on its operation. In this case, the temperature and relative humidity vary from one region to another was chosen as constraints. The results obtained from the different regions confirms the reliability provided by the designer of the Saharan cities Biskra, In Salah, Tamanraset, and affirms this value for the two Mediterranean cities of Oran and Algiers.

The proposed methodology is developed for the reliability prediction of the PV modules taking into account their future operating context and, the choice of different regions confirms or disproves the reliability provided by the designer of the PV modules studied. This application confirms their performance within the framework of the reliability prediction.

This study aims to investigate the relationship between government subsidies, R&D expenditures and overcapacity, and to explore the heterogeneity effects in different time periods and different types of companies. It can provide theoretical and practical guidance for the development of the photovoltaic industry.

This paper constructs a mediation model to explore the impact of government subsidies on overcapacity and on R&D expenditures, and to propose an indirect way to disentangle the impact of government subsidies on the creation of overcapacity from the positive aspect of increased R&D expenditures. A total of 94 listed enterprises in the Chinese photovoltaic industry were selected as the sample over the period 2012–2019.

There was significant overcapacity in the photovoltaic industry. Government subsidies had a positive effect in promoting overcapacity and R&D expenditures. The influence of government subsidies on excess capacity increased and on R&D expenditures decreased over time. Compared with large enterprises, government subsidies the small enterprises received had a greater positive impact on the overcapacity and a smaller positive impact on R&D expenditure. R&D expenditures restrained the influence of government subsidies on overcapacity, but the suppression effect was limited and decreased over time. The indirect effect in small enterprises was greater than that of large enterprises.

This paper studied government subsidies, R&D expenditure and overcapacity in the same framework and used bias-corrected bootstrapping to explore the path of “government subsidies–R&D expenditures–overcapacity”. The heterogeneous effects in different periods and different types of firms are discussed.

This paper aims to evaluate the hypothetical situation in a resembling airport to Esenboga Airport and analyzes the condition of all ground support equipment (GSE) equipment to be supplied by electricity produced by solar panels mounted on the rooftop of the terminal building. The case is discussed using environmental emissions and economic feasibility. The results of the resembling case can be generalized to all airports for the reduction of emissions caused by ground operations of aviation.

GSE fleet data which has been prepared by TGS operated in the Esenboğa Airport have been used to calculate emissions, and equivalent electricity consumption. A hypothetical solar panel construction on the rooftop of the terminal building and also the electricity production case was analyzed. Based on the calculations, both fuel and electricity use cases are compared by means of emissions and production costs using real data.

The electricity production and transmission pose a high value of emissions. Thus, electrification of GSE in the airport need a new approach such as producing the electric energy in the site. This research analyzes the case that the electricity is produced on the rooftop of terminal building and consumed by the GSE fleet. The authors discussed that it is both feasible and possible to electrify all the GSE except a shortage of two cold months with high fuel demand by using electric storage options.

Ground handling is performed by using GSE which is historically powered by diesel and such internal combustion engines which are well known for their high emission rates. As most of the airports reside in populated areas, GSE emissions need to be evaluated for reduction. However the electric energy could be an alternative for GSE emissions reduction

Aviation is a system of many subsystems in which the performance of each unit plays a crucial role in the final success of the system. Concerns on environmental protection make the aviation industry focus on reducing emissions produced during operations. Although aircraft emissions are widely discussed in the literature, ground handling systems which are an integral part of the whole aviation system, also need to be studied regarding the environmental issues. Besides, the European Union has set out targets of reducing emissions at the airports during ground operations to zero. This paper discusses the possibility of the target by comparing various scenarios