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DOE OSTI2022

Role of Renewable Energy, Storage, and Demand Response in Karnataka's Power Sector Future

Karnataka ranks fourth among Indian states in installed capacity of renewable energy, which accounts for over 50% of its resource mix. The state is positioned to play a leading role in India's energy transition and contribute to meeting national targets for renewable energy thanks, in part, to ambitious state goals to develop Karnataka's abundant zero carbon energy resources and plans to phase out new investments in thermal plants. Power system stakeholders in Karnataka are faced with the challenge of planning a generation portfolio that accounts for the variability of wind and solar resources, meets increasing and shifting electricity demand, and satisfies operational and reliability requirements. The objective of this study is to evaluate least-cost pathways for Karnataka's electric power system through 2050. The capacity expansion model developed for this study identifies power system investment and operational decisions for every year (2020-2050) for all of India, with detailed representation of the state of Karnataka. The study led to five high-level results and provides a framework for recurring planning studies to meet changing system conditions and needs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Wireless Instrumented RB Experiment Preliminary Design and Analysis

The ability to deploy new nuclear fuels for current or future reactor concepts requires carefully designed experiments to generate data to support fuel qualification. Ideally these experiments would include state of-the-art sensing to maximize the amount of in situ data that can be collected during operation. Furthermore, advanced reactor systems can take advantage of integrated in-core sensing technologies to maximize fuel utilization, reduce unnecessary conservativism in design margins, and improve operator’s understanding of limiting peaking factors. Before any novel sensing technologies can be readily adopted for nuclear applications, they must first demonstrate acceptable performance in test reactors. This report summarizes the preliminary design and analysis of the most highly instrumented irradiation experiment ever performed in the removable beryllium (RB) positions of the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL). The Wireless Instrumented RB Experiment 2021 (WIRE-21) will test a wide range of sensors including wireless sensors being developed by Westinghouse Electric Company (WEC) that could provide in situ measurements of peak fuel temperatures and fuel rod pressurization due to fission gas release. The ability to wirelessly transmit a signal through the fuel rod’s cladding is critical to improving fuel monitoring capabilities without requiring signal penetrations through the cladding pressure boundary, which would significantly impact fuel fabrication, handling, and operation. Other sensors that will be tested in WIRE-21 include an array of thermocouples, self-powered neutron detectors (SPNDs), and spatially distributed fiber-optic temperature sensors. More generally, WIRE-21 will establish a flexible irradiation vehicle design to allow accelerated, economical testing of advanced sensor technologies while leveraging the extremely high neutron flux that is available in HFIR. This report summarizes the mechanical design for WIRE-21, the experimental test matrix, initial neutronic and thermal design analyses, and the active monitoring and control system enhancements necessary to support testing of advanced sensor technologies. The containment for WIRE-21 is similar to previous RB irradiation vehicles but includes a few modifications, most notably the use of integrated compression seals to pass a larger number of sensor leads through the experiment’s pressure boundary. In addition to the sensor leads, inert gas lines are passed into the experiment to enable active temperature control and the ability to pneumatically actuate a bellows-driven pressure sensor. WIRE-21 is targeting temperatures (300–350°C) and neutron fluence levels (~10 22 n/cm 2 ) relevant to light water reactors (LWRs), but the flexible design of the experiment vehicle allows much higher operating temperatures (>1,100°C). Neutronic calculations determine the neutron flux conditions as well as the nuclear heating within the experiments. These results are used as inputs to detailed thermal finite element calculations, which are required to evaluate the complex, three-dimensional heat transfer that occurs within WEC’s wireless sensor enclosures. Initial results show that the temperatures of the sensors’ enclosures and the metal bellows can be operated near the temperature range of LWR coolants and cladding while simultaneously increasing the temperature of a surrogate fuel material to values in the range of 800–1200°C to simulate centerline fuel temperatures during LWR operation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Stochastic Optimization and Uncertainty Quantification of Natrium-based Nuclear-Renewable Energy Systems for Flexible Power Applications in Deregulated Markets

