The aim of this research is to optimize a Phase Change Material (PCM) glazing façade of an open-plan office building to minimize the total energy consumption in balance with providing thermal and visual comfort. An integrated simulation and optimization workflow is proposed based on GenOpt, Radiance, EnergyPlus and Python customized scripts. The optimization parameters are the location of PCM in the façade layout, the PCM layer thickness, the PCM type, and the proportion of the façade covered by PCM glazing.

The optimization process successfully achieves energy efficiency and improves indoor comfort. The process demonstrated low computational time (5 hours and 45 minutes) to identify the optimal PCM glazing design for an open-plan office building.

The results reveal that double-clear glazing incorporating PCM outperforms electrochromic glazing in an open-plan office in a semiarid climate. Compared to electrochromic glazing, the benefits of PCM glazing include a 41.2% reduction in cooling energy consumption and a 63% decrease in out-of-comfort hours. Despite a slight drop in Annual Sunlight Exposure (ASE), lighting energy consumption and visual comfort show no relevant improvements, underscoring the importance of implementing a daylight control system. The results also emphasize the impact of increased thermal inertia offered by PCM glazing on the building's energy performance.

Future research should extend to other climates and explore the accuracy of the Five-phase method for daylight simulations instead of the Three-phase method used in this research.

Beneficial community electrification is critical to the US energy transition and decarbonization movement. It also requires careful design and analysis to execute properly. This process often includes retrofitting heating systems with heat pumps but requires special consideration in cold climates. This study examines the effects heat pump sizing methods and switchover temperatures have on the energy consumption and energy costs of cold-climate air source heat pumps. We found that heat pump sizing methodology has a large effect on the resulting number of unmet hours, while switchover temperature has smaller effect on the same outcome. We also observed that a large difference in unmet hours/comfort can be made with minimal changes in energy bills.

This paper details the three-year development journey of ZEBIA (Zero Energy Building Integrated Analysis), a tool for Zero Energy Building (ZEB) projects. Developed collaboratively between a major Japanese Architecture & Construction company and American sustainable architecture partners, ZEBIA streamlines the evaluation of environmental qualities, integrating ZEB targets, user comfort, and design preferences. The paper delves into ZEBIA's wireframes, prototyping, user testing, and a comprehensive road-test. It emphasizes lessons learned and the importance of user-centric tools and systematic guidelines in achieving zero-energy building objectives. The discussion underscores ZEBIA's capacity to empower architects and engineers, support ZEB goals, and facilitate effective collaboration.

Various advanced control sequences for chiller plants with water-side economizers (WSE) have been proposed in literature, but the optimization of those controls is limited. It is possible to maximize energy savings by developing near-optimal control sequences, which are dependent on several factors such as the load profile. To address these gaps, we first identify an advanced control sequence and three key control parameters for chiller plants with WSE. Next, optimizations are performed to minimize energy consumption for seven combinations of control parameters. A chiller plant with WSE system in a warm and marine climate is studied and two load profiles are considered. The system and controls are modeled using the Modelica Buildings library. The results show optimizing the selected control parameters can reduce energy consumption by up to 11\% depending on the load profile. Specifically, optimizing the cooling tower efficiency threshold in the condenser water reset control can significantly reduce energy savings for the variable load profile by efficiently shifting the load from the cooling tower to the chiller. This paper provides practical guidance for developing near-optimal control sequences for chiller plant with WSE systems considering impacts such as the load profile.

Defining inputs for heating, ventilating, and air-conditioning (HVAC) equipment is an important part of creating a building energy model. Results from simulations depend on how HVAC systems perform at off-rated and part load conditions. Building energy simulation is often used in situations where efficiency targets are defined for HVAC equipment but guidelines on how this equipment should be modeled are lacking and have been for years. A new tool available for all practitioners was developed to help with this issue. This tool, named Copper, is a performance curve generator for building energy simulation that enables modelers to generate full and part load efficiency metric-specific performance curves for HVAC equipment to be used in applications such as baseline modeling for building energy code compliance and simulations for early design analysis. Copper uses a data-driven approach to derive typical performance curves that are then modified to target specific efficiency values. This study covers Copper's methodology and the factors to consider when dealing with integrated efficiency metrics in simulations and how they impact the modeling of part load performance.

Building Performance Standards (BPS) are being adopted globally and in the United States of America, where 14 different states and jurisdictions have a policy in place and many others are under development. To make informed decisions about concentrating investments for Building Performance Standards building upgrades, accurate and equity-informed data sources are essential. There have been multiple new tools related to Energy Equity and Environmental Justice (EEEJ) and the resulting datasets need to be integrated into large building portfolios for quick access and increased scalability. Integrating the EEEJ data in a user-friendly format can help decision makers more quickly evaluate the impact and parse through the multitude of potentially significant metrics which have yet to become consensus-based.

In the US and Canada, many BPS ordinances primarily rely on ENERGY STAR® Portfolio Manager® (ESPM) for collecting building characteristics and energy-water consumption data. These datasets can then be imported into city-specific building tracking tools like the Stand-ard Energy Efficiency Data Platform (SEED). Crucially, BPS decision makers require an efficient means of identifying buildings in prioritized communities to allocate support resources effectively. This process needs to integrate seamlessly into existing jurisdiction-al toolsets for optimal utility. This paper will demonstrate for the case of Washington D.C.’s (the District) data a workflow that provides actionable data for building upgrade investment prioritization in disadvantaged communities.

A comparison of an affordable housing complex in Visalia, California was performed using a genetic algorithm to optimize energy conservation measures from a prior low-energy design by design practitioners. Proposed ECMs were developed and evaluated with a cloud-based workflow using NSGA-II to create combinations of ECMs tested against carbon, cost, and Time Dependent Valuation. Numerous lower carbon solutions were identified, with the greatest saving 9%. The biggest determinant of savings was the selected HVAC system, with passive strategies yielding limited savings. Despite this magnitude of savings, the approach yields positive payback and financeable solutions with greater stability in energy cost against future climate changes.