公开(公告)号：US12159090B2

公开(公告)日：2024-12-03

申请号：US17338990

申请日：2021-06-04

Applicant: North China Electric Power University ,  State Grid Electric Vehicle Service Ltd.

Inventor： Dunnan Liu ,  Mingguang Liu ,  Xiaofeng Peng ,  Heping Jia ,  Wen Wang ,  Lingxiang Wang ,  Mengjiao Zou ,  Yue Zhang ,  Ye Yang ,  Shu Su ,  Desheng Bai

IPC: G06F30/27 ,  B60L58/10 ,  B60L58/14 ,  B60L58/16 ,  G06F30/25 ,  G06F119/06 ,  G06N3/006 ,  G06N5/01 ,  G06N7/01 ,  G06N20/10 ,  G06Q10/0631 ,  G06Q10/0635 ,  G06Q50/06 ,  H02J3/32 ,  B60L55/00 ,  G06F111/06 ,  G06F111/08 ,  G06Q10/04

Abstract: The invention relates to an optimal allocation method for stored energy coordinating electric vehicles (EVs) to participate in auxiliary service market (ASM), including the following steps: 1. Predict the reported capacity of daily 96 points for EVs to participate in the ASM by least square support vector machine (LSSVM). 2. Fit the daily total load distribution of EVs. 3. Determine the error distribution between the reported capacity and the actual response capacity, and simulate the total daily load capacity of EVs in the future with Monte Carlo method. 4. Calculate the energy storage capacity required by EVs daily participating in ASM. 5. Build the objective function to minimize the scheduling risk of auxiliary service. 6. Solve the energy storage model in step 5 with particle swarm optimization (PSO), and output the configuration results of optimal energy storage capacity and energy storage power. The invention can improve the adjustable capacity of EVs participating in ASM.

公开(公告)号：US20220147670A1

公开(公告)日：2022-05-12

申请号：US17338990

申请日：2021-06-04

Applicant: North China Electric Power University ,  State Grid Electric Vehicle Service Ltd.

Inventor： Dunnan Liu ,  Mingguang Liu ,  Xiaofeng Peng ,  Heping Jia ,  Wen Wang ,  Lingxiang Wang ,  Mengjiao Zou ,  Yue Zhang ,  Ye Yang ,  Shu Su ,  Desheng Bai

IPC: G06F30/27 ,  G06F30/25 ,  B60L58/10 ,  G06N20/10

Abstract: The invention relates to an optimal allocation method for stored energy coordinating electric vehicles (EVs) to participate in auxiliary service market (ASM), including the following steps: 1. Predict the reported capacity of daily 96 points for EVs to participate in the ASM by least square support vector machine (LSSVM). 2. Fit the daily total load distribution of EVs. 3. Determine the error distribution between the reported capacity and the actual response capacity, and simulate the total daily load capacity of EVs in the future with Monte Carlo method. 4. Calculate the energy storage capacity required by EVs daily participating in ASM. 5. Build the objective function to minimize the scheduling risk of auxiliary service. 6. Solve the energy storage model in step 5 with particle swarm optimization (PSO), and output the configuration results of optimal energy storage capacity and energy storage power. The invention can improve the adjustable capacity of EVs participating in ASM.