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DOE OSTI2020

Battery Equivalent Model for Residential HVAC

Flexible loads, especially heating, ventilation, and air-conditioning (HVAC) systems can be used to provide a battery-like service to the power grid by varying their demand up and down over a baseline. Recent work has reported that the round-trip efficiency for providing grid services with HVAC systems can be close to 1. Inspired by this promising result, in this work, we rigorously develop a battery equivalent model (BEM) for residential HVAC systems. Relying only on typically available data, the proposed BEM will bridge the observability and controllability gaps between utility companies and customers. The proposed BEM will enable the utility companies to manage the flexible HVAC devices as easy as charging/discharging the conventional energy storage devices. Validated physics-based models are used to train the BEM, whose prediction accuracy is illustrated through a simulation study.

Dong, Jin↗

DOE OSTI2023

Near-Term Electricity Requirement and Emission Implications for Sustainable Aviation Fuel Production with CO 2 -to-Fuels Technologies

Aviation contributed approximately 10% of the U.S. transportation sector's greenhouse gas (GHG) emissions and about 3% of the nation's total GHG production before the coronavirus disease (COVID-19) pandemic (EPA 2022). Unlike the ground transportation sector, which can be decarbonized by using batteries and hydrogen fuel cell powertrain technologies, the technical and economic challenges of aviation electrification open the opportunity for CO 2 utilization (CO2U) using clean power sources. The U.S. government set a goal to produce 3 billion gallons per year of sustainable aviation fuels (SAF) by 2030 and scale up the production to 35 billion gallons per year by 2050 (Bioenergy Technologies Office 2022). In this report, we examine three potential locations, in California, Iowa, and Louisiana, for SAF production using two production pathways that are expected to be available by 2030. We analyze the electricity cost to satisfy 10% of the SAF production potential for the select locations. Specifically, we consider (1) retail electricity cost from the default local utility in each location; (2) physical power purchase agreement (PPA) for renewable power and battery storage hybrid systems with preset prices; (3) financial PPA from a dedicated renewable plant; and (4) estimated real-time pricing (RTP) from the wholesale power market with utility delivery adders. Retail rates are available for the three potential locations; however, the developer should negotiate with the local utility in Iowa for new tariff riders, because the load of the proposed SAF plant (1.4 GW) is significantly higher than the current industrial tariff structure requirement (200 kW). The developers are not able to claim federal credits (i.e., the Inflation Reduction Act of 2022) when sourcing electricity from local utilities. Developers could consider prioritizing physical and financial PPAs as purchase options. While physical PPAs can be imported out of state, this structure imposes availability issues as developers must locate in the same electricity grid regions. Financial PPAs do not have the same location restrictions and provide the same cost savings as physical PPAs, but financial PPAs impose financial risks in the event of system curtailment and grid interruption. RTPs are available for customers in California with flexible load and hourly load management capability; however, utilities in our studied regions in Louisiana and Iowa only offer time-of-use and curtailment programs to incentivize lower energy usage in peak hours. These utilities do not currently offer RTP programs, and the developer may need to have further negotiations with the local utilities to access RTP programs. The results show that purchased electricity prices may range from 2.6 cents/kWh to 7.1 cents/kWh for the three studied plants.

02 PETROLEUM↗

DOE OSTI2022

Hierarchical Model-Free Transactional Control of Building Loads to Support Grid Services

A transition from generation on demand to consumption on demand is one of the solutions to overcome the many limitations associated with the higher penetration of renewable energy sources. Such a transition, however, requires a considerable amount of load flexibility in the demand side. Demand response (DR) programs can reveal and utilize this demand flexibility by enabling the participation of a large number of grid-interactive efficient buildings (GEB). Existing approaches on DR require significant modelling or training efforts, are computationally expensive, and do not guarantee the satisfaction of end users. To address the aforementioned limitations, this software code considers a scalable hierarchical model-free transactional control approach that incorporates elements of virtual battery, game theory, and model-free control (MFC) mechanisms. The developed approach separates the control mechanism into upper and lower levels. The MFC modulates the flexible GEB in the lower level with guaranteed thermal comfort of end users in response to the optimal pricing and power signals determined in the upper layer using a Stackelberg game integrated with aggregate virtual battery constraints. Additionally, the usage of MFC necessitates less burdensome computational and communication requirements, thus, it is easily deployable even on small, embedded devices. This software code enables the use of residential and small-size commercial buildings to offer a potentially substantial source of ancillary grid services that are currently underutilized. A hierarchical, model-free transactive building control provides a smooth interface between the grid service requests of utilities and the reliable control required by participating buildings. Model-free control, which supports distributed control architecture, will be a more scalable solution that can be deployed in neighborhood-size systems as well as individual buildings. The proposed approach contributes to the body of knowledge on two main aspects. First, it couples the MFC with the game-theoretic control and proposes a scalable model-free transactive control approach. MFC does not require any modeling effort or model training for the various building loads. This is very beneficial since deriving an accurate model for every single unit participating in DR programs and obtaining all the parameters about the units (e.g., thermal coefficients, standby losses) are infeasible. Also, MFC is computationally efficient, easily deployable even on small, embedded devices, and can be implemented in real time. Second, it integrates the concept of virtual battery into DR via the Stackelberg game. The concept of virtual battery enables efficient coordination and aggregation of a large number of flexible GEB with guaranteed thermal comfort of end users.

