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Energy and reserve capacity joint optimization scheduling method of integrated variable energy

A reserve capacity and joint optimization technology, applied in resources, data processing applications, forecasting, etc., can solve problems such as infeasible solutions

Pending Publication Date: 2022-07-01
ZHEJIANG HUAYUN ELECTRIC POWER ENG DESIGN CONSULTATION CO LTD +1
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

Therefore, these studies may offer solutions that are not feasible

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  • Energy and reserve capacity joint optimization scheduling method of integrated variable energy
  • Energy and reserve capacity joint optimization scheduling method of integrated variable energy
  • Energy and reserve capacity joint optimization scheduling method of integrated variable energy

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Embodiment Construction

[0061] The present invention will be further described below in conjunction with the accompanying drawings.

[0062] refer to figure 1 , a joint optimal scheduling method for energy and reserve capacity integrating variable energy, comprising the following steps:

[0063] Step 1, load prediction based on convolutional neural network

[0064] Use the convolutional neural network CNN to predict the load demand forecast results, considering the hourly load demand data of a certain region throughout the year;

[0065] Implemented through the convolutional neural network CNN, a supervised learning-based DL technique for prediction; CNN is inspired by biological processes and uses relatively less preprocessing than other classification algorithms; it Learn hand-designed filters in traditional algorithms. In order to improve the efficiency and speed of the algorithm, the selected features are refined; the CNN model is used to obtain the best load demand forecasting results and eff...

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Abstract

The invention relates to an energy and reserve capacity joint optimization scheduling method integrated with variable energy, which comprises the following steps of: firstly, predicting a load demand by real-time data per hour through a convolutional neural network (CNN); then, through integration of a renewable energy source RES and a storage battery energy storage system (BSS), combined scheduling of energy and spinning reserve capacity is realized so as to meet the predicted load demand; in addition, the power generation system punishes according to the energy demand quantity which is not met due to power generation limitation and the cost coefficient of an unserved load; meanwhile, due to the inclination of the thermal power unit, the available residual power is stored in the standby energy storage system in consideration of the charging state of the energy storage system; and solving cost minimization by adopting a particle swarm optimization algorithm. According to the invention, joint scheduling of thermal power generation and variable resources (including storage systems) is realized.

Description

technical field [0001] The invention relates to a joint optimal scheduling method of energy and reserve capacity integrating variable energy. Background technique [0002] The electrical system operator (ESO) is responsible for generating electricity, and it has to face many factors to make the system work smoothly. Typically, power systems consist of heterogeneous devices with different operating parameters. Systems are always prone to becoming more complex by integrating linear and nonlinear loads, communication devices, smart metering, distributed storage systems, security and quality improvements. These complexities increase as individual lifestyles improve and systems become more sustainable. ESOs must take responsibility for envisioning all aspects of the smooth, less vulnerable operation of the electricity market. Additionally, ESOs can handle this situation by making adjustments on the generation side, thereby providing a price-based disaster recovery plan to bala...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q10/04G06Q50/06G06N3/04
CPCG06Q10/06313G06Q10/04G06Q50/06G06N3/045
Inventor 黄海荣吴笛李振锋张帆刘臻腾晓兵郭丽婷毛毳周丹周勤刚
Owner ZHEJIANG HUAYUN ELECTRIC POWER ENG DESIGN CONSULTATION CO LTD