Rapid integration of variable renewable energy sources (VRES) has made modeling and stochastic optimization of hybrid energy systems crucial for studying their long-term performance and viability. However, most studies have focused on just historical data, which may be unreliable for capturing short-term fluctuations, rare events, and long-term patterns of energy demand, price, and the variability of renewable energy sources. For this study, optimal synthetic time series models were developed using Wasserstein distance. The models were validated by comparing the key statistical measures against those of the historical data. They were then used to optimize the integrated Natrium-style advanced energy systems and their long-term (30 years) economics. The stochastic model performs bi-level optimization to find the optimal sizes for the balance of plant and thermal energy storage, while also optimizing energy dispatch to achieve the maximum net present value. In studies of two deregulated markets (California ISO and the Electric Reliability Council of Texas), the integrated Natrium-style system performed better in CAISO than in ERCOT, given higher and more consistent electricity prices during peak-demand periods. The potentially enlarged cost associated with the variable operation and maintenance of the TES system also plays a significant role in driving the system sizing, thus its impacts on the system are investigated in detail through comparison against a baseline case. The study also finds that the bi-level optimization results based on stochastic gradient descent closely match the grid search results. The uncertainty quantification of the stochastic signals provides further NPV-related insights and probability distributions for the case studies. The normal standard error of the mean of NPV for the case with and without TES VOM for CAISO were found to be 7.73M (plus-minus sign) 1.09M USD and 104.99M (plus-minus sign) 1.25M USD, respectively based on a 95% confidence. Given the relatively small NPV variance based on 150 samples, the analysis affords the most robust possible prediction of the techno-economic performance of the integrated Natrium-style energy systems.

25 ENERGY STORAGE↗
DOE OSTI2025

Spatial Impacts of Electric Vehicle Charging on Power Grid Stability: A Downtown Atlanta Case Study

The rapid increase in electric vehicle (EV) charging demand poses a potential risk to power grid stability, particularly as the spatial distribution of this demand remains underexplored. Existing research often focuses on technical optimization models while overlooking the geographic and human dynamics that affect energy consumption. This study addresses this gap by incorporating mobility data to estimate both building energy use and EV charging demand while also considering geographic factors for a better understanding of grid load. Using agent-based simulations and the Open-Source Distribution System Simulator, the study evaluates the effect of various EV penetration scenarios on grid voltage and unbalance. The results show that, although voltage remains within acceptable limits at lower EV penetration rates, significant voltage drop and unbalance occur as EV penetration exceeds 40%, particularly in residential areas with high charging demand. This study offers a framework for integrating spatial analysis and mobility data in power network simulations, providing insights for future EV infrastructure planning.

Pan, Melrose [ORNL] (ORCID:000000031627448X)↗
DOE OSTI2021

On the Use of Smart Meter Data to Estimate the Voltage Magnitude on the Primary Side of Distribution Service Transformers

This paper develops a novel method to estimate the voltage magnitude on the primary side of distribution service transformers. The proposed method relies exclusively on smart meters, and therefore it is fully data-driven. This is an important feature because electric utilities have detailed models of only the primary network - that is, the network between the distribution substation and the primary side of service transformers that are installed closer to end-customer sites. The network that connects the secondary side of service transformers to end-customer sites, referred to as the secondary network, is simply represented by a lumped load. For each secondary network, the proposed method uses data acquired from only 2 smart meters: the closest and the farthest-in the sense of electrical distance - from the service transformer. As a reference to this feature, the proposed method is named SM2Vp. To our knowledge, this is the first time a method is shown to provide actionable information for realtime operation and control of power distribution grids using only two smart meters per secondary network. This is important because utilities have experienced barriers in managing and using large data sets for real-time operation and control. SM2Vp is primarily intended to provide pseudo-measurements for distribution system state estimation, but it can also be used directly for voltage control schemes. The performance of SM2Vp is demonstrated by numerical simulations carried out on three secondary network synthetic models and by using field data provided by a utility partner serving customers in southwestern California. A maximum relative error of approximately 3.9% or less is observed for the primary voltage magnitude estimates in all numerical experiments.

distribution service transformer↗
DOE OSTI2022

Arc Flash Evaluation Poster

Arc flash evaluation is a key aspect of assessing the safety of an electrical system. An arc flash occurs when a short circuit results in large amounts of unexpected current in a conductor leading to a massive release of energy. By conducting an arc flash evaluation engineers are able to design safer systems and determine the level of protective equipment that a worker needs to wear in order to survive an arc flash incident.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

A General Method for Estimating Zonal Transmission Interface Limits from Nodal Network Data: Preprint

Capacity expansion models for the electric power system often employ zonal (rather than nodal) resolution, necessitating estimates of aggregate power transfer limits across the interfaces between model zones. Interface limits between planning areas are sometimes published, but they are not generalizable to arbitrary zone shapes. There is thus a need for a reproducible method for estimating interface transfer limits (ITLs) between user-defined zones directly from nodal transmission system data. Here, we present a simple method for estimating ITLs using a DC power flow approximation via the power transfer distribution factor (PTDF) matrix. Linear optimization is performed to identify the distribution of power flows that maximizes the total flow on interface-crossing lines, subject to individual line ratings, limits on bus injection/withdrawal, and the relationships among flows, injections, and withdrawals imposed by the PTDF matrix. We demonstrate the application of the method on a 134-zone ~65000-bus system, and we explore the influence of flow direction, contingency level, and zone size on the estimated ITLs. There is significant heterogeneity in the ratio of the ITL to the sum of interface-crossing line ratings, which highlights the importance of accounting for the physical constraints on power flows imposed by Kirchhoff's laws when estimating zonal ITLs.

