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An Online Strategy Matching and Collaborative Optimization Method for Optical-storage Integration Based on Big Data Analysis

A collaborative optimization and big data technology, applied in photovoltaic power generation, AC network load balancing, AC network circuits, etc., can solve problems such as large instantaneous power fluctuations, power supply reliability, and negative impacts on stable power quality, and achieve mitigation Negative impact, taking into account stability and economy, and high timeliness effect

Active Publication Date: 2020-06-09
NANJING INST OF TECH
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AI Technical Summary

Problems solved by technology

However, the randomness and uncertainty of photovoltaic power generation make it very easy for the photovoltaic system to generate large instantaneous power fluctuations during grid-connected operation, which will have a negative impact on the reliability, stability and power quality of power supply.

Method used

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  • An Online Strategy Matching and Collaborative Optimization Method for Optical-storage Integration Based on Big Data Analysis
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  • An Online Strategy Matching and Collaborative Optimization Method for Optical-storage Integration Based on Big Data Analysis

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Embodiment Construction

[0028] The present invention will be further described below in conjunction with the accompanying drawings.

[0029] Such as figure 1 Shown is an online strategy matching and collaborative optimization method based on big data analysis, including the following steps:

[0030] S1. Analyze historical load big data, use weather, working days and holidays as attribute vectors, and cluster annual historical load big data according to the fuzzy C-means clustering algorithm;

[0031] S2. Classify each attribute vector value according to the clustering result;

[0032] S3. Taking season, weather, working days / holidays, and local peak and valley electricity prices as factors, considering the value of different factors, and aiming at the maximum daily income of energy storage, select more than five groups of factor value combinations as a plan;

[0033] S4. Initially match each scenario with the clustered classification to form an initial control strategy for each scenario;

[0034] ...

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Abstract

The invention discloses an integrated online strategy matching and collaborative optimization method based on big data analysis. Starting from the practical application of collaborative optimization of solar energy and storage, comprehensively considering seasons, weather, and load conditions and combining peak and valley electricity price policies, reasonable adjustment of storage The charging and discharging working state of energy can be fully utilized, and the characteristics of high energy storage timeliness and fast charging and discharging speed can be fully utilized. Through the analysis and clustering of historical load big data, five control plans are formulated, and combined with online real-time matching strategies, real-time adjustments are made to the plans that do not meet the actual situation. The invention not only alleviates the negative impact caused by the randomness and uncertainty of photovoltaic power generation, but also improves the synergy level of the photovoltaic storage system, taking into account the stability and economy of the system, and provides a more reliable method for researching photovoltaic storage synergy optimization.

Description

technical field [0001] The invention relates to an online strategy matching and collaborative optimization method for optical storage integration based on big data analysis, which belongs to the optical storage collaborative optimization technology. Background technique [0002] With the decreasing cost of photovoltaic power generation, it has become a development trend for large-scale photovoltaic systems to be connected to the grid. However, the randomness and uncertainty of photovoltaic power generation make it very easy for the photovoltaic system to generate large instantaneous power fluctuations during grid-connected operation, which will have a negative impact on the reliability, stability and power quality of power supply. The energy storage device has the characteristics of high energy, flexible installation, and fast charging and discharging speed. In the system, it can play the role of voltage and frequency regulation, power grid fault recovery, and power quality ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H02J3/38H02J3/32
CPCH02J3/32H02J3/383Y02E10/56
Inventor 陈光宇张仰飞任微逍郝思鹏王泽宇叶宇成李超杰
Owner NANJING INST OF TECH
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