• Energy Research
• 2021-2025close
• 11. Sustainability close
• AU close

Abstract Integration of solar photovoltaic (PV) and battery storage systems is an upward trend for residential sector to achieve major targets like minimizing the electricity bill, grid dependency, emission and so forth. In recent years, there has been a rapid deployment of PV and battery installation in residential sector. In this regard, optimal planning of PV-battery systems is a critical issue for the designers, consumers, and network operators due to high number of parameters that can affect the optimization problem. This paper aims to present a comprehensive and critical review on the effective parameters in optimal planning process of solar PV and battery storage system for grid-connected residential sector. The key parameters in process of optimal planning for PV-battery system are recognized and explained. These parameters are economic and technical data, objective functions, energy management systems, design constraints, optimization algorithms, and electricity pricing programs. A timely review on the state-of-the-art studies in PV-battery optimal planning is presented. The challenges, trends and latest developments in the topic are discussed. At the end, scopes for future studies are developed. It is found that new guidelines should be provided for the customers based on various electricity rates and demand response programs. Also, several design considerations like grid dependency and resiliency need further investigation in the optimal planning of PV-battery systems.

In recent years, sustainability concerns have gained increasing attention among countries and stakeholders worldwide. Towards the transition to sustainable rural development, the rural web framework (RWF) has become a consistent tool. Indicators from the RWF have been used to explore sustainable rural development for decision-making tasks, which improves the social, economic, and environmental performance of rural regions. However, the application of the RWF in studies is on the decline. Furthermore, there is a lack of literature reviews on the importance of the RWF and its relationship with different facets of sustainable development. We conducted a systematic literature review (SLR) (a) to explore how studies have used the RWF in the context of sustainable development and (b) to identify areas for further research. This study found that the RWF has mostly been used in developed countries, with fewer applications in developing countries. We suggest that there should be increased application of the RWF, particularly in developing countries, to broaden the rural web–sustainable development discourse and its relevance. This paper presents several areas where the indicators of the RWF can be applied to illustrate their relevance for policy decisions towards the achievement of the sustainable development goals (SDGs).

The COVID-19 pandemic has impacted all sectors of the tourism industry, particularly air transportation. However, air transport remains an important contributor to economic growth globally. Thus, this study examines whether air transport (a proxy for tourism) stimulates economic growth to validate the air-transportation-led growth hypothesis (ALGH) in the Australian context. To conduct the study, we analyse the asymmetric long-run and short-run impacts of the air passengers carried (a proxy for tourism) on the gross domestic product (GDP) in Australia. We use the nonlinear autoregressive distributed lag (NARDL) modelling approach on data for Australia from 1971 to 2019. We also examined the effects of selected control variables (i.e., energy consumption, financial development, socialisation, and urbanisation) on economic growth. In both the short and long run, we observed statistically significant asymmetric impacts of air transport on economic growth. The positive shocks in air transport propel the long-term growth of Australia’s economy. Additionally, according to the findings, negative shocks of air transport have a stronger detrimental impact on economic development than positive shocks.

Public transport systems in different parts of the world are currently undergoing a change characterised by the introduction of battery-powered electric buses in everyday operations. The introduction of electric buses brings new challenges such as high investment costs and technology concerns, as well as new forms of collaboration between both established and new actors. The aim of this paper is to disentangle different actors’ rationale for the transition, identifying underlying interests in and expectations of the electric bus system. With a focus on the Swedish context, we found that whilst common rationales exist, these are influenced by collective expectations and different underlying interests for the actor groups. We found that the interests of the actors are grounded in expectations of future developments, but also relate to the experience that the transition is occurring faster than previously anticipated. The results show a high degree of consensus regarding the transition to electric buses, although the actors have varying resources and action spaces with which to influence the transition, which is largely determined by the institutional and local context.

