Search results

This study aims to examine the determinants of adoption intention toward the rooftop solar photovoltaic (RSPV) systems among residents of peri-urban villages of Gurugram, Haryana, India. This study also analyzes the impact of the adoption of RSPV systems on carbon neutrality from a behavioral perspective.

Data was collected using a self-administrated structured questionnaire from 208 male villagers (195 usable) of 22 villages using the purposive sampling technique.

Results revealed that relative advantage, followed by simplicity, trialability, observability and compatibility, positively and significantly impact villagers’ attitude toward adopting RSPV systems in their homes. Perceived severity and perceived vulnerability significantly influence the perceived behavioral control of villagers toward adopting the RSPV systems. The results show villagers’ attitudes, subjective norms and perceived behavioral control are the essential predictors of their adoption intention of the RSPV systems. Most notably, carbon neutrality was significantly affected by villagers’ adoption intention of RSPV systems as the renewable energy source in their homes.

The findings of this study provide that innovation attributes are important factors in shaping the adoption intentions of customers toward RSPV systems. This study is also the extent of previous studies measuring customers’ perception of adopting renewable energy in developed and emerging countries worldwide.

The utilisation of renewable energy sources for generating electricity and potable water is one of the most sustainable approaches in the current scenario. Therefore, the current research aims to design and develop a novel co-generation system to address the electricity and potable water needs of rural areas.

The cogeneration system mainly consists of a solar parabolic dish concentrator (SPDC) system with a concentrated photo-voltaic module at the receiver for electricity generation. It is further integrated with a low-temperature thermal desalination (LTTD) system for generating potable water. Also, a novel corn cob filtration system is introduced for the pre-treatment to reduce the salt content in seawater before circulating it into the receiver of the SPDC system. The designed novel co-generation system has been numerically and experimentally tested to analyse the performance at Karaikal, U.T. of Puducherry, India.

Because of the pre-treatment with a corn cob, the scale formation in the pipes of the SPDC system is significantly reduced, which enhances the efficiency of the system. It is observed that the conductivity, pH and TDS of seawater are reduced significantly after the pre-treatment by the corncob filtration system. Also, the integrated system is capable of generating 6–8 litres of potable water per day.

The integration of the corncob filtration system reduced the scaling formation compared to the general circulation of water in the hoses. Also, the integrated SPDC and LTTD systems are comparatively economical to generate higher yields of clean water than solar stills.

This study aims to establish whether three technology-specific attributes – convenience, compatibility with cultural needs and social reputation – influence the sustained use of clean cooking technologies in Uganda’s households.

This study adopted a cross-sectional and correlational research design. A survey was conducted with 125 households. The data were analyzed using SPSS and Smart PLS.

The results indicate that, in contrast to convenience, social reputation and compatibility with cultural needs significantly influence the sustained use of clean cooking technologies in Uganda’s households.

This study focused on the Greater Kampala Metropolitan Area; hence, several households in other urban centers and rural communities were excluded from the study. In addition, technology-specific attributes only accounted for 34.4% of the variation in the sustained use of clean cooking technologies in Uganda, leaving 65.6 unexplained. Therefore, the authors recommend that future studies look at other technology-specific attributes that may influence the sustained use of clean cooking technologies in Uganda’s households.

This study provides initial evidence of technology-specific attributes and the sustained use of clean cooking technologies based on the expectation–confirmation model.

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.

To generate electricity, solar photovoltaic (PV) systems are among the best, most eco-friendly and most cost-effective solutions available. Extraction of maximum possible electricity from the solar PV system is complicated by a number of factors brought on by the ever-changing weather conditions under which it must operate. Many conventional and evolutionary algorithm-based maximum power point tracking (MPPT) techniques have the limitation of not being able to extract maximum power under partial shade and rapidly varying irradiance. Hence, the purpose of this paper is to propose a novel hybrid slime mould assisted with perturb and observe (P&O) global MPPT technique (HSMO) for the hybrid bridge link-honey comb (BL-HC) configured PV system to enhance the better maximum power during dynamic and steady state operations within less time.

