IBM in smart grid pilots in Shanghai and South Korea


Shanghai, China and Seoul, South Korea — (METERING.COM) — November 9, 2010 – IBM has announced its participation in smart grid pilot developments with Shanghai Electric Power Company in Shanghai and with POSCO ICT on the Jeju Island demonstration in South Korea.

The Shanghai project has involved the development of a new technology, now being piloted with Shanghai Power, to help energy companies manage power outages more effectively while improving productivity. The Integrated Distribution Outage Planner (IDOP) is an online, real time outage planning tool, which integrates data from relevant departments and processes and manages the schedule of different types of power outage tasks. Using analytics and optimization technology, the IDOP allows the power grid to draw data across the company to conduct analysis of possible factors causing outage and excessive energy consumption. It also can provide scientific arrangements of outage tasks, including the time frame and load transfer path for each outage task. This helps to minimize security risks, increase workload balance, and reduce the amount of time spent on monthly coordination of scheduled power outages from half a month to just a few days. 

Shanghai Power performs 5,000 to 6,000 maintenance tasks and tests every month. Since the project was completed earlier this year, the rate of equipment availability at Shanghai Power has increased significantly, and the company’s sale of electricity has increased by 50 million kWh per month, which is equal to an incremental revenue of 35 million Yuan (US$5.1 million) a month.

The Jeju Island project is involving the development with POSCO ICT of a renewable energy management system, which will be installed at the Smart Grid Demonstration Complex on the island. The system, which will be based on business analytics software, will enable informed decisions on power generation based on quantitative analysis. It will help establish optimum countermeasures for possible changes in energy supply and demand through a prior scenario analysis, and it will be able to integrate management efficiency initiatives and quickly propose fine-tuned plans for the management of energy.

The system, which is aimed at forecasting the electricity demand to ensure efficient and accurate production of electricity, is expected to be completed in December.