Name
Abstract | ||
|---|---|---|
Electricity information tracking systems are increasingly being adopted across China. Such systems can collect real-time power consumption data from users, and provide opportunities for artificial intelligence (AI) to help power companies and authorities make optimal demand-side management decisions. In this paper, we discuss power utilization improvement in Shandong Province, China with a deployed AI application - the Power Intelligent Decision Support (PIDS) platform. Based on improved short-term power consumption gap prediction, PIDS uses an optimal power adjustment plan which enables fine-grained Demand Response (DR) and Orderly Power Utilization (OPU) recommendations to ensure stable operation while minimizing power disruptions and improving fair treatment of participating companies. Deployed in August 2018, the platform is helping over 400 companies optimize their power consumption through DR while dynamically managing the OPU process for around 10,000 companies. Compared to the previous system, power outage under PIDS through planned shutdown has been reduced from 16% to 0.56%, resulting in significant gains in economic activities. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1609/AAAI.V34I08.7027 | AAAI |
DocType | Volume | Issue |
Conference | 34 | 08 |
ISSN | Citations | PageRank |
2159-5399 | 0 | 0.34 |
References | Authors | |
0 | 8 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yongqing Zheng | 1 | 18 | 8.94 |
| Han Yu | 2 | 639 | 48.71 |
| Yuliang Shi | 3 | 5 | 3.47 |
| Kun Zhang | 4 | 0 | 1.01 |
| Shuai Zhen | 5 | 0 | 0.68 |
| Li-zhen Cui | 6 | 282 | 71.41 |
| Cyril Leung | 7 | 899 | 62.23 |
| Chunyan Miao | 8 | 2307 | 195.72 |