In this method, a hybridization of two algorithms is proposed to track the true with faster convergence under PSCs. Initially, the slime mould optimization (SMO) algorithm is initiated for exploration of optimum duty cycles and later P&O algorithm is initiated for exploitation of global duty cycle for the DC–DC converter to operate at GMPP and for fast convergence.

The effectiveness of the proposed HSMO MPPT is compared with adaptive coefficient particle swarm optimization (ACPSO), flower pollination algorithm and SMO MPPT techniques in terms of tracked GMPP, convergence time/tracking speed and efficacy under six complex partial shading conditions. From the results, it is noticed that the proposed algorithm tracks the true GMPP under most of the shading conditions with less tracking time when compared to other MPPT techniques.

This paper proposes a novel hybrid slime mould assisted with perturb and observe (P&O) global MPPT technique (HSMO) for the hybrid BL-HC configured PV system enhance the better maximum power under partial shading conditions (PSCs). This method operated in two stages as SMO for exploration and P&O for exploitation for faster convergence and to track true GMPP under PSCs. The proposed approach largely improves the performance of the MPP tracking of the PV systems. Initially, the proposed MPPT technique is simulated in MATLAB/Simulink environment. Furthermore, an experimental setup has been designed and implemented. Simulation results obtained are validated through experimental results which prove the viability of the proposed technique for an efficient green energy solution.

Electric motor heating during biomass recovery and its handling on conveyor is a serious concern for the motor performance. Thus, the purpose of this paper is to design and develop a hardware prototype of master–slave electric motors based biomass conveyor system to use the motors under normal operating conditions without overheating.

The hardware prototype of the system used master–slave electric motors for embedded controller operated robotic arm to automatically replace conveyor motors by one another. A mixed signal based embedded controller (C8051F226DK), fully compliant with IEEE 1149.1 specifications, was used to operate the entire system. A precise temperature measurement of motor with the help of negative temperature coefficient sensor was possible due to the utilization of industry standard temperature controller (N76E003AT20). Also, a pulse width modulation based speed control was achieved for master–slave motors of biomass conveyor.

As compared to conventional energy based mains supply, the system is self-sufficient to extract more energy from solar supply with an energy increase of 11.38%. With respect to conventional energy based \ of 47.31%, solar energy based higher energy saving of 52.69% was reported. Also, the work achieved higher temperature reduction of 34.26% of the motor as compared to previous cooling options.

The proposed technique is free from air, liquid and phase-changing material based cooling materials. As a consequence, the work prevents the wastage of these materials and does not cause the risk of health hazards. Also, the motors are used with their original dimensions without facing any leakage problems.

This study aims to examine the effect of the different forms of attitudes on the behavioural intentions to adopt solar energy technologies (SETs) in Uganda. Although commonly examined, the effect of attitudes on people’s behavioural intentions to adopt SETs ought to be more distinctively examined to have a clear picture of how each of the identified sets of attitudes influences the adoption of SETs.

Based on a sample of 360 households from three urban districts in Uganda sampled using a multi-stage sampling technique, data were collected using a self-administrated structured questionnaire. The data were then analysed using partial least square–structural equation model with SmartPLS 3.0 software.

The study establishes that more specific attitudes affect behavioural intentions to adopt SETs than general pro-technology attitudes. Results reveal that both pro-environment and application-specific attitudes matter for behaviour intentions to adopt SETs amongst households. However, the general pro-technology attitudes are not significantly associated with behavioural intentions to adopt SETs.

The results are important for producers and promoters of solar technology to craft appropriate promotion campaigns intended to increase the acceptance and usage of SETs. This means focussing on creating positive attitudes specific to particular applications and popularising specific uses of solar technologies.