Olama, Mohammed [Oak Ridge National Lab. (ORNL), O↗

DOE OSTI2025

Energy performance of an operational government building retrofitted with ceiling phase change material tiles in a mixed-humid climate

The aging U.S. building stock requires various retrofit measures to enhance their energy efficiency. Here, this study explores the integration of thermal energy storage and advanced building controls as viable retrofit solutions for load flexibility and peak demand response while maintaining the occupants' comfort. A detailed assessment is conducted on the energy use of an administrative building in Sumner County, Kansas, focusing on the implementation of phase change materials (PCMs) in the ceiling of occupied zones. First, a time-resolved, whole-building energy model is developed in EnergyPlus, incorporating complex thermal behaviors such as air exchange between the plenum space and occupied zones, envelope leakage, and operational schedules. The model is then validated using experimental field test data, and subsequently a parametric assessment of key PCM properties and application strategies is performed to evaluate cooling electricity demand benefits. The parametric study shows that the optimal retrofit strategy, comprising a PCM with 23°C peak melting temperature, 0.125 in. (3.17 mm) thickness, and 150 kJ/kg latent heat, combined with active controls that include 8 h of precooling, forced convection under the ceiling, and a 2°C thermostat setback during peak hours, can result in a maximum load shift during the peak period of 99.6 % and the total electricity savings during the peak period of 98.9 % for the optimum case and thus provide significant cost savings under time-of-use pricing scenarios.

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NASA NTRS1979

Capabilities and applications of a computer program system for dynamic loads analyses of flexible airplanes with active controls /DYLOFLEX/

This paper describes and illustrates the capabilities of the DYLOFLEX Computer Program System. DYLOFLEX is an integrated system of computer programs for calculating dynamic loads of flexible airplanes with active control systems. A brief discussion of the engineering formulation for each of the nine DYLOFLEX programs is described. The capabilities of the system are illustrated by the analyses of two example configurations.

Perry, B., III↗

DOE OSTI2021

Net-Zero Carbon Microgrids

The microgrid concept has been effective in creating aggregations of distributed energy resources—generation, storage and loads—for resiliency, in the form of energy security. The success of microgrids in bringing energy security to a wide range of customers—from individual residences to commercial and industrial installations to military bases—has been exemplified during power disruptions and extended outages due to extreme weather events, cybersecurity attacks, and equipment failures. Now microgrids have an opportunity to meet the challenges of climate change and contribute to a carbon-free power delivery system. The transition to net-zero starts within microgrids themselves. In fact, today’s microgrids are largely dominated by generators using fossil fuels, natural gas and diesel, with high greenhouse gas emissions. In short, the transition to net-zero means replacing fossil fueled generators with renewable generation in microgrids. This transition is extended by including new dispatchable generation technologies that are 100% carbon-free and that offer additional advantage of a more-dependable and sustainable source of energy and power. Basically, the decarbonization of microgrids requires three elements: 1) maximizing generation from renewable energy resources, 2) management of storage and flexible loads to balance the variability and intermittency of renewable energy resources, and 3) introducing new clean power sources, including hydrogen-based generation and small modular reactors. This report affirms a need for specific focus by governmental agencies at national, regional, and local levels to establish technology, policy, and investment in this area. The intention of the Net-Zero Microgrid (NZM) Program is to inform these constituencies with cross-cutting research and tools for the reduction of GHG in microgrids – to net-zero in the near term eventually to zero in the longer term. The NZM Program is committed to achieving decarbonization for resiliency and for providing clean energy at the local or distribution level, from remote communities to underserved communities, and large industrial and military facilities. The NZM Planning and Design Platform is a core tool to be developed as an early deliverable of the NZM Program because only a fully integrated microgrid-design approach will ensure maximum carbon reduction in energy production.

