WebSTLF

webSTLF is a web-delivered short-term load forecasting tool developed by PowerAnser Labs (PAL) that provides utilities with accurate, automated, and accessible load predictions essential for efficient power system operation. Utilizing a Software-as-a-Service (SaaS) model through PAL’s innovative webDNA platform, webSTLF offers multiple forecasting engines including stochastic time series models, artificial neural networks, and expert systems. The tool supports flexible forecast intervals and horizons, automated data handling, and comprehensive analytics, all accessible via a rich web interface. By reducing forecasting errors and operational overhead, webSTLF enables utilities to optimize generation scheduling, reduce costs, and maintain system reliability in deregulated electricity markets.

Problem Statement

Short-term load forecasting (STLF) is vital for balancing electricity supply and demand within time frames ranging from minutes to days. Accurate STLF helps utilities plan generation, manage reserves, and schedule maintenance, minimizing operational costs and ensuring grid stability. However, many utilities lack automated, scalable forecasting tools that integrate seamlessly with their operations, often relying on manual processes or proprietary software with high maintenance costs. The need for a reliable, easy-to-use, and remotely accessible STLF solution is critical, especially as power systems become more complex with renewable integration and deregulation.

Salient technical feature(s)

Web-Based Delivery: Eliminates the need for local data servers and software installation, reducing IT overhead and enabling anytime-anywhere access.
Diverse Forecasting Engines: Incorporates ARMA, ARIMA, ANN, expert systems, and hybrid models to suit diverse load patterns and data sets.
Customizable Forecasting: Users can specify forecast intervals (5, 15, 30, 60 minutes) and forecast horizons up to one week, with unlimited scenario simulations.
Data Repository: Secure storage of historical load data maintained by PAL, with easy import/export functionality.
Comprehensive Analytics: Includes MAPE calculation, statistical summaries, outlier detection, and special holiday modeling for improved forecast accuracy.
User-Friendly Interface: Interactive graphical and tabular displays facilitate detailed analysis and decision-making.
Expert Support: On-demand consultation from PAL’s domain experts ensures optimal use and continuous improvement.

Prototype Details

webSTLF is implemented as a cloud-hosted web application built on PAL’s proprietary webDNA framework, which leverages modern web technologies and open industry standards to deliver complex power system applications efficiently and securely over the internet. The system integrates multiple forecasting engines that can be dynamically selected or combined based on the utility’s load data characteristics. Historical load profiles and related data are stored in a centralized repository maintained by PAL, ensuring data integrity and availability. The user interface provides real-time access to forecasting results, statistical analyses, and scenario management tools. The platform supports data import/export in MS Excel format, enabling seamless integration with existing utility workflows. The SaaS delivery model removes the need for utilities to maintain dedicated servers or software, significantly reducing overhead costs and simplifying deployment.

Societal Impact

By providing utilities with accurate and accessible short-term load forecasts, webSTLF supports economic and reliable power system operation. It reduces reliance on expensive reserve generation, facilitates renewable energy integration, and enhances grid stability. These benefits contribute to lower electricity costs, improved environmental outcomes, and increased energy security for society.

Applications