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Unit commitment optimization method considering new energy consumption

A technology of unit combination and optimization method, which is applied to AC networks with energy trade/energy transmission authority, power generation prediction in AC networks, AC network circuits, etc., can solve the same or similar problems that have not been found, and achieve a solution Vulnerability issues and the effect of improving grid connection efficiency

Pending Publication Date: 2022-03-18
ELECTRIC POWER SCI & RES INST OF STATE GRID TIANJIN ELECTRIC POWER CO +2
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  • Application Information

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Problems solved by technology

[0003] After searching, no documents of the prior art identical or similar to the present invention were found

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  • Unit commitment optimization method considering new energy consumption
  • Unit commitment optimization method considering new energy consumption
  • Unit commitment optimization method considering new energy consumption

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Embodiment Construction

[0061] Embodiments of the present invention are described in further detail below:

[0062] In the grid environment where a large number of new energy sources are connected, the present invention proposes a unit combination optimization method considering new energy consumption, builds a dynamic model of new energy consumption, and realizes the prediction of the power generation of new energy units based on the LSTM network , and transform the unit combination problem into a Markov decision process. Divide new energy power generation into six typical characteristics, build parameter adaptive agents based on these characteristics and train agents based on historical power grid operation data, and obtain unit output plans that meet the goal of new energy consumption.

[0063] A unit combination optimization method considering new energy consumption, such as figure 1 shown, including the following steps:

[0064] Step 1. Construct a dynamic evaluation model for new energy consu...

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Abstract

The invention relates to a unit commitment optimization method considering new energy consumption. The method comprises the following steps: step 1, constructing a day-ahead new energy consumption dynamic evaluation model; step 2, predicting the short-term generating capacity of the new energy unit based on an LSTM neural network, including preprocessing historical data and completing prediction of the generating capacity of the new energy unit by using the LSTM neural network; step 3, converting a unit commitment problem into a Markov decision process, including design of a power grid state st, an action at, a reward value Rt and a transfer function; and step 4, according to the historical operation data characteristics of the power grid, intelligent agent construction is completed based on a parameter adaptive neural network, an intelligent agent is trained, and a unit output plan meeting a new energy consumption target is obtained. According to the invention, the stability of a novel power system taking new energy as a main body can be improved, efficient utilization of clean energy is realized, and consumption of the new energy is completed on the premise of reliable operation of a power grid.

Description

technical field [0001] The invention belongs to the technical field of self-adaptive real-time dispatching of power systems, and relates to a unit combination optimization method, in particular to a unit combination optimization method considering new energy consumption. Background technique [0002] The new power system is based on new energy, supported by source-grid-load-storage interaction and multi-energy complementarity, and has the basic characteristics of clean and low-carbon, safe and controllable, flexible and efficient. The new power system has developed rapidly in recent years, but there are relatively few domestic and foreign researches on energy supply, safe operation and clean consumption. The control problem of the new power system has been transformed from a single optimization problem to a multi-layer, multi-region and multi-objective optimization problem in complex scenarios. Traditional dispatching methods first mathematically model the unit combination ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H02J3/00H02J3/46H02J3/48
CPCH02J3/004H02J3/466H02J3/472H02J3/008H02J3/48H02J2203/20H02J2203/10
Inventor 马世乾吴彬郝毅刘伟王天昊韩磊崇志强李昂张志军董佳黄家凯郭凌旭陈建商敬安穆朝絮徐娜韩枭赟
Owner ELECTRIC POWER SCI & RES INST OF STATE GRID TIANJIN ELECTRIC POWER CO
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