AIMS Energy最新文献

The performance of lithium-ion batteries declines rapidly over time, inducing anxiety in their usage. Ascertaining the capacity of these batteries is difficult to measure directly during online remaining useful life (RUL) prediction, and a single deep learning model falls short of accuracy and applicability in RUL predictive analysis. Hence, this study proposes a lithium-ion battery RUL indirect prediction model, fusing convolutional neural networks and bidirectional gated recurrent units (CNN-BiGRU). The analysis of characteristic parameters of battery life status reveals the selection of pressure discharge time, average discharge voltage and average temperature as health factors of lithium-ion batteries. Following this, a CNN-BiGRU model for lithium-ion battery RUL indirect prediction is established, and the Tree-structured Parzen Estimator (TPE) adaptive hyperparameter optimization method is used for CNN-BiGRU model hyperparameter optimization. Overall, comparison experiments on single-model and other fusion models demonstrate our proposed model's superiority in the prediction of RUL in terms of stability and accuracy.

Solar energy is one of the most important renewable energy sources due to its wide availability and applicability. One way to use this resource is by building-integrated photovoltaics (BIPV). Therefore, it is essential to develop a scientific map of BIPV systems and a comprehensive review of the scientific literature that identifies future research directions. For that reason, the bibliometric research methodology enables the quantification and evaluation of the performance, quality and influence of the generated maps and their elements. In this regard, an analysis of the scientific production related to BIPV, indexed from 2001 to 2022, was carried out using the Scopus database. This was done using a scientific mapping approach via the SciMAT tool to analyze the co-occurrence of terms through clustering techniques. The BIPV was integrated with the themes of buildings, investments, numerical models, office buildings, photovoltaic modules, roofs, solar cells and zero-energy buildings. As photovoltaic technology progresses, the production of flexible PV elements is increasing in lieu of silicon substrate-based PV elements, and this is of current scientific interest. The evaluations of BIPVs in various climatic contexts are encouraging in warm and sunny climates. BIPVs demonstrated high-energy generation, while in temperate climates, BIPV windows exhibited a reduction in heating and cooling loads, indicating notable efficiency. Despite significant benefits, BIPVs face challenges such as upfront costs, integration complexities and durability concerns. Therefore, silicon solar cells are considered a cross-cutting theme within the BIPV research field. It is highlighted that this study provides a comprehensive scientific mapping and critical review of the literature in the field of BIPV systems. This bibliometric analysis not only quantifies the performance and quality of the generated maps but also identifies key thematic areas that have evolved.

Peak shaving techniques have become increasingly important for managing peak demand and improving the reliability, efficiency, and resilience of modern power systems. In this review paper, we examine different peak shaving strategies for smart grids, including battery energy storage systems, nuclear and battery storage power plants, hybrid energy storage systems, photovoltaic system installations, the real-time scheduling of household appliances, repurposed electric vehicle batteries, uni- and bi-directional electric vehicle charging, the demand response, the time-of-use pricing, load shedding systems, distributed generation systems and energy-efficient management. We analyze the potential of each strategy to reduce peak demand and shift energy consumption to off-peak hours, as well as identify the key themes critical to the success of peak shaving for smart grids, including effective coordination and communication, data analytics and predictive modeling and clear policy and regulatory frameworks. Our review highlights the diverse range of innovative technologies and techniques available to utilities and power system operators and it emphasizes the need for continued research and development in emerging areas such as blockchain technology and artificial intelligence. Overall, the implementation of peak shaving strategies represents a significant step toward a more sustainable, reliable and efficient power system. By leveraging the latest technologies and techniques available, utilities and power system operators can better manage peak demand, integrate renewable energy sources, and create a more reliable and secure grid for the future. By discussing cutting-edge technologies and methods to effectively manage peak demand and incorporate renewable energy sources, this review paper emphasizes the significance of peak shaving strategies for smart grids as a crucial pathway towards realizing a more sustainable, dependable and efficient power system.