Feasibility of a 100% Global Renewable Energy System

Powering sustainable growth in West Africa: exploring the role of environmental tax, economic development, and financial development in shaping renewable energy consumption patterns

Over time, the economy's growth, financial development, and environmental taxes have become vital tools in countering ecological degradation and promoting clean energy. However, there needs to be a research gap in assessing these policies' collective impact on renewable energy adoption, especially in developing West African countries. This study addresses this gap by evaluating the effectiveness of these policies from 1990 to 2020, using the Generalized Method of Moments (GMM), fixed effect, and pooled Ordinary Least Squares (OLS) models. The Dumitrescu-Hurlin panel causality test reveals bidirectional causality between economic growth and renewable energy consumption, as well as between financial development and renewable energy use. Unidirectional causality is found from environmental tax to renewable energy consumption. GMM results highlight the positive influences of economic growth and environmental taxes on renewable energy consumption, while financial development negatively affects it. These outcomes are consistent with fixed effect and pooled OLS models. Sectorial heterogeneity analysis indicates better results for countries with strong institutions, advanced technology, and strict regulations. In conclusion, this study's insights can guide policies for sustainability in West Africa, leveraging economic growth, environmental taxes, and technology for effective renewable energy integration.

Sustainable development of renewable energy integrated power sector: Trends, environmental impacts, and recent challenges

The continuous growth in overall energy demand and the related environmental impacts play a significant role in the large sustainable and green global energy transition. Moreover, the electrical power sector is a major source of carbon dioxide emissions. Therefore, renewable energy (RE) integration into the power grid has attracted significant economic, environmental, and technical attention in recent years. However, RE can also harm the environment, even though it is deemed less harmful than fossil fuel-based power. It may also cause technical, operational, and social issues. This, in return, more consideration and appropriate precautions should be taken. Given the recent sharp increase in RE utilization and its progressing impact on the world energy sector, evaluating its effect on the environment and sustainable development is limitedly explored and must be investigated. This study aims to discuss the role of RE integration in sustainable development. It provides an up-to-date review of the most recent global trend of various RE integrations into the power sector. The role and impact of this high integration level on the environment and the adverse effects of each RE source are discussed in detail. The recent challenges, including technical and operational challenges (i.e., voltage stability, frequency stability, and power quality), integration policy and standards challenges, RE environmental concerns, resource selection and location, and social challenges towards a sustainable electricity future and grid decarbonization, are comprehensively reviewed, discussed, and analyzed. A review of the literature was conducted from 2010 to 2021. Around 712 articles were classified during this process, and 177 papers were filtered for critical review. The literature analysis showed that RE integration has increased dramatically and has many benefits; however, more attention should be paid to mitigate its harmful impacts and recent challenges appeared. The new challenges resulting from the increasing generation of RE and linking it to the electric grid were listed to allow for future studies to find the appropriate solutions towards green and sustainable energy. Finally, towards a sustainable power system, the paper concludes with recommendations for future research directions.

Assessing Global Long-Term EROI of Gas: A Net-Energy Perspective on the Energy Transition

Natural gas is expected to play an important role in the coming low-carbon energy transition. However, conventional gas resources are gradually being replaced by unconventional ones and a question remains: to what extent is net-energy production impacted by the use of lower-quality energy sources? This aspect of the energy transition was only partially explored in previous discussions. To fill this gap, this paper incorporates standard energy-return-on-investment (EROI) estimates and dynamic functions into the GlobalShift bottom-up model at a global level. We find that the energy necessary to produce gas (including direct and indirect energy and material costs) corresponds to 6.7% of the gross energy produced at present, and is growing at an exponential rate: by 2050, it will reach 23.7%. Our results highlight the necessity of viewing the energy transition through the net-energy prism and call for a greater number of EROI studies.

Feasibility and Economic Impacts of the Energy Transition

There is currently no consensus regarding whether or not renewable energies are capable of supplying all of our energy needs in the near future. To shed new light on this controversy, this paper develops a methodology articulating a macroeconomic model with two sectors (energy and non-energy) and an energy model that is able to calculate the maximum potentials of solar and wind energy. The results show that, in a business-as-usual context, a complete energy transition on a global scale is unachievable before the end of the century. The reason lies in the increasing capital needs of the energy sector, which slows, if not stops, economic growth and the energy transition. A complete transition can be achieved by 2070 provided that (i) energy demand is kept under control at its current level, (ii) a sufficient rate of capital growth is sustained (above its historical level), and (iii) substantial progress is made in terms of energy efficiency. However, this strategy requires a significant increase in the savings rate, with a negative impact on consumption, which ends up stagnating at the end of the transition.

