PIDS: An Intelligent Electric Power Management Platform
Author(s) -
Yongqing Zheng,
Han Yu,
Yuliang Shi,
Kun Zhang,
Shuai Zhen,
Lizhen Cui,
Cyril Leung,
Chunyan Miao
Publication year - 2020
Publication title -
proceedings of the aaai conference on artificial intelligence
Language(s) - English
Resource type - Journals
eISSN - 2374-3468
pISSN - 2159-5399
DOI - 10.1609/aaai.v34i08.7027
Subject(s) - electricity , electric power system , computer science , consumption (sociology) , process (computing) , power consumption , power management , power (physics) , electric power , demand response , business , environmental economics , operations research , operations management , telecommunications , risk analysis (engineering) , engineering , economics , electrical engineering , social science , sociology , operating system , physics , quantum mechanics
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.
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