看看这个：监管解决方案以实现大型负载的更好预测(英译中)

Investment Rating - The report indicates a positive outlook for the electricity demand sector, with utilities revising their load forecasts upward, projecting a 20% increase in load from 2023 to 2035 [10][27]. Core Insights - The report emphasizes the need for improved load forecasting practices to manage the risks associated with underestimating or overestimating electricity demand. Accurate forecasting is crucial for ensuring affordability and reliability in the energy sector [14][41]. - The emergence of new large loads, such as data centers and industrial electrification, presents unique challenges for load forecasting, necessitating the integration of these characteristics into modern forecasting processes [15][62]. Summary by Sections Executive Summary - Electricity demand in the U.S. is beginning to grow after decades of stagnation, with utilities expecting a 20% increase in load from 2023 to 2035 [10][27]. Load Growth and Forecasting - Utilities have significantly increased their peak load forecasts, with projections rising from an expected 23 GW to 128 GW between 2022 and 2024 [27]. - The report highlights that load forecasting is foundational for utility investment decisions, impacting the reliability and affordability of energy services [34][37]. Risks of Underestimation and Overestimation - Historical data shows that utilities have systematically overestimated electricity demand, with an average overestimation of 8% in five-year forecasts and 17% in ten-year forecasts from 2006 to 2023 [43][47]. - The report identifies the risks associated with both underestimating and overestimating load forecasts, which can lead to affordability issues and reliability challenges [49]. Load Characteristics and Their Importance - New large loads, particularly from data centers and industrial sectors, require specific considerations in forecasting due to their unique operational characteristics and flexibility potential [55][62]. - The report outlines the importance of understanding load shape, forecasting uncertainty, flexibility potential, and flight risk in the context of new load types [56][58]. Best Practices for Load Forecasting - The report suggests several best practices for improving load forecasting, including scenario-based forecasting methods and integrating terminal demand forecasts with econometric predictions [19][20]. - It emphasizes the need for utilities to adopt a more dynamic approach to forecasting that reflects the rapid changes in load characteristics and market conditions [22][24]. Regulatory Actions to Improve Forecasting - Regulatory bodies are encouraged to enhance their understanding of new loads and revise planning guidelines to incorporate emerging forecasting practices [24]. - The report outlines a series of actions that regulators can take to ensure that load forecasts align with the evolving energy landscape [24][25].