13 HYDRO ENERGY↗

DOE OSTI2021

OCHRE: The Object-oriented, Controllable, High-resolution Residential Energy Model for Dynamic Integration Studies

Electrification and the growth of distributed energy resources (DERs), including flexible loads, are changing the energy landscape of electric distribution systems and creating new challenges and opportunities for electric utilities. Changes in demand profiles require improvements in distribution system load models, which have not historically accounted for device controllability or impacts on customer comfort. Although building modeling research has focused on these features, there is a need to incorporate them into distribution load models that include DERs and can be used to study grid-interactive buildings. In this paper, we present the Object-oriented, Controllable, High-resolution Residential Energy (OCHRE) model. OCHRE is a controllable thermal-electric residential energy model that captures building thermal dynamics, integrates grid-dependent electrical behavior, contains models for common DERs and end-use loads, and simulates at a time resolution down to 1 minute. It includes models for space heaters, air conditioners, water heaters, electric vehicles, photovoltaics, and batteries that are externally controllable and integrated in a co-simulation framework. Using a proposed zero energy ready community in Colorado, we co-simulate a distribution grid and 498 all-electric homes with a diverse set of efficiency levels and equipment properties. We show that controllable devices can reduce peak demand within a neighborhood by up to 73% during a critical peak period without sacrificing occupant comfort. We also demonstrate the importance of modeling load diversity at a high time resolution when quantifying power and voltage fluctuations across a distribution system.

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DOE OSTI2022

Site demonstration and performance evaluation of MPC for a large chiller plant with TES for renewable energy integration and grid decarbonization

Thermal energy storage (TES) for a cooling plant is a crucial resource for load flexibility. Traditionally, simple, heuristic control approaches, such as the storage priority control which charges TES during the nighttime and discharges during the daytime, have been widely used in practice, and shown reasonable performance in the past benefiting both the grid and the end-users such as buildings and district energy systems. However, the increasing penetration of renewables changes the situation, exposing the grid to a growing duck curve, which encourages the consumption of more energy in the daytime, and volatile renewable generation which requires dynamic planning. The growing pressure of diminishing greenhouse gas emissions also increases the complexity of cooling TES plant operations as different control strategies may apply to optimize operations for energy cost or carbon emissions. This paper presents a model predictive control (MPC), site demonstration and evaluation results of optimal operation of a chiller plant, TES and behind-meter photovoltaics for a campus-level district cooling system. The MPC was formulated as a mixed-integer linear program for better numerical and control properties. Compared with baseline rule-based controls, the MPC results show reductions of the excess PV power by around 25%, of the greenhouse gas emission by 10%, and of peak electricity demand by 10%.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Ten questions concerning occupant-centric control and operations

Occupant-Centric Control and Operation (OCC) represents a transformative approach to building management, integrating sensing of indoor environmental quality, occupant presence, and occupant-building interactions. These data are then utilized to optimize both operational efficiency and occupant comfort. This paper summarizes the findings from the IEA-EBC Annex 79 research program's subtask on real world implementations of OCC during the past 5 years. First, in Q1 and Q2, we provide a definition and categorization of OCC. Q3 addresses the role of building operators for OCC, while Q4 describes the implications for designers. Then, Q5 and Q6 discuss the role and possibilities of OCC for load flexibility, and for pandemic induced paradigm shifts in the built environment, respectively. In Q7, we provide a taxonomy and selection process of OCC, while Q8 details real world implementation case studies. Finally, Q9 explains the limits of OCC, and Q10 provides a vision for future research opportunities. Furthermore, our findings offer valuable insights for researchers, practitioners, and policy makers, contributing to the ongoing discourse on the future of building operations management.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Mapping use cases and dataset needs for benchmarking buildings data

