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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Application of thermal energy storage with electrified heating and cooling in a cold climate

Ground source heat pumps (GSHPs) have been shown to be an effective means of decarbonizing building heating and cooling, but the operation of these systems at scale presents challenges to sites and the grid due to increases in peak demand. Here, in this study, we investigate how the use of Thermal Energy Storage (TES), in the form of stratified water storage, could reduce the peak daily demand associated with GSHP systems and thus improve their cost effectiveness. This system was compared to a Combined Heat and Power (CHP) plant, to investigate the potential cost and emissions impacts of electrification on large energy users transitioning from high efficiency fossil fuel equipment. This study builds on previous research by using a significant campus area, and investigating the various impacts of an electrified system versus a state of the art fossil fuel system. An established method of TRNSYS modeling is used for the heat pumps and borehole heat exchangers (BHEs), along with the TES. The GSHP system with TES is modeled to follow industry standards and sized to provide an optimal balance of capital and operating costs. Costs were investigated for a unique large energy user rate structure, as well as for a more common generalized rate structure. The results show that the addition of TES to the GSHP system could reduce operating costs by 4.5%, but still incurs a 5.64% cost increase from the baseline CHP system. It is also shown, however, that a tactical integration of heat pumps into the CHP system is the most cost effective solution, only increasing the operating costs by 4.71%. Likewise, the impacts of different rate structures are highlighted, with the TES only resulting in 0.75% cost savings under the generalized utility rate. Furthermore, it is shown that thermal storage has great potential for demand reduction, with the addition of storage incurring a decrease of 7–22% in annual peak demand kW, dependent on the rate structure.

25 ENERGY STORAGE↗
DOE OSTI2025

Terra-Populus v0.1: A Python Library for LandScan High-Definition Population Analysis and Modeling

The terra-populus library is designed for use by the LandScan HD technical team, offering a streamlined set of tools for generating and updating LandScan HD datasets from foundational building-level data, referred to as 'molecules,' provided by the building-level attribution team. This document serves as the primary technical documentation for terra-populus. Version 0.1 of the library includes the core modeling components necessary for LandScan HD production. It enables the generation of the LandScan HD Baseline dataset as well as corresponding confidence measures for the occupancy rates used. Parameters have been included for incorporating damaged building indicators and changes in population, to faciliate the creation of rapid updates for LandScan HD. Future iterations of terra-populus will introduce tools for creating a confidence index, and quantifying and propagating uncertainty, facilitating the creation of probabilistic LandScan HD outputs. This report provides an overview of the tools available in the library and the corresponding code implementations. One of the key advancements implemented in terra-populus is a redefinition of the atomic modeling unit for LandScan HD. Traditionally, the LandScan HD vector analytical framework has generated population estimates at the building sub-component (molecule) level. However, terra-populus adopts a building-level modeling approach. This shift is an operational decision aimed at aligning LandScan HD outputs with confidence measures, which are computed and validated at the building level (confidence measures are not included in this version of terra-populus, aside from those associated with the occupancy rates). Additional advancements to the LandScan HD modeling, as implemented by terra-populus, include a minimum population value parameter and an auto assignment of building floor counts. The population minimum value was implemented to prevent buildings and subsequent LandScan HD pixels that contained small values that may not rasterize in production. An 'auto' value has been included as a method for dealing with buildings lacking floor count information, where it is the average floor count of all other buildings with a residential building use type tag. The logic behind this is to remain consistent with the current logic employed for dealing with building use type null instances, where a null use type is defaulted to residential since it is the most common building type. The auto logic is intended to apply the most common building floor count of the most common type of buildings. The tools provided in terra-populus represent a significant step forward in improving the efficiency, reproducibility, and transparency of the LandScan HD modeling process. As the library evolves, it will continue to serve as a foundational resource for high-resolution population modeling.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2025

Refining seasonal performance metrics for room air-conditioning in emerging markets: Integrating building simulations with real-world equipment performance data

