Peak Energy Load Management System for Cities (PELMS) 

Background:

This document presents the Peak Energy Load Management System (PELMS), an approach to forecasting and managing citywide energy demands during extreme heat and cold events. Traditional methods rely on limited weather data and aggregated historical demand records, which often prove insufficient in rapidly changing conditions and densely urbanized areas. By integrating high-resolution urban weather modeling and building energy simulations, PELMS aims to more accurately capture how the urban heat island phenomenon, varied building types, and other local factors drive spikes in energy use. These spikes, already substantial under current climate patterns, are likely to escalate as heat waves increase in frequency and intensity throughout this century.

Industry Need:

Utilities, city authorities, and energy service providers face mounting challenges related to peak demand, especially during prolonged heat waves that can overload local grids. Current forecasting tools often lack the granularity required to address demand at the neighborhood or substation level, leading to reactive rather than proactive load management strategies. By refining forecast accuracy and incorporating renewable energy variables—such as rooftop solar potential—PELMS offers a practical pathway for reducing both the operational risk of blackouts and the financial costs of emergency measures.

Objectives:

The primary objectives include creating a fine-scale peak load forecast system for extreme conditions in urban environments (initially New York City), adjusting forecasts dynamically to minimize disruptions across the distribution system, and developing a user-friendly dashboard to relay actionable insights. Further goals include demonstrating measurable benefits in real-world scenarios, such as preventing costly demand-response events, and extending PELMS to other major cities through collaboration with utility partners and licensing opportunities with private-sector ventures.

Methodology:

PELMS combines a numerical weather prediction system with multi-layer urban parameterization and integrated building energy models, a process referred to as uWRF. This coupled framework captures interactions between atmospheric conditions and the urban fabric—e.g., building morphology, land use, rooftop solar capacity—to produce demand forecasts at 1 km resolution or finer. By separating weather-dependent energy usage from the baseline load and augmenting these forecasts with real-time data from utilities, the system provides short-term (72-hour) and longer-range projections of peak load intensity and timing. Multiple data sources, including high-resolution land-use and tax-lot records, ensure accurate representation of building stock and urban infrastructure.

Deliverables:

The project culminates in a practical peak load forecasting tool that can be seamlessly integrated into utility operational systems, enabling them to plan for and respond to extreme weather events with greater agility. Stakeholders will gain access to hourly forecasts of demand at the substation level, complete with suggested interventions such as demand shifting, energy storage utilization, or rooftop solar deployment. In addition to a patent filing and peer-reviewed publications, these forecasts will be validated through pilot implementations, laying a foundation for broader deployment in various urban settings.