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Author ：Iflowpower – Portable Power Station Supplier
my country's energy storage network news: In September 2020, my country announced in the UN General Assembly to achieve carbon-up peaks, 2060 years ago, my country's electrochemical energy storage will enter rapid growth period, expected 2020 By 2050, electrochemical reservoir installed space has approximately 400 times rising, and will reach 600 million kilowatts in 2050. How to effectively manage and operate such a large-scale battery asset will become a severe challenge. A large number of monomer batteries together form a container energy storage, due to the difference in actual parameters such as the capacity, internal resistance, open circuit voltage, etc.
Encouncing a series of questions: 1. Capacity loss: the battery cell constitutes a battery pack, the battery pack capacity is in line with the "wooden bucket principle", the worst capacity of the battery determines the capacity of the entire battery pack. In order to prevent the battery overcharge, the logic of the battery management system is set this: When the lowest monomer voltage reaches the discharge cut voltage, the entire battery pack stops discharge; when charging, when the highest monomer voltage touches the shutoff voltage , Stop charging.
Under this control logic, the capacity of the battery pack cannot be fully utilized, resulting in battery pack capacity loss. 2. Problem Battery Early Warning and Positioning: A large energy storage system will have thousands of batteries, and each battery is not attenuated.
The health status is very different. We must accurately portray the capacity of each battery, Internal resistance, voltage, temperature, etc., and can predict the battery that may have security issues in time, to ensure the overall security of the energy storage system in order to ensure the overall security of the energy storage system.
3. Battle battery capacity calculation and life prediction: With the operation of the energy storage system, the capacity of the energy storage battery will continue to decay. Although the BMS will calculate SOH, it is limited to the weakness of the BMS hardware and the limited amount of data, The calculated SOH error is large, how much is the actual capacity of the energy storage system, how many times in the future, the attenuation speed is agreed in the technical agreement of the battery, and these investors are black Box, investors unable to accurate future investment income.
4. Delivery and maintenance dispersion and cost: As the energy storage project increases, many energy storage projects are only deployed locally, and some people must stay 24 hours a day, no unified remote system for centralized operation, operation and maintenance Personnel receive alarm, can't analyze the reason for judging the alarm, the operation and maintenance consumption. Here, a series of technical problems, internal resistance, capacity prediction estimate, battery life prediction, battery life prediction, micro short circuit safety warning, battery inconsistency weight equalization, etc.
Traditional BMS can only save short time data due to the limitations of computing and storage capability, without complex computational analysis, can only complete battery monitoring data acquisition, instant charging management, etc., and weak calculations. Therefore, it is difficult to solve these technical difficulties through BMS.
In order to solve the above problems and challenges, some academic institutions and high-tech companies at home and abroad began using big data, artificial intelligence technology, combined with the superput calculation and large data storage capabilities of the cloud, and calculate and analyze massive battery data. , Intelligent diagnosis of the battery to achieve intelligent operation and maintenance. Tencent Tsinghua Joint Team relies on massive battery data in Tencent data, and constructs battery fault prediction model.
You can discover faulty batteries in advance 5-30 days. Professor Richardd.braatz Professor of the Massachusetts Institute issued a battery life prediction model, and the battery life can be predicted accurately.
The first 100-turn cycle data can be used to achieve more accurate prediction of battery life, predictive error Is only 9.1%. Many domestic and foreign universities have also been a large number of research in terms of battery pack, publish a lot of related papers.
Standardizing these battery intelligence analysis and diagnostic methods, productization, building battery asset management platforms, quickly accessing various energy storage battery assets, achieving fast intelligent analysis diagnosis and operation, and holders and operators on battery assets Will be very valuable. Wanke Energy Technology Co., Ltd.
has done multi-year technical practice and productization, commercialization in battery asset management platform, and announced this year's 2.0 version of the battery asset management platform, customers only need to access battery asset data to the platform. The battery diagnosis report can be quickly obtained, let customers have comprehensive, timelyly mastered the current health status of the future battery, and find safety risks in advance, ensuring that the battery assets have been safe and efficient, and protect the asset holder's income.
Wanke Energy also has the integrated energy intelligence operation service platform for independent intellectual property development, based on "Internet + new energy" as the concept, based on the Internet of Things, big data, artificial intelligence technology, for user-side energy storage, power supply side energy storage, power grid Side energy storage, microgrid, etc.
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