The study provides an alternative approach to the general representation of the attitudes–intentions relationships by examining the differences in the attitudes developed towards the different aspects of these technologies as a substantial source of variations in adoption behaviour, which is rarely addressed.

This paper assesses the impact of this program on the rural women's employment opportunities using data from the 2015 round of the household's living standard survey (HLSS) of Côte d'Ivoire.

In 2013, in order to improve the living conditions of the rural population, the Ivorian government launched the National Program for rural electrification (PRONER) to electrify all localities with more than 500 inhabitants.

The results show that PRONER, while reducing the time allocated to performing household chores, increases women's employment through the reallocation of time to full-time paid work in the agricultural and non-agricultural sectors. The authors also find that the allocation of men's time is not affected by this programme. A possible mechanism that would explain such a pro-women effect is the labour-saving technology introduced to home production as an effect of the reform.

As a limitation, it is important to note that these results were obtained in the specific context of PRONER in Côte d’Ivoire and are not necessarily applicable to rural electrification programmes in other contexts. Furthermore, the choice of other indicators to measure women's empowerment is limited by the quality of the data available. It would be interesting for future research to extend this analysis to include other aspects of women's empowerment and household welfare.

This paper is the first to the author’s knowledge to apply a robust econometric method by combining an inverse probability weighted regression adjustment model with Heckman sample selection method to access a robust causal effect of the PRONER in Côte d'Ivoire.

Over the years, the significance of retrofitting has gained much attention with the unveiling of its different applications, such as energy retrofit and deep retrofit, to enhance the climate-resilience of buildings. However, no single study comprehensively assesses the climate-resilience of retrofitting. The purpose of this study is to address this gap via a systematic literature review.

Quality journal studies were selected using the PRISMA method and analysed manually and using scientometrics. Three dimensions of climate-resilience, such as robustness, withstanding and recovery, were used to evaluate the contribution of retrofit measures for achieving climate-resilient houses across four climate zones: tropical, arid, temperate and cold.

Most passive measures can enhance the robustness of residential buildings but cannot verify for withstanding against immediate shocks and timely recovery. However, some passive measures, such as night-time ventilation, show excellent performance over all four climate zones. Active measures such as heating, ventilation and air conditioning and mechanical ventilation with heat recovery, can ensure climate-resilience in all three dimensions in the short-term but contribute to greenhouse gas emissions, further exacerbating the long-term climate. Integrating renewable energy sources can defeat this issue. Thus, all three retrofit strategies should appropriately be adopted together to achieve climate-resilient houses.

Since the research is limited to secondary data, retrofit measures recommended in this research should be further investigated before application.

This review contributes to the knowledge domain of retrofitting by assessing the contribution of different retrofit measures to climate-resilience.

The effective prediction of crude oil futures prices can provide a reference for relevant enterprises to make production plans and investment decisions. To the nonlinearity, high volatility and uncertainty of the crude oil futures price, a matrixed nonlinear exponential grey Bernoulli model combined with an exponential accumulation generating operator (MNEGBM(1,1)) is proposed in this paper.

First, the original sequence is processed by the exponential accumulation generating operator to weaken its volatility. The nonlinear grey Bernoulli and exponential function models are combined to fit the preprocessed sequence. Then, the parameters in MNEGBM(1,1) are matrixed, so the ternary interval number sequence can be modeled directly. Marine Predators Algorithm (MPA) is chosen to optimize the nonlinear parameters. Finally, the Cramer rule is used to derive the time recursive formula.

The predictive effectiveness of the proposed model is verified by comparing it with five comparison models. Crude oil futures prices in Cushing, OK are predicted and analyzed from 2023/07 to 2023/12. The prediction results show it will gradually decrease over the next six months.

Crude oil futures prices are highly volatile in the short term. The use of grey model for short-term prediction is valuable for research. For the data characteristics of crude oil futures price, this study first proposes an improved model for interval number prediction of crude oil futures prices.