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Небесная энциклопедия

Космические корабли и станции, автоматические КА и методы их проектирования, бортовые комплексы управления, системы и средства жизнеобеспечения, особенности технологии производства ракетно-космических систем

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Мониторинг СМИ

Мониторинг СМИ и социальных сетей. Сканирование интернета, новостных сайтов, специализированных контентных площадок на базе мессенджеров. Гибкие настройки фильтров и первоначальных источников.

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Поддерживает ввод нескольких поисковых фраз (по одной на строку). При поиске обеспечивает поддержку морфологии русского и английского языка
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Применить Всего найдено 3. Отображено 3.
15-08-2023 дата публикации

Typical scene integrated energy system planning method and system based on energy concentrator

Номер: CN116596204A
Автор: GAI CHAO, ZHANG KAI, LIN HUA, WU PENG, LI ZAIZHONG, SUN KANGNAN, CHEN JIA, YANG KAI
Принадлежит:

The invention provides a typical scene comprehensive energy system planning method and system based on an energy concentrator. The method comprises the following steps: acquiring annual electricity-heat-gas load and wind-light prediction data of a typical scene; constructing an energy framework of the industrial park integrated energy system in each typical scene based on the obtained data, analyzing energy configuration conditions of each system in different scenes, matching power supply equipment and coupling equipment for different scenes, and establishing an energy coupling model of each subsystem of the integrated energy system; on the basis of the energy coupling model of each subsystem, a regional integrated energy system planning model based on the energy hub theory is established in combination with integrated demand response; and solving the regional integrated energy system planning model to obtain the commissioning capacity and the commissioning age limit of the planning equipment ...

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Номер записи: 1
16-05-2023 дата публикации

Offshore wind power reactive compensation optimization calculation method and system based on power factor

Номер: CN116131276A
Автор: ZHENG HAICUN, LIU YI, LI ZHANJIANG, CHENG WEI, CHEN LIZHI, GAO SHANBIN, LI YINUO, SUN FENGJIA, XIE HONGLONG, GAI CHAO, XU JING, TANG PENG, LI BO, PENG DONGYU, CHU YINHE, LI NA, WANG CHENGYU, SONG XINJIA
Принадлежит:

The invention belongs to the technical field of reactive compensation, and particularly relates to an offshore wind power reactive compensation optimization calculation method and system based on a power factor, and the method comprises the steps: obtaining a fan type and an operation state of an offshore wind turbine generator; constructing an offshore wind power equivalent model according to the obtained fan type and the operation state; based on the constructed equivalent model, determining the AC bus voltage of the flexible DC transmitting end converter station; judging a selection range of a fan power factor according to the obtained alternating current bus voltage; and according to the selection range of the fan power factor, reactive vacancy fluctuation of the offshore wind turbine generator is calculated, and reactive compensation of the fan is configured.

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Номер записи: 2
14-04-2023 дата публикации

Electricity price prediction method based on neural network and pattern recognition

Номер: CN115965401A
Автор: QIAN JIANAN, CAI NING, GAI CHAO, ZHAO KUN, LIN HUA, ZHAO JUN, SHI JIE, TAN YIMING
Принадлежит:

The invention discloses an electricity price prediction method based on a neural network and pattern recognition. The electricity price prediction method specifically comprises the following steps: S1, acquiring an electricity market characteristic value; s2, performing data preprocessing on the power market feature values, including missing value fitting and normalization processing, to form a preprocessed feature value data set; s3, constructing an improved BP neural network model and a pattern recognition model, respectively inputting the normalized characteristic value data set into the neural network model and the pattern recognition model for training, and respectively obtaining an improved BP neural training network and a pattern recognition training network; s4, obtaining the electricity market characteristic value of the prediction date, and performing training to obtain an electricity price prediction result of the prediction date; according to the method, empirical reference ...

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Номер записи: 3