Buildings significantly impact worldwide energy consumption, emphasizing the need to reduce the cooling energy demand, especially in warm climates. Minimum energy performance standards (MEPS) and seasonal performance metrics such as the Cooling Seasonal Performance Factor (CSPF) are crucial for improving room air conditioning (RAC) efficiency. However, challenges remain, particularly in emerging markets like Brazil, where seasonal performance metrics have recently been introduced. This study assesses the factors influencing country-level seasonal efficiency metrics and proposes a framework to refine these calculations by considering local climates and expected RAC usage in real-world households via building simulations. Key considerations include outdoor air temperature binning for different climates, RAC usage patterns (i.e., daytime and nighttime usages), envelope thermal performance of households, and urban heat island (UHI) effects. The results reveal that CSPF values can vary significantly based on climate conditions, with observed CSPF ranging from 4.10 to 11.59 Wh/Wh across 577 Brazilian climates. The inclusion of UHI effects led to a reduction in CSPF values by up to 29% during nighttime operations in hot urban areas. Additionally, building envelope efficiency showed contrasting impacts on RAC performance, with CSPFs reaching up to 15.35 Wh/Wh under specific optimized conditions. These findings highlight the need for transparent policymaking in RAC performance databases, facilitating the application of approaches like those proposed in this study and supporting diverse stakeholders in decision-making.

Bavaresco, Mateus↗
DOE OSTI2022

Risk-Informed Operations and Maintenance Decision Making Using Deep Reinforcement Learning

A challenge for operating nuclear power plants is the significant cost of operations and maintenance, at times consuming up to 66% of annual operating costs. This project aims to build a framework for a risk-informed asset-management tool that integrates inspections, repairs, spare-part inventory, supply chain, and business choices to lower overall O&M costs. Our approach uses a combination of data-driven modeling and deep reinforcement learning to create and implement optimal maintenance policies for the existing nuclear fleet, as well as new advanced reactors. The creation of an asset management tool that uses these advanced methods will give operators new capabilities to help reduce the burden of O&M spending in nuclear power plants.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Behind the Meter Storage for Electric Vehicle Charging, Electrochemical and Thermal Energy Storage, and Solar Photovoltaic

In response to the potentially large and irregular demand from EVs, along with changing load profiles from buildings with on-site generation, utilities are evaluating multiple options for managing dynamic loads, including time-of-use pricing, demand charges, battery storage, and curtailment of variable generation. Buildings, as well as commercial, public, and workplace EV charging operations, can use a combination of electrochemical battery storage and thermal energy storage coupled with on-site generation to manage energy costs as well as provide resiliency and reliability for EV charging and building energy loads. We are completing a behind the meter storage analysis that focuses on determining the optimal system designs and energy flows for thermal and electrochemical behind the meter storage with on-site solar photovoltaic (PV) generation enabling electric vehicle charging in various climates, building types, and utility rate structures. In completing this analysis, we have developed a tool that combines existing battery models via the System Advisor Model (SAM) and building modeling software via EnergyPlus into a single interface. This tool allows us to simulate a building with a detailed battery model to properly size the battery, thermal energy storage, and solar PV systems to maximize profit for the system owner. This also allows us to assess how the battery degrades under various supervisory control dispatch algorithms to control charging/discharging; we can also see how thermal energy storage is created and used to complement the battery to reduce thermal loads in the building. With this project, we can analyze new batteries that are designed specifically for energy storage, rather than designed to be extremely energy dense for electric vehicle applications, using battery lifetime models from other national labs and the existing SAM battery model, which has detailed lifetime and degradation parameters. We can also assess novel thermal storage technologies by integrating them into the whole building energy simulation program EnergyPlus. Because the model calls both SAM and EnergyPlus, required inputs need to be compatible for both models. These inputs include, on a high-level, the following: weather files, building and electric vehicle load profiles, electricity rate tariff information, and system cost information for the stationary battery, solar PV, and thermal storage system. The various buildings we are studying for this analysis are retail big-box grocery store, commercial office building, fleet vehicle depot and operations facility, multi-family residential, and electric vehicle charging station. For these different applications, the battery and thermal storage will be dispatched differently, and the various technologies are sized differently to optimize cost.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2025

Building 100 Groundwater Bioremediation at the Former DOE Pinellas Plant, Florida: Review of Progress and Opportunities