A perennial challenge in buildings research is the lack of high-quality datasets that can be relied upon for a wide array of tasks, including model calibration and improving energy efficiency and load flexibility. Instrumenting a building for data collection is resource intensive, so it is important to be methodical in the approach and ensure that resulting data are flexible and useful for a broad range of analyses. This study aims to fill the gaps in characterizing potential use cases for buildings datasets and mapping them to dataset needs using a well-defined data infrastructure. Here, we have developed a systematic mapping strategy between buildings dataset needs and use cases to help streamline the processes of efficiently targeting datasets, designing building sensing systems, and determining buildings research use cases. We selected 14 prospective use cases and 11 refined buildings data categories for developing the preliminary dataset-needs-to-use-cases mapping matrix (‘DN-UC mapping matrix’) with generic ‘Tags’—a detailed sub-level of data categories extracted by justifying the needs of an aspect of the datasets to use cases. We present two example applications of the developed mapping matrix to demonstrate use of the mapping matrix and its effectiveness.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

A data-driven linear formulation of the optimal demand response scheduling problem for an industrial air separation unit

Demand response (DR) has become a key element in balancing the power grid as the contribution of time-varying renewable power generation increases. Chemical plants are appealing candidates for DR programs as they offer large, concentrated and flexible loads. DR participation calls for frequent production rate changes over time scales that overlap with the dominant dynamics of the plant. Production scheduling should therefore consider the process dynamics explicitly. Here we present a data-driven approach for modelling the scheduling-relevant dynamics based on historical closed-loop operating data using autoregressive with extra inputs (ARX) models. We introduce a new, linear scheduling problem formulation based on the ARX representation, and demonstrate its implementation on an industrial air separation unit.

42 ENGINEERING↗

DOE OSTI2023

The first field application of a low-cost MPC for grid-interactive K-12 schools: Lessons-learned and savings assessment

K-12 schools are the largest energy consumers in the public sector, with their HVAC energy consumption representing the largest portion of their total energy use. While transitioning these schools to grid-interactive HVAC system operation through advanced controls offers significant financial and environmental benefits, and model predictive control (MPC) has been identified as a promising solution to achieve that, very few MPCs are affordable and have been deployed in K-12 schools. This situation raises concerns about the unclear real-world benefits of MPC technology among facility managers and industries. To address this gap, this paper presents a low-cost MPC solution that requires minimal control infrastructure costs and a unique field demonstration at a K-12 school, conducted for both cooling and heating seasons. This work adopted a previously developed MPC and extended it for use in the school application. The MPC aims to coordinate multiple packaged units to eliminate unnecessary peaks and shift cooling or heating loads in response to grid signals based on load conditions, while maintaining thermostat temperatures within school-defined bounds. Throughout the field tests, the MPC achieved a 24% reduction in peak demand during the cooling season and shifted cooling or heating loads by up to 16% in response to the school's utility tariff, considering load conditions, while also allowing end-users to override thermostat setpoints. Further, the paper also discusses the limitations of this study and future research directions for better performance of the MPC at K-12 schools.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Optimal strategies for a cost-effective and reliable 100% renewable electric grid

This paper explores cost-optimal pathways to 100% renewable power systems for the U.S. building stock. We show that long-duration misalignments of supply and demand, spanning from multi-day to seasonal timescales, present a dominant challenge that must be addressed to meet real-time 100% renewable targets. While long-duration misalignments can be addressed through energy storage, we show that alternative and readily available solutions that are more cost-effective should be considered first. Through a techno-economic analysis, we identify cost-optimal, region-dependent, supply-side, and demand-side strategies that reduce, and in some U.S. regions eliminate, the otherwise substantial capacities and associated costs of long-duration energy storage. Investigated supply-side strategies include optimal mixes of renewable portfolios and oversized generation capacities. Considered demand-side strategies include building load flexibility and building energy efficiency investments. Our results reveal that building energy efficiency measures can reduce long-duration storage requirements at minimum total investment costs. In addition, oversizing and diversifying renewable generation can play a critical role in reducing storage requirements, remaining cost effective even when accounting for curtailed generation. We identify regionally dependent storage cost targets and show that for emerging long-duration energy storage innovations to achieve broad adoption, their costs will need to compete with the decreasing cost of renewables. The findings of this research are particularly important given that most long-duration storage technologies are currently either uneconomical, geologically constrained, or still underdeveloped.

