In dense urban environments, thermal comfort is shaped by highly local conditions like shade, wind, and surface material that citywide weather forecasts often miss. Comfort NYC was built to close that gap.

Developed by the KPF Design Technology team, Comfort NYC is a real-time simulation-driven digital twin of Bryant Park that maps thermal comfort at the human scale. The system integrates spatial data, environmental simulations, and live meteorological inputs into a unified, cloud-based computational framework. High-resolution geometry drives predictive models of wind, radiation, and thermal load, producing continuous comfort metrics refreshed daily.

Results are delivered through an interactive web interface. The goal is a practical answer to a simple question: where in the park is it pleasant to be right now?

Comfort NYC is both a working tool and a proof of concept, with an approach scalable to other parks, plazas, and urban environments.

When considering decarbonizing 200+ buildings, where do you start? This was the challenge faced when a state client set out to eliminate on site emissions from all of their government-owned building portfolio. Building energy models could help inform the most cost effective decarbonization pathways, but making detailed energy models for each building would be expensive and time consuming. Instead, a few strategic detailed models can inform design decisions by providing key insights.

The suite of buildings were divided according to priority, building type, and mechanical systems. From there, building energy models were created for the top priority buildings, and calibrated to three years of past data. Energy conservation measures, controls updates, and full HVAC upgrades were modeled and considered. Based on insights from the priority buildings, the remaining buildings were categorized, evaluated, and solutions recommended. Past building energy data unlocked site-specific insights, and the efficiency gains from decarbonization. This method allows for both detailed analysis, and for providing solutions for all the relevant buildings. Order-of-magnitude cost estimating for the decarbonization solutions also help provide an outlined budget. This presentation will discuss both process and findings from this project.

Ambient loop thermal energy networks are dynamic, interdependent systems, and design engineers need a way to make informed design decisions that account for their interconnectedness. Energy modeling of these systems allows for an iterative process with the design team that can be used to size thermal assets and pumps, check supply temperatures, optimize control strategies, and dynamically calculate key performance indicators.

This presentation will discuss the possibilities of ambient loop thermal energy networks as a decarbonization solution, how energy modelers can collaborate with design teams on ambient loop thermal energy network projects, and why dynamic modeling of ambient loops is crucial for the design process. A case study will be explored in which a thermal energy network with multiple ground source heat exchangers and a wastewater energy transfer system serving the thermal needs of residential, commercial, and mixed-use buildings was modeled to provide key insights for the control strategy and thermal asset connection configuration.

The current design process for building systems, in particular those involving complex design decisions and integration of storage, is not well suited to achieve cost-effective, reliable retrofit at the scale needed to support large-scale building retrofits. They typically lack in either holistic design space exploration because too detailed models are used, or in derisking system integration (mechanical system, geothermal systems, and controls) because too simplistic models are used. To address this gap, we transferred from other industry sectors a new, data-driven design methodology for cost-effective design and reliably de-risking of integrated energy systems, and demonstrate its use to the retrofit of a military base.

The design methodology is Platform-Based Design (PBD), a sequential, data-driven methodology that uses reusable component models to assemble and verify performance of candidate solutions against functional requirements. PBD enables holistic design space exploration and de-risks both the design and operation of integrated energy systems by employing increasing model fidelity throughout the process, from optimization for holistic design space exploration to detailed dynamic simulation of energy, control and geothermal systems for de-risking system integration.

We present how we applied the PBD methodology to a case study involving the retrofit of 17 buildings at Joint Base Andrews (JBA). Initial multi-objective optimization identified the optimal configuration: a geothermal-coupled Thermal Energy Network (TEN) integrated with photovoltaics (PV) and batteries. Crucially, the subsequent PBD de-risking phase—which utilized nonlinear, coupled dynamic Modelica simulations and detailed feedback controls compliant with ASHRAE Standard 231—was essential. This de-risking using virtual testing of the coupled energy, subsurface and control system identified a critical flaw: an overestimation of the geothermal borefield's capacity that required major modifications to the system integration, sizing and controls. Without this de-risking step, the physical installation would have likely failed, resulting in multi-million-dollar change orders and undermining confidence in advanced energy retrofits.

The optimized PBD solution delivers significant performance benefits, including a 74% reduction in imported energy and a 45% reduction in peak electrical demand compared to the baseline, while enhancing mission resilience at a levelized cost of energy of $0.210/kWh. The upfront cost of the PBD process proved cost-effective, identifying investment cost reductions and operational savings that far exceeded its cost, while preventing the likely multi-million-dollar expense of rectifying design flaws post-installation.

These findings stress that a new design process like PBD is not merely beneficial, but critical for enabling the rapid, reliable, and cost-effective energy system retrofits at the scale and complexity demanded by the building industry.

Using Game Engines for visualization of building performance analysis results opens up new ways to conveying data to our clients. The powerful visuals help to drive decision making, understand trade-offs of multi-variable problems, and answer questions in real time. This presentation will share a series of use cases of visualizing data within a Game Engine Environment and share the methodologies used to connect simulation software data into these environments.

In the absence of detailed metered data of each building and foresight into future performance, how do you correctly size and analyze the performance of a geothermal system for a network of buildings? This presentation showcases a streamlined solution where we collaboratively employ a strategic combination of software to inform decision making and analyze system design. This method allows modelers to take advantage of the strengths and benefits offered by each software, minimizing duplication of work while maximizing output potential.

In this presentation, we explore 3 different tools: 1) Integrated Environmental Solutions - Virtual Environment (IES-VE), which distinctively focuses on building level energy modeling, 2) Ground Loop Design (GLD), which specializes in ground loop heat pump performance analysis, and 3) TRNSYS, a transient system simulation tool popular for dynamic models.

TRNSYS is a complex modeling software capable of modeling any geothermal network, but modeling many individual buildings within it proves to be an onerous, time-consuming process. Instead, utilizing other building modeling software (IES-VE in this case) and GLD can simplify initial steps and cut down modeling time. IES-VE can be used to model the individual buildings, as the software conveniently comes with a suite of editable building templates and HVAC libraries with prototype systems. The heating and cooling loads of the buildings are then brought into GLD along with ground loop design assumptions, and GLD quickly provides a representative estimate of the borefield sizing and impact on the ground temperature and the heat pump system. With the load profile from IES-VE fed into TRNSYS and the initial sizing decision assisted by GLD, we now take full advantage of TRNSYS’s unique feature to evaluate geothermal energy network. This presentation demonstrates enhanced workflow efficiency through incorporation of multiple software, a workflow with a wide-range prospective use cases outside the discussed simulation tools and design goals.