Weapons research, development, and production operations at the former Pinellas Plant, which includes the Building 100 area, released chlorinated organic solvents into the subsurface, contaminating the underlying soil and groundwater. The site was sold to Pinellas County and is now home to a thriving industrial park known as the Young - Rainey Science, Technology, and Research (STAR) Center. The US Department of Energy (DOE) has applied bioremediation at the Building 100 Area as a key technology to clean up the chlorinated volatile organic compound (cVOC) contamination in soil and groundwater. The monitoring data indicate significant progress toward remedial objectives over the past two decades. Starting conditions in the 1980s-1990s included areas containing residual undissolved dense nonaqueous phase liquids (DNAPLs) and the associated presence of an extensive high concentration plume in the groundwater. The original parent cVOCs were primarily tetrachloroethene (PCE) and trichloroethene (TCE). After several informative pilot studies, bioremediation was implemented at the Building 100 Area of the site and relies on reductive biological pathways and the sequential removal of chlorine from the parent cVOCs forming dichloroethane (DCE) and chloroethene (vinyl chloride, VC). As bioremediation sites evolve toward cleanup, the trends in VC concentrations often serve as a critical indicator for progress and remediation timeframe because VC typically has a lower concentration target remedial objective (nominally 1 to 2 μg/L) compared to PCE and TCE (nominally 3 to 5 μg/L).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

An Integrated Feasibility Study of Reservoir Thermal Energy Storage (RTES) in Portland, OR, USA

In regions with long cold overcast winters and sunny summers, Deep Direct-Use (DDU) can be coupled with Reservoir Thermal Energy Storage (RTES) technology to take advantage of pre-existing subsurface permeability to save summer heat for later use during cold seasons. Many aquifers worldwide are underlain by permeable regions (reservoirs) containing brackish or saline groundwater that has limited beneficial use due to poor water quality. We investigate the utility of these relatively deep, slow flowing reservoirs for RTES by conducting an integrated feasibility study in the Portland Basin, Oregon, USA, developing methods and obtaining results that can be widely applied to RTES systems elsewhere. As a case study, we have conducted an economic and social cost-benefit analysis for the Oregon Health and Science University (OHSU), a teaching hospital that is recognized as critical infrastructure in the Portland Metropolitan Area. Our investigation covers key factors that influence feasibility including 1) the geologic framework, 2) heat and fluid flow modeling, 3) capital and maintenance costs, 4) the regulatory framework, and 5) operational risks. By pairing a model of building seasonal heat demand with an integrated model of RTES resource supply, we determine that the most important factors that influence RTES efficacy in the study area are operational schedule, well spacing, the amount of summer heat stored (in our model, a function of solar array size), and longevity of the system. Generally, heat recovery efficiency increases as the reservoir and surrounding rocks warm, making RTES more economical with time. Selecting a base-case scenario, we estimate a levelized cost of heat (LCOH) to compare with other sources of heating available to OHSU and find that it is comparable to unsubsidized solar and nuclear, but more expensive than natural gas. Additional benefits of RTES include energy resiliency in the event that conventional energy supplies are disrupted (e.g., natural disaster) and a reduction in fossil fuel consumption resulting in a smaller carbon footprint. Key risks include reservoir heterogeneity and a possible reduction in permeability through time due to scaling (mineral precipitation). Lastly, a map of thermal energy storage capacity for the Portland Basin yields a total of 43,400 GWh, suggesting tremendous potential for RTES in the Portland Metropolitan Area.

14 SOLAR ENERGY↗
DOE OSTI2020

Commercial building loads providing ancillary services In PJM

The adoption of low carbon energy technologies such as variable renewable energy and electric vehicles, coupled with the efficacy of energy efficiency to reduce traditional base load has increased the uncertainty inherent in the net load shape. Handling this variability with slower, traditional resources leads to inefficient system dispatch, and in some cases may compromise reliability. Grid operators are looking to future energy technologies, such as automated demand response (DR), to provide capacity-based reliability services as the need for these services increase. While DR resources are expected to have the flexibility characteristics operators are looking for, demonstrations are necessary to build confidence in their capabilities. Additionally, building owners are uncertain of the monetary value and operational burden of providing these services. To address this, the present study demonstrates the ability of demand response resources providing two ancillary services in the PJM territory, synchronous reserve and regulation, using an OpenADR 2.0b signaling architecture. The loads under control include HVAC and lighting at a big box retail store and variable frequency fan loads. The study examines performance characteristics of the resource: the speed of response, communications latencies in the architecture, and accuracy of response. It also examines the frequency and duration of events and the value in the marketplace which can be used to examine if the opportunity is sufficient to entice building owners to participate.

