Recently, the Smart Microgrid Research Group of the Shenyang Institute of Automation, Chinese Academy of Sciences has made progress in the field of smart grid optimization dispatching, and related results have been published in the smart grid journal IEEE TRANSACTIONS ON SMART GRID.
As global climate change and environmental pollution problems become more and more serious, the cleanliness, safety and sustainability of electric power systems are increasingly valued by countries around the world. The development of large-scale distributed renewable clean energy, the use of advanced intelligent optimization and control technology to accelerate the transformation of traditional power systems to cleaner, safer and more sustainable smart grids are the future development trend of power systems and emerging research hotspots . At present, domestic and foreign researches on renewable energy access, transient stability control, and the economics of power grid operation have made important progress. However, the safety of the operation of power systems with a high proportion of renewable energy access And related intelligent optimization scheduling methods still need to be broken through.
In a research paper entitled Dynamic Energy Management of a Microgrid using Approximate Dynamic Programming and Deep Recurrent Neural Network Learning, the Smart Microgrid Research Group proposed a real-time energy optimization method for microgrids based on deep reinforcement learning technology. This method considers the randomness of renewable energy output and its impact on grid AC power flow constraints. It uses a deep recurrent neural network to extract features from the current operating state of the microgrid, and on the basis of ensuring the security of the microgrid, Each distributed power generation unit performs scheduling to realize real-time optimized control of microgrid operation. In addition, compared with the current microgrid operation control method, the proposed method is completely based on learning, without predictive modeling of renewable energy output, showing good adaptability. This work is not only a new exploration and breakthrough in the research of smart grid optimization dispatch, but also provides new research ideas for the future application of artificial intelligence technology to promote the development of smart grids.
Deep recurrent neural network
Microgrid structure diagram considering power flow security constraints
Approximate optimal value function based on deep neural network and shallow network
Spherical Roller Bearings are most suitable option for applications that need shock resistant components yet this is not the only quality these Bearings have. These Bearings can handle heavy loads because of their rings` alignment. Due to the curved outer ring, Spherical Bearings come with self aligning capabilities that make it possible to absorb shocks and also enable the apparatus to carry high axial and radial load even in harsh environment with lot of vibration. Even with this rugged working environment, Roller Bearings tend to have high precision.
DESIGN
Spherical Bearings have two rows of rollers that are separated by a cage or rib that could be sealed or unsealed depending on the specific model and application, external raceway and dual raceways in inner ring to support rotating shaft. Amazingly the quality and alignment of raceways, cages and rings define the overall performance and quality of the product. Asymmetrical rollers increase performance and precision while symmetrical rollers offer better load distribution, lesser vibration that ultimately leads to durability.
MATERIAL
These Bearings are manufactured with several kind of material based on the application and working environment. Chrome steel is one of the most popular materials used in production of these Bearings because of its durability yet sheet steel, polyamide and brass are also used for some applications. One of the most important parts of Spherical Bearings is the cage that holds bearings at their place. That cage is usually manufactured with pressed steel or brass because both of these materials offer strength as well as temperature resistance.
These Bearings tend to have seals in order to prevent contaminants like dirt, liquid, debris as well as harsh temperature. This type of these bearing doesn`t even need lubrication if they do not exceed 50% of their maximum allowed RPM.
APPLICATIONS
Spherical Bearings are essential part of heavy machines like gearboxes, turbines, mechanical fans, constructions equipment, mining equipment and drilling equipment. Roller Bearings are available in multiple standard sizes and dimension yet they are also made with custom sizes and specifications.
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MODELS AND VARIATIONS
Usually these Bearings come in two different types that have totally different design, structure, specifications and applications.
Single Row Spherical Roller Bearings
These are also known as Barrel Bearings because of their design and they are widely used where only low radial load carrying capacity is required. Other than the load capacity difference, Single Row these Bearings is quite similar to their counterpart in terms of performance and durability.
Double Row Spherical Roller Bearings
These are used where high radial load carrying capacity if required and that make them an essential part of almost all heavy duty machinery out there. The design difference between these two is obvious; Double Row Roller Bearings come with central flanges that optimize the overall performance of the apparatus.
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