17 WIND ENERGY↗
DOE OSTI2021

Numerical Investigation of Enhanced Dehumidification Processes By Using Dielectrophoresis Principles in Moist Airflows

Dispersed particle-laden flows are encountered in many building and industrial applications, such as flow in a fluidized bed, hydrocarbon transportation in pipelines, and the fouling of air-cooled heat exchangers (Kuruneru et al., 2016; Ray et al., 2019; Wang et al., 2019). Computational fluid dynamic (CFD) models have been developed in recent years to depict particle-fluid and particle-particle interactions in laminar or turbulent flows with increasing accuracy and stability. One particular particle-laden system of interest for moisture control is electrically-enhanced condensation in air and water droplet flows. Electrically-enhanced condensation consists of the use of highly charged water droplets injected in the moist air. The droplets become electric seeds that attract polar water vapor molecules to their surfaces and promote condensation. The nucleation and growth of the charged droplets deplete the vapor phase near a droplet, which is compensated for by the dielectrophoresis flow and diffusion. Dielectrophoresis flow involves surrounding vapor at a distance of about 10 to 100 nm for droplets charged by an electrospray compared to ~2 nm for a single electron charge in a droplet. As the vapor molecules collapse on the surface of the droplets, their initial electrical charge decreases with time due to the neutralization of the ions. While the physics of this phenomena is well known, engineering models for predicting the condensation rates are not available. This work computationally investigates dehumidification of moist airflow in a converging rectangular duct. The objective is to develop an engineering model that predicts water vapor condensation by employing dielectrophoresis principles. We construct a Computational Fluid Dynamics (CFD) model of the duct with electrically-enhanced condensation. The model is implemented in the open-source software OpenFOAM. We utilize the Multi-Phase Particle-In-Cell (MP-PIC) method coupled with a Population Balance Equation (PBE) approach to simulate the particle-laden system. This methodology is an Eulerian-Lagrangian approach used to simulate the droplets' behavior in the humid air. The MP-PIC approach (Andrews and O'Rourke, 1996) mitigates the computational cost by parceling several fundamental particles with similar properties (such as types, sizes, and temperature) into one computational particle. Thus, the billions of particles can be substituted by millions of computational particles without significant loss of information. The PBE was considered with the Lagrangian frame to combine the particle distribution function used in MP-PIC (Kim et al., 2020). This approach preserves mass and energy conservation between the phases in the Eulerian and Lagrangian structures. The PBE in this procedure was directly linked to the discrete parcels, making the simulation of the particle distribution computationally efficient and robust. The MP-PIC-PBE approach used in the present work was applied to the dehumidification of air. Water droplets were injected in the air stream and forced to grow according to experimentally derived correlation. The experiments were conducted on a converging duct with the same geometry and boundary conditions used to build the CFD model. This approach enabled us to approximate the effect of dielectrophoresis phenomena on the droplet and air interface. This presentation will discuss the details of the new CFD model built for the duct, the implementation of the model in OpenFOAM CFD programming language, and the experimental validation of the newly developed model. The results revealed a moderate yet measurable increase in droplet diameter due to water vapor condensation at the vapor-liquid interface of the electrically charged droplets' surface. The seed water droplet particles grew in size by capturing the water vapor in the surrounding air. The OpenFOAM model predicted reductions of humidity in the air from 5 to 10 percent.