MacDonald, Jason↗
DOE OSTI2023

Inverse reinforcement learning control for building energy management

Reinforcement learning (RL) based control is widely considered a promising approach in building automation and control as it has demonstrated the potential to deal with complex objectives in adjacent domains like robotics, autonomous vehicles, gaming applications, and advertisement recommendations. When applied to any environment, model-free RL learns to improve its control performance over time without requiring a control model, by receiving and then analyzing feedback from the building environment after each control action. Operational objectives are becoming increasingly complex through the simultaneous consideration of thermal comfort, carbon emissions, grid services, and indoor air quality. In this context, conventional rule-based control approaches are proving sub-optimal, mostly heuristic, and inadequate. The model-free and self learning nature of RL appears promising and attractive as it may address the scalability issues associated with advanced control approaches. However, it suffers from long training times and unstable control behavior during the early stages of its learning process, which makes it unsuitable to be applied directly to buildings. This paper addresses these issues using an inverse reinforcement learning approach (IRL), a technique utilized to learn the objective of a controller agent which is considered an expert in its respective domain. Here, we consider a rule-based control as the expert demonstrator. IRL is different from a direct imitation (i.e., direct mapping of states to actions) of control actions as it tries to find the underlying intent of an expert's policy, providing the controller with a better-generalized policy for unseen states or environments with slightly different dynamics. This approach propels the RL controller's policy to levels similar to or better than that of a rule-based policy before it starts learning by interacting with the building. This makes RL for building energy management applications more practical as it prevents the erratic and exploratory behavior in the initial training period, simultaneously speeding up the learning process when compared to applying an untrained RL agent directly to a building environment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Metrics for Evaluating Grid Service Provision from Communities of Grid-interactive and Efficient Buildings and other DER

Tapping into the flexibility of aggregations of Grid-interactive and Efficiency Buildings (GEBs) represent a large opportunity to cost-effectively improve operations in future low-carbon power grids. The US Department of Energy's Connected Communities program seeks to demonstrate collections of these GEBs at 10 different sites across the country. However, consistent metrics for evaluation across all projects are needed to build confidence in the approach. This paper presents the metrics relating to Grid Service Provision that will be computed at the 10 demonstrations. The metrics proposed quantity the magnitude of service offers, the consistency and quality of services provided by the community, and the individual DER contributions to the community-level service. The goal of this work is to present these metrics and describe some of their intended insights. The hope is that these insights will be useful and build confidence for grid operators, regulators, and aggregators and practitioners as they look to deploy these resources in grids of the future.

MacDonald, Jason S↗
DOE OSTI2026

Experimental study of a thermal energy storage-integrated heat pump system for load shifting in space cooling and heating

This study experimentally investigates an all-season thermal energy storage-integrated heat pump (TES-HP) system developed to enhance building energy efficiency and support grid-interactive operation through load shifting in both cooling and heating. A 4-ton commercial rooftop air-source heat pump was modified by integrating a hydronic thermal energy storage (TES) unit containing a phase change material (PCM) with a melting temperature of 22.0 °C. The system employs two reversing valves and three electronic expansion valves to enable six operating modes, including normal, TES charging, and TES discharging in both cooling and heating seasons. A subcooling-controlled electronic expansion valve was implemented to mitigate refrigerant maldistribution caused by unequal internal volumes among the heat exchangers. Compared with a baseline heat pump, the TES-HP reduced power consumption by 30–50% during cooling at an ambient temperature of 40.6 °C, and by up to 60% during heating at −15.0 °C, while maintaining high performance under cold-climate conditions. Additionaly to experimental evaluation, a simplified annualized on-peak analysis was conducted to compare the TES-HP with the baseline system, indicating an on-peak electricity reduction of approximately 876 kWhₑ per unit per year and associated on-peak cost savings under time-of-use pricing. These results demonstrate that the TES-HP effectively decouples HP operation from adverse ambient conditions, improving flexibility, resilience, and energy efficiency. This work advances prior research by experimentally proving the integration of PCM-based TES for a year-round, load-flexible HVAC operation.

