Korea Power Exchange makes faster decisions with SAS® Business Analytics

The nonprofit Korea Power Exchange ensures the fair and transparent management of the country’s power market. With SAS Business Analytics, consolidated data allows staff members to create reports in a fraction of the time it once took. The result: The Exchange can do its job to keep electricity prices low and transmission standards high.

Electricity exchanges are critical to efficiently and cost-effectively managing power supplies in a free market. They are increasingly replacing the highly regulated model that many countries used for more than a century. Power producers and users buy and sell energy through the exchange with the exchange ensuring that prices don’t skyrocket nor do end users suffer outages from too little power. The exchange also analyzes power consumption to provide government and industry with economic and usage trends. Is a slump in power demand foreshadowing an economic slowdown? Should producers build more power plants to meet demand in another region?

Facing unique challenges
Electricity exchanges face unique challenges. Electricity is difficult to store. And while a shortage in shoes or apples isn’t catastrophic, a power interruption can have serious adverse consequences on users (particularly manufacturers). To maintain a transparent market, the 8-year-old Korea Power Exchange needed to first be able to make decisions faster and then perform comprehensive analysis. But with data spread across numerous silos neither goal was possible. Analysts would go from one database to another, hunting for data. Making decisions about the entire marketplace was difficult and time-consuming. It took too much time to produce the weekly, monthly, quarterly and yearly reports that the exchange relies on.

Within five months of purchasing SAS the organization had a single consolidated view of its data – showing supply and demand in real time. The project worked so well that the exchange added an analytics component a year later. The database is about two terabytes in size and with SAS, the exchange can extract and load 400 records every two seconds. There is no need for a master key to generate this unified database (which gets data from three different sources).

"By consolidating data, we have reduced time and expense,’’ explains Young-min Choi, Manager of the Software Management Team for the Information Technology Department at Korea Power Exchange. Data from three systems is extracted in real time to generate a unified database. “Before SAS, users had to access data from separate systems to find information they wanted. But now, we can freely share the information in a single infrastructure."

Data consolidation, easy of use critical to KPX
KPX met with several solution providers and chose SAS because of the ability to consolidate and manage the extract, transform and load process and the BI capabilities for getting the data into the hands of users. SAS Business Analytics helps the organization create regular and ad hoc reports, unstructured scenario analysis, and advanced statistical analysis to automate operation reporting. Data can be ported to Microsoft Word, Excel and PowerPoint documents.

SAS provides the Exchange with critical centralized metadata management capability. It also allows the staff to effortlessly back through the data to find problems or errors. This aspect increases staff insight and help them make the right decisions.

Reports that once took two weeks to produce now take two hours. “The biggest change is users can see the data on their own computer. With the previous system, it was pretty hard to do that. You had to go to individual consoles or request the data from the computing manager. But now, users can get a large amount of data easily and conveniently," Choi says. The organization must provide monthly and quarterly statistical information to a government authority – and the type of information requested changes slightly each time. While it was taking two to three weeks to prepare this information, it now takes a few days.

The analytics capability is particularly critical. The exchange was previously limited to the statistical functions available in Excel. It can now use functions like time series forecasting in SAS to create more reliable forecasts for electricity demand. Before introducing SAS, statistical data on electricity was produced using the statistical functions available in Excel. Since SAS was adopted, it has been possible to leverage various statistical functions and time series forecast data provided by SAS, which has enhanced the reliability of the electricity demand forecast.

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