Yel Mahi, Maliha↗
DOE OSTI2025

Comparative analysis of thermal management systems in electric vehicles at extreme weather conditions: Case study on Nissan Leaf 2019 Plus, Chevrolet Bolt 2020 and Tesla Model 3 2020

With the surge in electric vehicle (EV) adoption and the need for extended driving ranges, optimizing energy efficiency, particularly through thermal management, is critical, especially in extreme weather. Managing the substantial energy needed for cabin climate control and battery temperature regulation can increase energy demands by over 50 %, severely limiting range. This study conducts a comparative analysis of thermal management systems (TMS) in three popular EV vehicles, 2020 Chevrolet Bolt, 2019 Nissan Leaf Plus, and 2020 Tesla Model 3, evaluating their distinct TMS configurations and performance under varied weather conditions. Using both numerical simulations and experimental data collected on a controlled test bench at Argonne National Laboratory, we assess how TMS architecture and operational modes influence energy consumption and range. A comprehensive TMS model was developed, integrating cabin and battery thermal sub-models in the Autonomie software platform, to simulate temperature fluctuations and range impacts. Cabin climate was modeled using a mono-zonal approach, while battery cell temperature distribution was estimated through a 2D nodal structure. Each vehicle's distinct TMS setup was evaluated: the Chevrolet Bolt and Tesla Model 3 use a dual evaporator vapor compression cycle with a PTC heater for the cabin and a coolant loop for battery thermal management; the Nissan Leaf Plus employs a heat pump with a PTC heater for the cabin and air-cooling for the battery. Tests conducted at ambient temperatures of 35°C, 22°C, -7°C, and -18°C reveal significant differences in energy use and range reduction across both configurations and conditions. At 35°C, the Tesla Model 3, Chevrolet Bolt, and Nissan Leaf Plus have a range reduction of 8%, 9%, and 13%, respectively, due to air conditioning. In winter, heating technology is paramount; at -7°C, the Nissan Leaf's heat pump configuration achieves a lower range reduction (19.3%) compared to the Tesla and Chevrolet Bolt PTC heaters, which reduce range by 28.3% and 31%, respectively. Further, this study provides valuable insights for automotive engineers, EV technology researchers, and thermal management system designers aiming to enhance electric vehicle performance by understanding how different weather conditions and TMS architectures impact energy consumption and driving range.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Cyber–physical vulnerability and resiliency analysis for DER integration: A review, challenges and research needs

High penetration of renewable and sustainable Distributed Energy Resources (DER) into the traditional distribution system requires a well-coordinated control strategy for the improvement of system-wide reliability and resiliency. Implementation of such a holistic control architecture requires a flexible, near real-time, and bi-directional communication framework for facilitating the participation of various agents in a multi-vendor heterogeneous smart grid. While the sustainability of energy generation is ensured, this exposes the smart grid to extrinsic cyber threats, and appropriate defense mechanism(s) must be deployed to guarantee continued reliability and resiliency of the power grid. Further, the comprehensive literature review presented in this paper discusses the latest trends in the DER control schemes with fast communication requirements and their accompanying cyber–physical vulnerabilities. These control schemes are compared and contrasted for various traits. A three-level DER system architecture has been depicted, facilitating the deployment of these control schemes. The current developments of standard communication protocols, key security mechanisms, and best practices along major standards and guidelines are explored. The impacts of different attack types with miscellaneous DER functions based on various control schemes and associated mitigation solutions are also provided. Finally, challenges and future research directions for limiting cyber-power susceptibility to enhance resiliency are summarized. The work presented here will help us enabling a cyber-resilient and sustainable smart electric grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Nonnuclear Experimental Capabilities to Support Design, Development, and Demonstration of Microreactors

This work provides a summary of selected experimental capabilities being developed to support nonnuclear testing and demonstration of technology in support of microreactors under the U.S. Department of Energy’s (DOE’s) Microreactor Program. Major capabilities include the Single Primary Heat Extraction and Removal Emulator (SPHERE) and the Microreactor Agile Non-nuclear Experimental Test Bed (MAGNET). The SPHERE facility allows for controlled testing of the steady-state and transient heat rejection capabilities of a single heat pipe using electrical heaters that simulate nuclear heating. The facility is capable of monitoring axial temperature profiles along the heat pipe and surrounding test articles during startup, steady-state operation, and transients. Instrumentation includes noncontact infrared thermal imaging, surface thermocouples, spatially distributed fiber optic temperature and strain sensors, electrical power meters, and a water-cooled, gas-gap calorimeter for quantifying heat rejection from the heat pipe. The facility can be operated under both vacuum and inert-gas conditions. The MAGNET facility is a large-scale, 250-kW electrically heated microreactor test bed to enable nonnuclear experimental evaluation of a variety of microreactor concepts. It can be supplied to electrically heat a scaled section of a microreactor and further test the capabilities of heat rejection systems. The initial MAGNET experiments will support technology maturation and reduce uncertainty and risk associated with the design, operation, and deployment of monolithic heat pipe–based reactors. However, this test bed can broadly be applied to multiple microreactor concepts to evaluate a wide range of thermal-hydraulic and structural phenomena such as interface coupling with power conversion units and other collocated systems. MAGNET can evaluate integral thermomechanical effects during electrical heating of an array of heat pipes in a larger test article. Examples of initial testing will include thermal stresses in the monolith and the impact of debonding of a heat pipe from the core block and how that failure could impact surrounding heat pipes, i.e., understanding the potential for cascading failure. This work also discusses some modeling capabilities that can support experiment design, analysis, and interpretation, including the heat pipe code Sockeye and a comparison of thermal-structural simulations performed using ABAQUS and STAR-CCM+.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Equalization of Intensity-Modulated Fiber-Optic Voltage Sensors for Power Distribution Systems

