Saturday, August 17, 2024

Load Forecasting- Foundational Step for Enabling Energy Transition.

 


Source- ESIG- 2023 Long Term Forecasting Workshop

The era of stagnant load growth is over. With the upcoming electrification of heat and transport driven by the need for reducing carbon emissions, our electricity consumption is forecasted to double. This forecasted electricity growth transforms the existing planning process- the electric system will change from summer peaking to winter peaking, it changes periods of resource adequacy, planning on transmission and distribution system, availability of generation resources, and everything in between. The task of identifying that the electric load will be is the task of Long-Term Forecasting process.

This Long-Term Load Forecasting is the foundational process for a utility’s operations. These long-term forecasting often look ahead 10 years in ahead in the future and anticipate what the load will be in the future. Based on this plan, the electric utility then plans for development of its infrastructure to be able to meet the electric demand. In an energy market, the load term forecasting provides the market signal the price for Forward Capacity Market, development of Transmission Planning, process for Generation Interconnection, and other processes.

Long term forecasting consists of econometric models based on historical load growth and weather, which is then adjusted based on exogenous forecasts of various factors including energy efficiency, state policy, building electrification, transportation electrification, and other trends. Proper load forecasting needs a strong understanding of the emerging trends, and how these impact the electric load in the future.

Load forecast provides future energy load, but also future demand. The demand modeling provides what the future electric peak load will look like. Using historical weather history (30+ years), a weekly weather distribution is developed that provides what is the total variance of the weather that will be in each week. For each week a Weighted Temperature Humidity Index (WTHI) is used to forecast the demand for each week.

The forecasts provide 50/50 and 90/10 load. The 50/50 load forecast is the load that has a 50% probability of the forecast will exceed. 90/10 load forecast is that there is a 10 percent probability that the forecast will exceed. In other words, the 50/50 load level is a peak demand that is expected every two years, 90/10 is the extreme weather level that is expected once every ten years. The Transmission Planners use the 90/10 peak demand data to plan the load to plan for meeting system reliability to meet all the expected peak. For other resource adequacy measure planners can use the 50/50 peak.

With the energy transition, there is a wide variability in the future load in terms of forecasted solar PV installs, energy storage system, installed wind energy, electric vehicles, and electrification of buildings. These provide a challenge in terms of being able to forecast exactly what the future load will look like. With electrification of the building, the system transitions into a winter peaking system from summer peaking system. The high adoption of solar PV transitions the daily load curve into a duck curve with a sharp peak during in the evenings. Electric Vehicles double the use of electric use.

Our society's successful energy transition relies on accurate load forecasting, providing critical insights into the future grid. This enables the integration of clean energy, resource balancing, adequate energy reserves, and robust transmission infrastructure. As the energy landscape evolves, embracing advanced technologies, distribution-level forecasting, enhanced weather forecasting, and scenario planning will be essential for accurate and reliable load forecasting.

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