Abstract In recent years, modern appliances with high electricity demand have played a significant role in residential energy consumption. Despite the positive impact of these appliances on the quality of life, they suffer from major drawbacks, such as serious environmental concerns and high electricity bills. This paper introduces a consolidated framework of load management to alleviate those drawbacks. Initially, benefiting from a demonstrative analysis of home energy consumption data, controllable and responsive appliances in smart home are identified. Then, the energy consumption pattern is reduced and shifted using flexible load models and better utilization of existing energy storage systems. This can be achieved through data mining approaches, i.e., density-based spatial clustering of application with noise (DBSCAN) method. In this technique, no sensor for detection or measurement instruments will be required, whose deployment incur cost to the system or increase security risk for consumers. In the following, one scheduling of using controllable appliances, which is formulated by convex optimization, is considered for the demand response (DR) program, provided that this plan doesn't affect customers’ priority and convenience. In the last stage, the deployment of energy storage systems, such as plug-in hybrid electric vehicles (PHEVs) and battery energy storage systems (BESS), is introduced to lower the energy cost and improve the performance of the proposed DR model. Simulation results of this demand response are compared with conventional k-clustering methods to confirm the economic superiority of the DBSCAN clustering technique using the data of a residential unit during three different scenarios.

The integration of sustainable practices into infrastructure projects under the auspices of public-private partnerships (PPPs) is vital in the attainment of United Nation’s Sustainable Development Goals (SDGs). Since the inception of the SDGs in 2015, the attention of world has been shifting towards more sustainable practices and it is essential that the conventional performance measurement models on PPP projects also adapt to the trend of sustainable practices. Therefore, This study aims at reviewing and operationalising sustainable performance measures for the PPP infrastructure projects. A systematic literature review (SLR) methodology was utilised in this study. The research process began with the search, retrieval and selection of thirty-three (33) journal articles. Thoroughly, the selected articles were contently analysed to form key themes that form the basis of this research’s findings. The outcomes of this review demonstrate twenty-seven (27) most critical sustainable performance criteria of PPP projects such as the lowest project costs, green index, disability-friendly inclusion rate and carbon emission per project among others. Although, the study is limited to few journal articles, it provides theoretical and practical understanding of integration of sustainability in PPPs. Further, it gives a list of relevant research gaps for further studies. This study contributes to the benchmarking and management of sustainable performance assessment of PPP projects.

AbstractClimate change, migration, and conflict have been featured prominently in academic and policy literature. While Africa remains the major reference point, studies on key conflict hotspots fail to adequately examine empirical demonstrations of how climate change forces migration, and consequently major conflicts. Drawing on semi‐structured interviews, focus group discussions, and employing the scarcity theory in a study of Agogo (Ghana), we illustrate how regional and local climate/environmental variability and scarcity trigger and sustain migration and farmer–herder conflicts. The findings offer insights into how other non‐climatic and ecological conditions reinforce the so‐called climate‐induced conflicts, exposing the limitations of the scarcity‐theory. Importantly, this study has provided an illustrative argument centered around the contextual dynamics of the nexus between climate change and farmer–herder conflict in Agogo to contribute to national, regional, and continental discussion on this critical topic.

Abstract Accurate rooftop solar energy potential characterization is critically important for promoting the wide penetration of renewable energy in high-density cities. However, it has been a long-standing challenge due to the complex building shading effects and diversified rooftop availabilities. To overcome the challenge, this study proposed a novel 3D-geographic information system (GIS) and deep learning integrated approach, in which a 3D-GIS-based solar irradiance analyzer was developed to predict dynamic rooftop solar irradiance by taking shading effects of surrounding buildings into account. A deep learning framework was developed to identify the rooftop availabilities. Experimental validations have shown their high accuracies. As a case study, a real urban region of Hong Kong was used. The results showed that the annual solar energy potential of the entire building group was reduced by 35.7% due to the shading effect and the reduced rooftop availability. The reductions of individual buildings varied from 13.4% to 74.5%. In spite of the substantial reductions of the annual solar energy, the shading effect could only slightly reduce the peak solar power. In fact, the annual solar energy reduction could be five times higher than the peak solar power reduction. Further analysis showed that simple addition of the respective solar energy potential reductions, caused by the shading effect and the rooftop availability, tends to highly overestimate the total reduction by up to 26%. For this reason, their impacts cannot be considered separately but as joint effects. The integrated approach provides a viable means to accurately characterize rooftop solar energy potential in urban regions, which can help facilitate solar energy applications in high-density cities.