100% renewable↗

DOE OSTI2020

Distribution Operations: The Evolution of Distributed Energy Resources [Guest Editorial]

Utilities around the world are experiencing change with the increasing digitalization of their systems and those of their customers. Efforts to decarbonize the electric power system have led to growth in renewable energy resources, particularly distributed energy resources (DERs), such as generation, storage, and flexible load, both in front of and behind the meter. As this change occurs in any given utility service area, new tools, such as advanced distribution management systems (ADMSs), are needed to manage utility operations, planning, and business issues, some of which are discussed here.

distributed energy resources, DER, decarbonize, re↗

DOE OSTI2025

Future Industrial Demand: Large, Elastic, and Concentrated [Guest Editorial]

Here, the future industrial demand on the grid is expected to be large, price sensitive, and concentrated. Grid industrial demand increasingly encompasses a new customer type defined as a large flexible load (LFL). This LFL type defines customers with consumption that responds quickly to price or other incentives without interrupting their core business process, such cryptocurrency mining. This customer type can often ramp up and down quickly, which across an entire industry can mean gigawatts of power within a few minutes. In addition to these price-sensitive loads, significant growth is also anticipated in sectors like manufacturing, data centers, and electrification of transportation and buildings.

Mukherjee, Srijib [Oak Ridge National Laboratory (↗

DOE OSTI2021

Transactive HVAC Agent - Design and Performance Evaluation

Transactive energy systems are playing an increasingly important role in the efficient and reliable marketbased operation of the power grid. Since a significant portion of the residential building energy consumption is from heating ventilation and air conditioning (HVAC) systems, HVAC is one of the most promising resources to provide load flexibility. However, utilizing HVAC flexibility to provide various grid services while simultaneously maintaining consumer comfort and cost-reductions is challenging. This paper presents a design of a transactive HVAC agent (T-HVAC) to be used as a supervisory control for the HVAC system that can simultaneously ensure comfort and cost-reduction. In particular, the T-HVAC a) estimates HVAC thermal dynamics, b) ensures optimal operations of the HVAC system, and c) participates into markets, and d) implements a market-based control via controlling the thermostat temperature set-point. The T-HVAC performance is demonstrated through multiple scenarios and illustrations.

Demand flexibility, distribution system, HVAC, Tra↗

DOE OSTI2024

HP-FLEX MPC v0.1.0

HP-FLEX MPC is control software developed by Lawrence Berkeley National Laboratory with support from the California Energy Commission (CEC) through EPIC-19-301. HP-FLEX aims to provide load flexibility for heat pumps (HPs) in response to dynamic grid signals (including Time-of-Use, Dynamic Pricing, and Critical Peak Pricing) while maintaining thermostat temperatures within user-specified bounds. The software includes a system-identification module, which models the dynamics of the building envelope with thermostat data, and a control module based on a model predictive controller (MPC) to make optimal decisions. HP-FLEX receives forecasts of outdoor air temperature, solar irradiation, and internal gain (if available), as well as trajectories of energy price, temperature lower and upper bounds over a prediction horizon. It then optimizes heating and cooling capacities to minimize energy cost and peak power (with a user-defined weight on peak power) over the prediction horizon, while maintaining room air temperature within the temperature constraints, and outputs the optimal thermostat setpoints.

Kim, Donghun↗

DOE OSTI2024

Security Constrained Distributed Transaction Model for Multiple Prosumers

Massive access of renewable energy has prompted demand-side distributed resources to participate in regulation and improve flexibility of power systems. With large-scale access of massive, decentralized, and diverse distributed resources, demand-side market members have transformed from traditional “consumers” to “prosumers”. To explore the distributed transaction model of prosumers, in this paper, a multi-prosumer distributed transaction model is proposed, and the Conditional Value-at-Risk (CVaR) theory is applied to quantify potential risks caused by the stochastic characteristics inherited from renewable energy. First, a prosumer model under constraints of the distribution network including photovoltaic units, fuel cells, energy storage system, central air conditioning and flexible loads is established, and a multi-prosumer distributed transaction strategy is proposed to achieve power sharing among multiple prosumers. Second, a prosumer transaction model based on CVaR is constructed to measure risks inherited from the uncertainty of PV output within the prosumer and ensure safety of system operation in extreme PV output scenarios. Then, the alternating direction multiplier method (ADMM) is utilized to solve the constructed model efficiently. Finally, distributed transaction costs of prosumers are distributed fairly based on the generalized Nash equilibrium to maximize social benefits. Simulation results show the multi-prosumer distributed transaction mechanism established under the proposed generalized Nash equilibrium method can encourage power sharing among prosumers, increasing their own income and social benefits. Also, the CVaR can assist decision making of prosumers in weighting the risks and benefits, improving system resilience through energy management of prosumers.

24 POWER TRANSMISSION AND DISTRIBUTION↗