Search results

Solar power forecasting will have a significant impact on the future of large-scale renewable energy plants. Predicting photovoltaic power generation depends heavily on climate conditions, which fluctuate over time. In this research, we propose a hybrid model that combines machine-learning methods with Theta statistical method for more accurate prediction of future solar power generation from renewable energy plants. The machine learning models include long short-term memory (LSTM), gate recurrent unit (GRU), AutoEncoder LSTM (Auto-LSTM) and a newly proposed Auto-GRU. To enhance the accuracy of the proposed Machine learning and Statistical Hybrid Model (MLSHM), we employ two diversity techniques, i.e. structural diversity and data diversity. To combine the prediction of the ensemble members in the proposed MLSHM, we exploit four combining methods: simple averaging approach, weighted averaging using linear approach and using non-linear approach, and combination through variance using inverse approach. The proposed MLSHM scheme was validated on two real-time series datasets, that sre Shagaya in Kuwait and Cocoa in the USA. The experiments show that the proposed MLSHM, using all the combination methods, achieved higher accuracy compared to the prediction of the traditional individual models. Results demonstrate that a hybrid model combining machine-learning methods with statistical method outperformed a hybrid model that only combines machine-learning models without statistical method.

This study aims to exploit the abundance of solar energy resources for socioeconomic development in the semi -arid Northeastern Brazil as a potent adaptation tool to global climate change. It points out a set of conjuncture factors that allow us to foresee a new paradigm of sustainable development for the region by transforming the sun’s radiant energy into electricity through distributed photovoltaic generation. The new paradigm, as presented in this essay, has the transformative potential to free the region from past regional development dogma, which was dependent on the scarce water resource, and the marginal and predatory use of its Caatinga Biome.

The research uses a pre ante design, following the procedures of scenario building, as an adaptation mechanism to climate change in the sector of energy generation and socioeconomic inclusion.

The scenarios of socioeconomic resilience to climate change based on the abundance of solar radiation, rather than the scarcity of water, demonstrates its potential as a global adaptation paradigm to climate change.

The developments proposed are dependent on federal legislation changes, allowing the small producer to be remunerated by the energy produced.

The proposed smart grid photovoltaic generation program increases the country's resiliency to the effect of droughts and climate change.

As proposed, the program allows for the reversion of a pattern of long term poverty in semi-arid Northeast Brazil.

The exploitation of the characteristics of abundance of the semiarid climate, i.e. its very condition of semi-aridity with abundant solar radiation, is itself an advantage factor toward adaption to unforeseen drought events. Extensive previous research has focused on weighting and monitoring drought i.e. the paradigm of scarcity. The interplay between exploiting Northeast Brazil’s abundant factors and climate change adaptation, especially at the small farmer levels constitutes a discovery never before contemplated.

This paper aims to forecast the availability of used but operational electric vehicle (EV) batteries to integrate them into a circular economy concept of EVs' end-of-life (EOL) phase. Since EVs currently on the roads will become obsolete after 2030, this study focuses on the 2030–2040 period and links future renewable electricity production with the potential for storing it into used EVs' batteries. Even though battery capacity decreases by 80% or less, these batteries will remain operational and can still be seen as a valuable solution for storing peaks of renewable energy production beyond EV EOL.

Storing renewable electricity is gaining as much attention as increasing its production and share. However, storing it in new batteries can be expensive as well as material and energy-intensive; therefore, existing capacities should be considered. The use of battery electric vehicles (BEVs) is among the most exciting concepts on how to achieve it. Since reduced battery capacity decreases car manufacturers' interest in battery reuse and recycling is environmentally hazardous, these batteries should be integrated into the future electricity storage system. Extending the life cycle of batteries from EVs beyond the EV's life cycle is identified as a potential solution for both BEVEOL and electricity storage.

Results revealed a rise of photovoltaic (PV) solar power plants and an increasing number of EVs EOL that will have to be considered. It was forecasted that 6.27–7.22% of electricity from PV systems in scenario A (if EV lifetime is predicted to be 20 years) and 18.82–21.68% of electricity from PV systems in scenario B (if EV lifetime is predicted to be 20 years) could be stored in batteries. Storing electricity in EV batteries beyond EV EOL would significantly decrease the need for raw materials, increase energy system and EV sustainability performance simultaneously and enable leaner and more efficient electricity production and distribution network.

Storing electricity in used batteries would significantly decrease the need for primary materials as well as optimizing lean and efficient electricity production network.

Energy storage is one of the priorities of energy companies but can be expensive as well as material and energy-intensive. The use of BEV is among the most interesting concepts on how to achieve it, but they are considered only when in the use phase as vehicle to grid (V2G) concept. Because reduced battery capacity decreases the interest of car manufacturers to reuse batteries and recycling is environmentally risky, these batteries should be used for storing, especially renewable electricity peaks. Extending the life cycle of batteries beyond the EV's life cycle is identified as a potential solution for both BEV EOL and energy system sustainability, enabling more efficient energy management performance. The idea itself along with forecasting its potential is the main novelty of this paper.

