Making the Wind Pay

Iowans are a hardy breed. They have to be with ice storms, floods and tornadoes part of living in America’s Heartland. Winters are snowy, summers are hot, spring and fall are gorgeous and mild – and rain or shine, the Central Iowa Power Cooperative (CIPCO) is there to supply the reliable, affordable energy that its customers need to heat their homes and light their businesses.

CIPCO is Iowa’s largest cooperative energy provider. Its 13 distribution members serve a population of nearly 320,000 rural and suburban residents and some 7,000 commercial and industrial accounts, covering a 300-mile diagonal swath from the Mississippi River in the east to the Shenandoah in the southwest. The company draws from multiple sources of electrical power, including coal, nuclear, hydroelectric, natural gas and wind. Nearly 40 percent of CIPCO’s electricity is generated from carbon-free resources. Distribution members rely on CIPCO to help them manage load growth, keep pace with burgeoning demand and adapt to an evolving regulatory climate. In turn, CIPCO relies on the power of IBM SPSS Statistics to optimize decisions on capital planning, utility rate setting, power purchases, emissions tracking and more.

Power, flexibility, and time savings
Lisa Sell, Energy Planning Manager at CIPCO, views Statistics as an essential business tool for analyzing data and driving decision-making for the cooperative. “It really is a time saver for us,” she says. “Many large power companies have entire departments dedicated to analysis and forecasting, but we don’t have that luxury at CIPCO. Our small group really values the efficiency that we get from analyzing our data with IBM SPSS Statistics.”Power generation and distribution is a complex affair. CIPCO is required to sell its power into the Midwest Independent System Operator (MISO) market, which then resells the power to ensure unbiased regional grid management and open access to transmission facilities. MISO acts as the master dispatcher, continually reviewing loads across the entire system and adjusting resources to ensure a consistent power supply. CIPCO needed a way to track MISO pricing streams for 3,000 power nodes – power plants, power units, wind farms and the like – and assess the related profitability profile.

This set of tasks involves a large dataset (currently estimated at more than 2 GB) that is downloaded and aggregated daily. The price from each power node changes hourly, depending on load and congestion factors. Says Sell: “If we had stayed with Excel, we would be paralyzed by the mass of data. IBM SPSS Statistics gives us the power and flexibility to keep track of everything, with very little manual manipulation.” Since writing the initial syntax, Sell and her team have continued to expand their use of the product into many new areas.

Projecting future scenarios
The wind that blows across Iowa’s tallgrass prairies has given rise to a fast-growing wind farm industry. But a variety of factors – including natural disaster, economic recession and load-based plant curtailment by MISO – can affect the demand for and consumption of energy. Sell uses Statistics to analyze the dynamic pricing of wind-generated energy and its effect on the rest of the system. “We can understand what’s happened in the last few months, and use that to project possible future scenarios,” she says. “Accuracy in forecasting affects CIPCO’s margins and bottom line, so quantifying the data is extremely important.”Statistics also supports the huge job of year-end power generation and cost reporting to government agencies. Sell uses the software to compare the reported figures to the hourly prices from MISO. “This comparison tells me how profitable a given plant was during any hour, day or month,” she explains. A related piece of financial analysis – comparing the prices CIPCO receives from selling its power to the cost of running its infrastructure – becomes an important factor in decisions regarding plant capacity and modernization.

Regulatory compliance is a major issue for today’s energy companies. With “greenhouse” legislation pending in Congress and Environmental Protection Agency (EPA) rules already on the books, CIPCO must be able to accurately track its power plant emissions. Also critical is the ability to forecast the price of allowances and develop appropriate strategies to optimize business outcomes. Here again, Statistics proves its worth as a powerful engine for analyzing emissions data, threshold levels and related financial consequences – all of which helps guide company strategies. For example, one possible outcome of this analysis might be a shift in the company’s power generation profile to more environment-friendly sources.

Streamlining analysis
The evolution from Excel to Statistics has had a positive impact on the overall efficiency of Sell and her team, allowing them to streamline and accelerate their analysis. Says Sell: “Now that we have more time, we can handle many more tasks – and in much greater depth – than we could before.” Analyses done with Statistics support general resource planning, including forward-looking power purchases based on pricing streams and load forecasts. The software also provides critical guidance in areas as diverse as fuel purchases, contract negotiations, future capital needs, capacity development and rate design based on peak usage. At the end of each month, the master fuel forecast pulls in a variety of fuel forecasts from one of CIPCO’s sources. “Because the prices change on a seasonal basis, the color-coded graphs that we generate in IBM SPSS Statistics are particularly valuable,” says Sell. “They make it easy to visualize and understand the need to make forward power purchases in the face of extreme price volatility.”

Sell adds that Statistics makes it easy to customize charts and graphs to emphasize key indicators for the benefit of engineers and executive management. “The graphing capabilities of IBM SPSS Statistics definitely help, especially the IBM SPSS Custom Tables add-on. Once you work with your dataset and determine the optimal graph, you can paste it right into the syntax. The next time, you can just rerun it; you don’t have to recreate it from the beginning. In Excel, we would need to rebuild the graph each time, so this feature of IBM SPSS Statistics has really saved us a lot of time.”

Actionable information
IBM SPSS Statistics is easy to use. Says Sell: “The beauty of the software is that you don’t need a statistical background in order to really exploit its value. It turns data into actionable information without the need to understand complex statistical formulas. It’s also very easy to program, with color coding that lets you know immediately if you’ve made an error. This is especially helpful when you’re first starting to use the product.”Statistics provides timely and in-depth analysis of the data on which CIPCO runs its successful business, and it saves a significant amount of time for the analysts. “It takes me two seconds each day to press ‘Run’ and pull in the new MISO data,” Sell concludes. “If I didn’t have IBM SPSS Statistics, I don’t know how I would do my job. I think it’s fair to say that IBM SPSS Statistics has been truly transformational here at CIPCO.”