Start of Demonstration Experiment for Base Station Power Rescue System Using Electric Vehicles

Supplying Reliable and Safe Communication Services with Speedy Power Supply throughout Power Outages through AI-Based Dispatch Planning

WEBWIRE — Monday, January 15, 2024

NTT DOCOMO, INC. (hereinafter described as DOCOMO), NIPPON TELEGRAPH AND TELEPHONE CORPORATION (NTT), and NIPPON CAR SOLUTIONS CO., LTD. (NCS) will begin a presentation experiment, as part of their boosted catastrophe reaction steps including reacting to power blackouts. This experiment concentrates on a base station power healing system making use of electrical automobiles (EVs).

The system for this experiment consists of DOCOMOs Energy Management System (EMS) platform for tracking and managing base station power, NTTs AI-based automobile dispatch preparing produced utilizing deep support finding out *1and real-time EV information (consisting of place, kept power, and driving information) gathered by NCS. The goal is to effectively dispatch efficiently situated and charged EVs to power-downed base stations. This recognition will occur from January 12 to June 30, 2024. NTT is a member of the EV100 effort *2and this presentation experiment is performed as part of the efforts efforts.

Throughout power interruptions, base stations presently offer interaction services utilizing backup batteries for a restricted time and release generators for prolonged blackouts. This experiment intends to boost catastrophe action by efficiently utilizing EVs, which are anticipated to end up being more typical as business cars.

This effort will be showcased at the docomo Open House24 hosted by DOCOMO, beginning January 17, 2024.
(https://docomo-openhouse24.smktg.jp/public/application/add/32

1. Deep support knowing is a mix of support knowing and deep knowing.
2. EV100 is a global effort focused on promoting using electrical cars and associated facilities amongst companies. In 2018, NTT ended up being the very first telecom operator to sign up with the effort.

Appendix

Summary of the Demonstration Experiment

1. Function

To examine the effectiveness of the EV-based base station power healing system in dispatching ideal EVs for fast power supply to power-downed base stations.

2. Experiment Details

Experiments imitating power interruptions will be carried out to examine and recognize difficulties in the base station power healing system. These consist of:

• Producing dispatch prepare for each EV on the basis of base station info and EV information, replicating a wide-area power failure in Chiba Prefecture and verifying the efficiency of the AI-based dispatch preparation by in fact driving the EVs based on the strategies.
• Evaluating whether the base station batteries charge as anticipated throughout the organized power supply from the EVs and examining the performance of the power supply strategy established by the EMS platform.

3. Technologies Used in the Experiment

The experiment will use the following innovations:

EMS Platform

• Keeps an eye on the charge status of each base station and creates power supply strategies.
• Controls effective direct present power supply after linking EVs to base stations.

AI-Based Dispatch Planning

• Creates paths for numerous EVs to accomplish prompt arrival at base stations before their batteries diminish and to reach charging stations before the EVs own battery goes out.
• Accelerate conventional path generation problems through the application of deep support knowing.
  Referral:https://ntt-dkiku.github.io/rl-evrpeps/

EV Data

• Gathers info such as the area, saved power, and driving information of each EV.
• Offers access to and distributes gathered information.

4. Experiment Period

January 12 to June 30, 2024.

5. Functions of Each Company

DOCOMO

• Preparation and total management of the experiment.
• Supplying power-sharing innovation in between base stations and EVs; examining the driving outcomes of the EVs.

NTT

• Offering the path generation innovation and AI-based dispatch preparing for effective EV flow.
• Taking a look at difficulties for enhancing precision and functionality of the path generation innovation and AI dispatch preparation.

NCS

• Gathering and offering EV details
• Analyzing difficulties associated with the arrangement of EV details.

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