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Background - The Opportunity

It's been more than a decade since deregulation of electricity markets began and although there have been some starts and stops as rules, rates and regulation evolved, Central Markets such as ERCOT, MISO, CAISO, PJM, NYISO and NEISO have slowly developed into competitive and profitable energy markets. As in most developing markets the initial rush by new entrants to gain market share and sufficient load to profitably participate in the market overshadowed the benefits of operational efficiency. But as these markets mature and more Competitive Energy Suppliers gain market share, the focused has turned toward improving operational efficiencies to maximize margins through advanced forecasting analytics.

Forecasting analytics allows Competitive Energy Suppliers to compile disparate streams of meter data, market data and other external inputs to create micro-accurate load forecasts. For Competitive Energy Suppliers, accurate profile creation, forecasting and settlements are the core analytics that impact margin optimization. Competitive Energy Suppliers need accurate forecasts to avoid exposure to volatile market clearing prices and steep imbalance penalties which could wipe out their already thin margins. To develop accurate forecasts energy retailers must consider the following components in load forecasting:

 

  • Actual historical profiles of customer accounts and/or rate class profiles

  • Regional economic swings or interruptions that impact load

  • End use load data and demand response commitments.

  • Customer expansion, contraction or scheduled outages

  • Weather impacts on heating and cooling loads or closures due to storms.

 

      

 FORrunner-input

 

Compiling all of these disparate streams of data into useful input for load profile creation and forecasting is becoming more and more complex.

 

FORrunner Forecasting Analytics - Leveraging Data to Drive Decisions
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  • Micro-accurate load forecasting and shadow settlement

  • Preconfigured solutions for ERCOT, PJM, NYISO, ISO-NE, MISO and CAISO

  • Leverages AMI data granularity to aggregate accurate near real-time load data

  • Rich GUI for intuitive data-driven decision making

  • Sandbox environment for strategic modeling

 

The FORrunner Forecasting Analytics for Competitive Energy Suppliers is an application module that integrates with Oracle Utilities - Energy Information Platform (EIP) to provide Competitive Energy Suppliers with advanced forecasting and shadow settlement capabilities. FORrunner Forecasting Analytics is a bottom-up forecasting solution that allows Competitive Energy Suppliers to create micro-accurate meter level load forecasts which can then be aggregated by customer class, delivery point, LCD or portfolio contract. The FORrunner ability to segment and aggregate loads on a micro and macro level gives PowerRunner clients the analytics they need to make data-drive business decisions. To accelerate profile creation and forecasting, FORrunner comes with preconfigured profile modules for all of the active central markets. These out-of-the-box modules allow PowerRunner to implement FORrunner Forecasting Analytics in weeks instead of months.

 

Market Optimization 

The volatility of spot market pricing, imbalance penalties and other market fees can quickly erode the thin margins of a Competitive Energy Supplier. FORrunner Forecasting Analytics can help Competitive Energy Suppliers manage these risks by creating micro-accurate load profiles and forecasts built on near real-time client load data. By leveraging the time-series interval data from the Oracle EIP, FORrunner can profile aggregated or segmented load data by delivery node, customer rate class or individual customer account. The FORrunner ability to analyze data on a granular level can provide a Competitive Energy Supplier with visibility into how variations in individual load performance can impact forecasts and potential nodal imbalances the their overall portfolio performance. 

 

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The value of FORrunner Forecasting Analytics is demonstrated in this PowerRunner client settlement analysis. After an 8-week implementation at a leading Competitive Energy Supplier, FORrunner Forecasting Analytics was generating short term forecast that were less than 1% deviation from the actual load. FORrunner Forecasting Analytics immediately improved this client’s daily scheduling and supply forecasting capabilities and significantly reduced its hourly imbalance charges. When compared to the client's previous forecasting solution FORrunner Forecasting Analytics would have saved this client over $400,000 in just one month.