Critical Review of Flywheel Energy Storage System

This review presents a detailed summary of the latest technologies used in flywheel energy storage systems (FESS). This paper covers the types of technologies and systems employed within FESS, the range of materials used in the production of FESS, and the reasons for the use of these materials. Furthermore, this paper provides an overview of the types of uses of FESS, covering vehicles and the transport industry, grid leveling and power storage for domestic and industrial electricity providers, their use in motorsport, and applications for space, satellites, and spacecraft. Different types of machines for flywheel energy storage systems are also discussed. This serves to analyse which implementations reduce the cost of permanent magnet synchronous machines. As well as this, further investigations need to be carried out to determine the ideal temperature range of operation. Induction machines are currently stoutly designed with lower manufacturing cost, making them unsuitable for high-speed operations. Brushless direct current machines, the Homolar machines, and permanent magnet synchronous machines should also be considered for future research activities to improve their performance in a flywheel energy storage system. An active magnetic bearing can also be used alongside mechanical bearings to reduce the control systems’ complications, thereby making the entire system cost-effective.

Towards Understanding Interactions between Sustainable Development Goals: The Role of Climate-Well-Being Linkages. Experiences of EU Countries

The 2030 Agenda with 17 Sustainable Development Goals (SDGs) is a challenge for all countries in the world. Their implementation may turn out to be a compromise or the creation of effective interactions that dynamize sustainable development. To achieve the SDGs, it is essential to understand how they interact with each other. It seems that in the times of the climate and health crisis caused by the COVID-19 pandemic, caring for the environment and ensuring a healthy life and promoting well-being at all ages is the basis for environmental, economic and social sustainable development. The aim of the study is to compare the degree of implementation of the goals of sustainable development in the scope of goal 13 “Climate action” and goal 3 “Good health and well-being” in the EU countries. In addition, we analyze how trade-offs and synergies between these goals have developed. Data from the Eurostat database were used to achieve the goal. The study used the method of multivariate comparative analysis—linear ordering of objects. The technique for order preference by similarity to an ideal solution (TOPSIS) method was used to measure the studied phenomenon. The results indicate a different degree of implementation of the sustainable development goals related to climate change and the improvement of health and social well-being. Only a few countries have synergy in achieving these goals, most of them compromise, manifesting themselves in improving one goal over another. In the group of analyzed EU countries, a simultaneous deterioration in the effectiveness of achieving both objectives were also noted. Our research also shows that energy policy is an important attribute in improving the achievement of these goals. The conducted analysis fills the gap in the research on the implementation of selected sustainable development goals and their interactions. It contributes to the discussion on increasing the links between them, in particular with regard to emerging compromises. This research can provide a basis for re-prioritizing and intensifying the actions where individual EU countries are lagging most behind.

New Energy Technologies: Microalgae, Photolysis and Airborne Wind Turbines

Because of the near-term risk of extreme weather events and other adverse consequences from climate change and, at least in the longer term, global fossil fuel depletion, there is worldwide interest in shifting to noncarbon energy sources, especially renewable energy (RE). Because of possible limitations on conventional renewable energy sources, researchers have looked for ways of overcoming these shortcomings by introducing radically new energy technologies. The largest RE source today is bioenergy, while solar energy and wind energy are regarded as having by far the largest technical potential. This paper reviews the literature on proposed new technologies for each of these three RE sources: microalgae for bioenergy, photolysis and airborne wind turbines. The main finding is that their proponents have often underestimated the difficulties they face and the time taken for their introduction on a very large scale.

Combined Multi-Layer Feature Fusion and Edge Detection Method for Distributed Photovoltaic Power Station Identification

Distributed photovoltaic power stations are an effective way to develop and utilize solar energy resources. Using high-resolution remote sensing images to obtain the locations, distribution, and areas of distributed photovoltaic power stations over a large region is important to energy companies, government departments, and investors. In this paper, a deep convolutional neural network was used to extract distributed photovoltaic power stations from high-resolution remote sensing images automatically, accurately, and efficiently. Based on a semantic segmentation model with an encoder-decoder structure, a gated fusion module was introduced to address the problem that small photovoltaic panels are difficult to identify. Further, to solve the problems of blurred edges in the segmentation results and that adjacent photovoltaic panels can easily be adhered, this work combines an edge detection network and a semantic segmentation network for multi-task learning to extract the boundaries of photovoltaic panels in a refined manner. Comparative experiments conducted on the Duke California Solar Array data set and a self-constructed Shanghai Distributed Photovoltaic Power Station data set show that, compared with SegNet, LinkNet, UNet, and FPN, the proposed method obtained the highest identification accuracy on both data sets, and its F1-scores reached 84.79% and 94.03%, respectively. These results indicate that effectively combining multi-layer features with a gated fusion module and introducing an edge detection network to refine the segmentation improves the accuracy of distributed photovoltaic power station identification.