• Energy Research
• 7. Clean energy close
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The high-voltage battery is a crucial element for EV traction systems. It is the primary energy source that must be regularly recharged to reach the autonomy declared by the manufacturer. Therefore, an EV charging system is required to ensure the battery charging process. This review thoroughly investigates the available EV charging technologies and the most popular batteries for EV applications. The contributions of this work can be summarized as follows: the classification and topologies of electric vehicle chargers are examined, an overview of the current EV charging standards is provided, the state-of-the-art of EV charging couplers is discussed, and the most widely used batteries in EV applications are reviewed.

In underground mining, it is not currently feasible to forecast a coal burst incident. A coal burst usually includes suddenly abrupt energy release in line with the significant deformed shape in a coal mass as well as coal ejection. The major source of the released energy is the energy stored in the coal. The effect of geological characteristics in the coal on the possible released energy due to material and joint damping is classified as a current silent issue. Therefore, innovative research is needed to understand the influence of coal’s joint and cleat characters (directions and densities) on the possible energy release and/or dissipation. A simple and novel analytical solution is developed in this paper to calculate the amount of released energy due to varying joint density. A broad validation is conducted by comparing the outcomes of the developed analytical model with the results of a three-dimensional numerical simulation using the commercial discrete element package 3DEC. An appropriate agreement has been observed between the results from the numerical modelling and the suggested closed form solution. The paper derives a novel analytical solution to calculate the amount of released energy in coal with different joint densities.

Energy storage technology plays a significant role in the pursuit of the high-quality development of the electricity market. Many regions in China have issued policies and regulations of different intensities for promoting the popularization of the energy storage industry. Based on a variety of initial conditions of different regions, this paper explores the evolutionary process of electricity market players considering energy storage technology. The trilateral evolutionary game model is adopted to analyze the strategies of the power plant, the power grid, and the government. After assigning the model according to an actual situation, each equilibrium point corresponds to a real electricity market situation. The results indicate the following: (1) In the process of stabilizing, the role of “Advanced Imitators” leading the strategy of building energy storage changes between the power plant and the power grid. (2) In Eastern, Middle, and Southern China, the power plants and power grids on a greater-than-medium scale will choose to build energy storage without governmental regulations, due to the abundant net profit. (3) In the northeast of China, power plants with a medium-or-lower scale will choose not to build energy storage because of the relatively low on-grid price, and small power grids can make enough profits by operating energy storage facilities. (4) In Northern China, the large power plants and the medium power grids will choose to build energy storage due to the high electricity sale price and the resulting high profit. (5) In Western China, the small power plants and power grids cannot afford to build energy storage due to the low electricity price. The results lead to valuable policy suggestions for the local governments of China in promoting energy storage in the future. To meet the goal of energy storage popularization, regional electricity market plans need relevant policies based on its existing conditions, offering suitable external conditions for adding energy storage.

Energy ecosystems are under a significant transition. Local flexibility marketplaces (LFM) and platforms are argued to have significant potential in contributing to such a transition. The purpose of this study was to answer the following research question: how do market conditions and stakeholders shape emerging LFM platform governance choices? We approached this objective with an exploratory single-case study by conducting ten semi-structured interviews with key stakeholders in the Finnish energy ecosystem. The results of the content and pattern analyses revealed the key challenges to LFM implementation such as the current regulatory treatment of flexibility, high costs of gadget installations, and ensuring sufficient liquidity in the market. In addition, we also demonstrated that despite such barriers, the Finnish ecosystem is largely pragmatic about LFMs’ in its midst. All in all, we contributed to the non-technological streams of LFM literature by developing an exhaustive framework with four distinctive dimensions (i.e., ecosystem readiness, value-creation logic, platform architecture and governance, platform competitiveness) for LFM development, which helps academics, practitioners, and policy-makers to understand how novel platforms emerge and develop.

The prevailing need for a more sustainable management of natural resources depends not only on the decisions made by governments and the will of the population, but also on the knowledge of the role of energy in our society and the relevance of preserving natural resources. In this sense, critical work is being done to instill key concepts—such as the circular economy and sustainable energy—in higher education institutions. In this way, it is expected that future professionals and managers will be aware of the importance of energy optimization, and will learn a series of computational methods that can support the decision-making process. In the context of higher education, this paper reviews the main trends and challenges related to the concepts of circular economy and sustainable energy. Besides, we analyze the role of simulation and serious games as a learning tool for the aforementioned concepts. Finally, the paper provides insights and discusses open research opportunities regarding the use of these computational tools to incorporate circular economy concepts in higher education degrees. Our findings show that, while efforts are being made to include these concepts in current programs, there is still much work to be done, especially from the point of view of university management. In addition, the analysis of the teaching methodologies analyzed shows that, although their implementation has been successful in favoring the active learning of students, their use (especially that of serious games) is not yet widespread.

Deployment of photovoltaic (PV) systems has recently been encouraged for large-scale and small-scale businesses in order to meet the global green energy targets. However, one of the most significant hurdles that limits the spread of PV applications is the dust accumulated on the PV panels’ surfaces, especially in desert regions. Numerous studies sought the use of cameras, sensors, power datasets, and other detection elements to detect the dust on PV panels; however, these methods pose more maintenance, accuracy, and economic challenges. Therefore, this paper proposes an intelligent system to detect the dust level on the PV panels to optimally operate the attached dust cleaning units (DCUs). Unlike previous strategies, this study utilizes the expanded knowledge and collected data for solar irradiation and PV-generated power, along with the forecasted ambient temperature. An expert artificial intelligence (AI) computational system, adopted with the MATLAB platform, is utilized for a high level of data prediction and processing. The AI was used in this study in order to estimate the unprovided information, emulate the provided measurements, and accommodate more input/output data. The feasibility of the proposed system is investigated using actual field data during all possible weather conditions.

Coal will continue to be the main energy source in China for the immediate future, although the environmental pollution and ecological impacts of each stage in the full life cycle of coal mining, transportation, and combustion generate large quantities of external costs. The Late Permian coals in southwestern (SW) China usually contain high amounts of fluorine (F), arsenic (As), and ash, which together with high-F clays cause abnormally high levels of endemic fluorosis, As poisoning, and lung cancer in areas where coal is mined and burned. In this paper, we estimate the external costs of the life cycle of coal. The results show that the externalities of coal in SW China are estimated at USD 73.5 billion or 284.3 USD/t, which would have accounted for 6.5 % of the provincial GDP in this area in 2018. The external cost of human health accounts for 87.2% of the total external costs, of which endemic skeletal fluorosis diseases and related lung cancers have the most important impact. Our study provides a more precise estimate of externalities compared with its counterparts in other provinces in China. Therefore, several policy recommendations would be proposed to internalize the external cost.