42 ENGINEERING↗
DOE OSTI2026

Categorizing Plug Load Solutions by Ease of Implementation

Plug loads account for a growing share of U.S. commercial building electricity use, projected to rise from 16% today to 21% by 2050. Managing these loads presents a substantial opportunity for reducing energy costs while providing additional operational benefits, such as improved asset management and occupant comfort. Despite their potential, plug loads are numerous, diverse, and highly occupant-dependent, making control challenging. This publication organizes plug load control strategies by level of effort, offering building owners and operators a staged approach to implement interventions ranging from smart outlets and automatic receptacle controls to behavioral strategies. By following these actionable steps, building stakeholders can reduce energy consumption, lower utility bills, and realize broader operational advantages.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

A Three-in-One Hybrid Strategy for High-Performance Semiconducting Polymers Processed from Anisole

The development of semiconducting polymers with good processability in green solvents and competitive electrical performance is essential for realizing sustainable large-scale manufacturing and commercialization of organic electronics. A major obstacle is the processability-performance dichotomy that is dictated by the lack of ideal building blocks with balanced polarity, solubility, electronic structures, and molecular conformation. Herein, through the integration of donor, quinoid and acceptor units, an unprecedented building block, namely TQBT, is introduced for constructing a serial of conjugated polymers. The TQBT, distinct in non-symmetric structure and high dipole moment, imparts enhanced solubility in anisole—a green solvent—to the polymer TQBT-T. Furthermore, PTQBT-T possess a highly rigid and planar backbone owing to the nearly coplanar geometry and quinoidal nature of TQBT, resulting in strong aggregation in solution and localized aggregates in film. Remarkably, PTQBT-T films spuncast from anisole exhibit a hole mobility of 2.30 cm 2 V -1 s -1 , which is record high for green solvent-processable semiconducting polymers via spin-coating, together with commendable operational and storage stability. The hybrid building block emerges as a pioneering electroactive unit, shedding light on future design strategies in high-performance semiconducting polymers compatible with green processing and marking a significant stride towards ecofriendly organic electronics.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Tackling the Giants: Applying Smart Labs Principles to Constant Air Volume Lab Buildings

Laboratories typically consume 3 to 10 times more energy than similarly sized commercial buildings, and as much as 50% of that energy is wasted by inefficient and poorly operating fume hoods and ventilation systems. One challenge faced by older laboratory buildings is the heating, ventilation, and air-conditioning systems serving many of these buildings. The older systems are usually constant air volume (CAV) systems that maintain constant ventilation rates that cause excess airflow and inefficient energy use. Variable air volume systems can be more efficient systems with sensors to detect the need for a change in volumetric flow rate; however; renovation of ventilation systems can create disruption to ongoing research and operations along with considerable up-front costs. When a Smart Labs program is implemented, an organization has a systems-based management approach that yields a high-performing laboratory building. As decarbonization continues as a priority for sites, buildings with CAV systems are difficult to address. This work centers around practical guidance for improving lab buildings with CAV. In conjunction with industry input on top technology solutions and best practices, recommendations will include performing a laboratory ventilation risk assessment in conjunction with robust retro-commissioning work, which is a crucial step in the Smart Lab process. By applying Smart Labs principles, the aging laboratory building stock of 153,343 (Lawrence Berkeley National Laboratory [LBNL] 2017), comprising roughly 500,000 lab spaces in the United States, can be brought to safe and high-performance operations.

building↗
DOE OSTI2024

Support of the Massachusetts — NREL Wind Technology Testing Center (Cooperative Research and Development Final Report)

Under the shared-resources CRADA agreement, NREL will collaborate with the Massachusetts Technology Park Corporation, d/b/a Massachusetts Technology Collaborative (MTC), in its efforts to design, construct, and operate the Massachusetts-NREL Wind Technology Testing Center (WTTC), which is an advanced blade testing facility capable of testing blades up to at least 70 meters in length. The WTTC building will be owned and the facility operated by the MTC. In the CRADA, NREL agrees to provide certain capital equipment and certain NREL employees at the WTTC facility for training, commissioning, and continued technical assistance. In addition, NREL will provide one or more Laboratory staff to serve on any WTTC advisory committee, a no-cost license of the NREL blade-resonance fatigue testing technology (NREL Testing IP) and training to MA staff at the NREL blade test facilities in Colorado. MTC will provide all other resources necessary to design, construct, and operate the WTTC.

17 WIND ENERGY↗
DOE OSTI2023

Modular Power Electronics Approach for High Power Dynamic Wireless Charging System

Dynamic wireless power transfer (DWPT) can provide energy to EVs in motion and extend the drive range. Upscaling the charging power to 200 kW (High Power DWPT) reduces the percentage of electrified roadway required, and the solution becomes cost-effective. To smooth the power at the battery and grid, a secondary regulation stage must be added. The DWPT system therefore relies on power electronics to interface with the coils and regulate the power flow. Designing this high power system using wide bandgap devices makes ensuring high efficiency, small size, and reliable operation very challenging, and significant engineering effort is required to build such complicated systems for large-scale installation and deployment. Here, this paper describes a modular design approach for the power electronics to achieve the 200 kW wireless power transfer. As described, the SiC power electronics building block is designed, simulated, and characterized. The approach is validated in the DWPT system to build the inverter, the rectifier, and the DC/DC converter, which demonstrated high performance and reliable operation with 188 kW power.

