Energy storage optimal configuration method based on user side BESS full life cycle

A technology with full life cycle and optimized configuration, which is applied in the energy industry, circuit devices, data processing applications, etc., can solve the problem that the typical day loses the meaning of the typical day, does not fully consider the sensitivity of the initial value of the user-side configuration energy storage benefit, nonlinearity And other issues

Pending Publication Date: 2021-03-16
国网重庆市电力公司营销服务中心 +2
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Problems solved by technology

[0005] In the patents disclosed above, when constructing the optimal allocation model of energy storage, they did not fully consider the benefits of energy storage configuration on the user side and the sensitivity of the initial value in the process of obtaining typical days. meaning, and the problem being solved is either a nonlinear problem, or a mixed integer programming problem that has been converted into a linear problem

Method used

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  • Energy storage optimal configuration method based on user side BESS full life cycle
  • Energy storage optimal configuration method based on user side BESS full life cycle
  • Energy storage optimal configuration method based on user side BESS full life cycle

Examples

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Embodiment 1

[0084] Such as figure 1 As shown, the energy storage optimization configuration method based on the user-side BESS life cycle includes the following steps:

[0085] Step 1. Data preparation: set energy storage cost parameters and characteristic parameters, upload real-time electricity price data and one-year historical load data of large industrial users, and restore the load data to 12-month load data, 55 of which were selected in this application The user conducts test processing;

[0086] Step 2. Acquisition of typical days: Use Fuzzy C-Means to cluster the load data of each month to obtain the cluster center, use the cluster center as the typical daily load curve of the current month, and output the monthly load data of the cluster center at the same time The weight to account for the number of days in the month.

[0087] Step 3. Selection of optimal configuration model constraints: select state of charge (SOC), energy storage SOC continuity constraints, SOC cycle initia...

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Abstract

The invention discloses an energy storage optimal configuration method based on a user side BESS full life cycle, and relates to a power and capacity optimal configuration technology of a battery energy storage system and a Fuzzy C-Means clustering method in the field of machine learning. The method comprises the steps of data preparation, typical day acquisition, optimal configuration model constraint condition selection, user-side energy storage optimal configuration model establishment and evaluation index selection and solution, a Fuzzy C-Means clustering method is used for typical day selection, an obtained clustering center is taken as a typical day, and a fuzzy membership degree is assigned to each class cluster for each data point and iteratively updated. The clustering result is stable, the volatility is small, the initial value sensitivity is low, in the model solving process, the model is ingeniously converted into an LP problem, the solving speed is high, the obtained solution is a globally optimal solution, and the example result shows that the model has high practical significance, and the commercial development of energy storage can be effectively promoted.

Description

technical field [0001] The present invention relates to the power and capacity optimization configuration technology of battery energy storage system and the FuzzyC-Means clustering method in the field of machine learning, in particular to the energy storage optimization configuration method based on the user-side BESS full life cycle. Background technique [0002] Energy storage configuration and operation optimization are divided into grid side and user side. At present, the penetration rate of new energy in the power grid is gradually increasing, and the power generation output of new energy represented by wind power and photovoltaic has strong volatility and uncertainty. Therefore, it plays an increasingly important role in the power system. However, the cost of configuring energy storage is very high, and the energy storage configuration on the user side is often distributed, and it is difficult to form a scale effect to reduce costs. These reasons make energy storage ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06G06K9/62H02J3/00H02J3/32
CPCG06Q10/04G06Q50/06H02J3/008H02J3/32H02J2203/20G06F18/23213Y02P80/10Y02E40/10
Inventor 龙羿龙方家何锦华胡泽春黄会吴高林徐鸿宇胡文汪会财徐婷婷池磊
Owner 国网重庆市电力公司营销服务中心
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