This study aims to examine the concept of innovative technologies and identify their impacts on the environmental sustainability of commercial properties in South Africa. This slow adoption is attributed to South Africa’s energy building regulation, SANS 204, which does not promote energy-conscious commercial property development. Furthermore, it was observed that buildings waste significant amounts of energy as electrical appliances are left on when they are not in use, which can be prevented using innovative technologies.

The researchers attempted to evaluate the impact of innovative technologies through an overarching constructivist mixed-method paradigm. The research was conducted using a multi-case study approach on green buildings which had innovative technologies installed. The data collection took the form of online, semi-structured interviews, where thematic analysis was used to identify emergent themes from the qualitative data, and descriptive statistics was used to evaluate the quantitative data.

It was found that implementing innovative technologies to reduce the energy consumption of commercial buildings could achieve energy savings of up to 23%. Moreover, a commercial building’s carbon footprint can be reduced to 152CO2/m2 and further decreased to 142CO2/m2 through the adoption of a Photovoltaics plant. The study further found that innovative technologies improved employee productivity and promoted green learning and practices.

This research demonstrated the positive impact innovative technologies have on energy reduction and the sustainability of commercial properties. Hence, facility managers should engage innovative technologies when planning a commercial development or refurbishment.

This paper seeks to analyze the relationship between China and the Northeast region of Brazil, aiming to identify how the renewable energy sector is being developed.

The authors analyzed secondary data from the official databases from China-Brazil chambers of commerce to establish the main points related to renewable energy in Brazil's Northeast.

It is possible to notice the main investments, highlighting the wind energy as a more prominent source recently. The authors also point the huge influence from China on Brazil's Northeast energy sector.

It is difficult to identify the amount of Chinese capital due to the large number of mergers and acquisitions that has been taking place in recent years.

Identification of regions that have been receiving investments and the main interests of Chinese investors in the renewable energy sector.

Demonstration of how the renewable energy sector has taken an important turn in Brazil due to Chinese investment.

To evaluate a regional consortium, analyzing its strategies for partnerships with China to help each other in global questions, as is the case of renewable energy.

Measuring shared value (SV) created in innovation ecosystems (IEs) is increasingly relevant but complex, given the multidimensional and multiactor nature of both concepts, which challenges traditional performance measurement systems (PMSs). Moving from this gap, the authors propose an integrated approach to extend the balanced scorecard (BSC) for measuring and monitoring SV creation at IE level.

The proposed approach combines the most recent contributions on PMS in IEs and SV to define perspectives and dimensions that are better suited to deal with the nature of both IEs and SV. The approach is also applied to the real case (Alpha) of an Italian IE through a step wise method. Starting from the IE vision, the authors identify in the strategy map the specific objectives related to each perspective/dimension combination and then associate a performance indicator with each objective.

The resulting SV BSC is composed of indicators interconnected along different perspectives and dimensions. The application of the approach to the real case proves its feasibility and highlights characteristics, advantages and disadvantages of the SV BSC when used at IE level. The authors also provide guidelines for its application to other IEs.

The study contributes to the research on PMS by introducing and applying to a real case an integrated approach to assess SV in IEs, overcoming the shortcomings of PMS framed for single firms. It can be of interest for both researchers in the field of ecosystems value creation and practitioners managing or promoting such complex structures.

The purpose of this paper is to enlarge the body of knowledge on research through design (RtD) methods that can be employed by landscape architects and others working on (but not limited to) sustainable energy transition.

A specific approach to RtD – qualitative landscape structure analysis (QLSA) – is introduced and illustrated by means of diagrams and photographs. Two case studies showcase the application of QLSA for research on solar parks in the Netherlands and research on wind turbines in the Alpine foothills in Southern Germany.

The case studies show how RtD can help to define design principles for large solar parks and arrangement of wind turbines in particular landscape types in the Netherlands and Germany, respectively. In doing so, RtD can help to expand the breadth of spatial research beyond well-established methods such as multi-criteria decision analysis and environmental impact assessment.

The paper provides insights into contemporary RtD in two countries and affirms the importance of such research with regard to landscape transformations while starting to define a research niche for landscape architects and other environmental designers working on the topic of sustainable energy transition.

This study investigates the barriers and drivers of using green methods and technologies (GMTs) in supportive educational buildings (SEBs) in South Africa, and assesses their impact on the circular economy (CE) in achieving net-zero carbon goals. While there has been extensive literature on green building technologies, there is limited research on the barriers and drivers of using GMT in SEBs, as well as their impact on the circular economy (CE) in achieving net-zero carbon goals.

This study adopts an interpretivist approach with an ontological basis, using an overarching case study of a SEB at the University of Cape Town (UCT). Semistructured interviews were conducted with executive UCT management, and a field survey of a UCT supportive education building was performed.

At UCT, multiple GMTs have been installed across various buildings to enhance monitoring and management of water and energy consumption. Moreover, initiatives to positively influence student behavior, such as water and energy-saving campaigns around UCT premises, have been introduced. The findings further indicate that UCT has recently emphasized the implementation of GMTs, resulting in improved resource efficiency, CE practices and progress toward achieving net-zero carbon targets for supportive education buildings and the university as a whole.

This research highlights the positive impact of GMTs on a SEB’s CE and net-zero carbon operations. As a result, facility managers should consider incorporating GMTs when planning the development or refurbishment of SEBs.