42 ENGINEERING↗
DOE OSTI2020

Quantification of Load Flexibility in Residential Buildings Using Home Energy Management Systems

With increasing penetration of renewable energy resources, the flexibility of operating behind-the-meter (BTM) resources plays a key role in enhancing grid reliability and resilience. Residential buildings with home energy management systems (HEMS) can provide desired flexibility for the distribution system operator (DSO) while considering customer comfort and preferences. This paper discusses a methodology to quantify the flexibility of BTM resources of residential buildings using HEMS. First, we propose a model predictive control framework to formulate the flexibility band comprising nominal, upper, and lower demand profiles. Second, the paper proposes a dispatch method for HEMS to compute the control signals for each BTM resource (e.g., air conditioner, water heater, home battery system) upon receiving a flexibility service request from the DSO. The case study provides insight into the flexibility provided at the whole-home level with different user preferences and seasons. The results demonstrate that HEMS is capable of providing flexibility service at the request of the DSO while delivering primary services to the building occupants.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2022

Technology Integration to Gain Commercial Efficiency for the Urban Goods Delivery System, Meet Future Demand for City Passenger and Delivery Load/Unload Spaces, and Reduce Energy Consumption

This three-year project supported by the U.S. Department of Energy Vehicle Technologies Office has the potential to radically improve the urban freight system in ways that help both the public and private sectors. Working from 2018-2021, project researchers at the University of Washington’s Urban Freight Lab and collaborators at the Pacific Northwest National Laboratory have produced key data, tested technologies in complex urban settings, developed a prototype parking availability app, and helped close major knowledge gaps. All the fruits of this project can be harnessed to help cities better understand, support and actively manage truck load/unload operations and their urban freight transport infrastructure. Project learnings and tools can be used to help make goods delivery firms more efficient by reducing miles traveled and the time it takes to complete deliveries, benefitting businesses and residents who rely on the urban freight system for supplies of goods. And, ultimately, these project learnings and tools can be used to make cities more livable by minimizing wasted travel, which, in turn, contributes to reductions in fuel consumption and emissions. Cities today are challenged to effectively and efficiently manage their infrastructure to absorb the impacts of ever-increasing e-commerce-fueled delivery demand. All delivery trucks need to park somewhere to unload and load. Yet today’s delivery drivers have no visibility on available parking until they arrive at a site, which may be full. That means they can wind up cruising for parking, which wastes time and fuel and contributes to congestion. Once drivers do find parking, the faster they can unload at the spot, the faster they free up space for other drivers, helping others avoid circling for parking. This makes the parking space—and thus the greater load/unload network—more productive. To this end, the research team successfully met the project’s three goals, developing and piloting strategies and technologies to: 1. Reduce parking-seeking behavior in the study area by 20%; 2. Reduce parcel truck dwell time (the time a truck spends in a spot to load/unload) in the study area by 30%; 3. Increase curb space, alley space and private loading bay occupancy rates in the study area. The research team met these goals by creating and piloting on Seattle streets OpenPark, a first-of-its-kind real-time and forecasting curb parking app customized for commercial delivery drivers—giving drivers the “missing link” in their commonly used routing tools that tell them how best to get to delivery locations, but not what parking is available to use when they get there. Installing in-ground sensors on commercial vehicle load zones (CVLZs) and passenger load zones (PLZs) in the 10-block study area in Seattle’s downtown neighbourhood of Belltown let researchers glean real-time curb parking data. The research team also met project goals by piloting three parcel lockers in public and private spaces open to any delivery carrier, creating a consolidated delivery hub that lets drivers complete deliveries faster and spend less time parked. Researchers collected and analysed data to produce the first empirical, robust, statistically significant results as to the impact of the lockers, and app, on on-the-ground operations. In addition to collecting and analyzing sensor and other real-time and historical data, researchers rode along with delivery drivers to confirm real-world routing and parking behavior. Researchers also surveyed building managers on their private loading bay operations to understand how to boost usage.

97 MATHEMATICS AND COMPUTING↗