We test fiber-optic voltage sensors based on optical reflection from a piezoelectric transducer. Our specific devices possess a 2 kHz fundamental resonance, and we verify a readily usable frequency band from approximately 10 Hz to 3 kHz, with a dynamic range of 60 dB for a detection system integrating over this entire band. Additionally, we demonstrate a digital signal processing approach to equalize the measured frequency response, enabling accurate retrieval of short-pulse inputs. These results suggest the value and applicability of intensity-modulated fiber-optic voltage sensors for measuring both steady-state waveforms and broadband transients which, coupled with the straightforward and compact design of the sensors, should make them effective tools in electric grid monitoring.

42 ENGINEERING↗
DOE OSTI2021

On the Use of Smart Meter Data to Estimate the Voltage Magnitude on the Primary Side of Distribution Service Transformers: Preprint

This paper develops a novel method to estimate the voltage magnitude on the primary side of distribution service transformers. The proposed method relies exclusively on smart meters, and therefore it is fully data-driven. This is an important feature because electric utilities have detailed models of only the primary network--that is, the network between the distribution substation and the primary side of service transformers that are installed closer to end-customer sites. The network that connects the secondary side of service transformers to end-customer sites, referred to as the secondary network, is simply represented by a lumped load. For each secondary network, the proposed method uses data acquired from only 2 smart meters: the closest and the farthest--in the sense of electrical distance--from the service transformer. As a reference to this feature, the proposed method is named SM2Vp. To our knowledge, this is the first time a method is shown to provide actionable information for real-time operation and control of power distribution grids using only two smart meters per secondary network. This is important because utilities have experienced barriers in managing and using large data sets for real-time operation and control. SM2Vp is primarily intended to provide pseudo-measurements for distribution system state estimation, but it can also be used directly for voltage control schemes. The performance of SM2Vp is demonstrated by numerical simulations carried out on three secondary network synthetic models and by using field data provided by a utility partner serving customers in southwestern California. A maximum relative error of approximately 3.9% or less is observed for the primary voltage magnitude estimates in all numerical experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Large Scale Pumped Storage to Support Renewable Deployment; PSH Resource Assessment and Complementary Analysis for Alaska

The State of Alaska has a rather unique electric power system, as it has two larger transmission grids (Railbelt and Southeast Alaska) and over 150 islanded stand-alone power systems that are serving remote rural communities. In 2010, the Alaska legislature enacted a non-binding goal for 50% of renewable electricity generation by 2025. With the expected increase in wind and solar generation in the future, the role of energy storage becomes increasingly important. Considering the specific power system characteristics in Alaska, energy storage technologies that can supply electricity over an extended period of time, such as pumped storage hydropower (PSH), may play a key role in enabling the reliability and resiliency of both integrated and rural power systems. The overarching objective of the subject study of this presentation is to investigate the prospects and opportunities for PSH in Alaska.

Alaska↗
DOE OSTI2024

South Asia Group for Energy - Bhutan

Bhutan's electricity system is already low-carbon through the use of hydropower. However, generation from hydroelectric plants is reduced during the dry winter months and will be impacted by climate change and other extreme weather events. Bhutan is mitigating these risks by diversifying their energy mix with clean energy resources. Bhutan is exploring photovoltaic (PV) solar energy development to enhance its energy system's overall resilience. To ensure efficient grid planning and solar integration, Bhutan's power generator, Druk Green Power Corporation, and the transmission and distribution utility, Bhutan Power Corporation, are partnering with the South Asia Group for Energy (SAGE) to develop their solar capabilities, integrate solar energy into the grid, and strengthen Bhutan's energy infrastructure and efficiency.

Bhutan↗
DOE OSTI2022

Small Hydropower Interconnections: Best Practices

Small hydropower projects have been the predominant source of capacity growth of U.S. hydropower for more than a decade, and they present the most cost-effective and environmentally permissible avenues for hydropower growth (DOE 2016; Johnson et al. 2018). However, interconnection to electricity distribution and transmission grids is a persistent barrier due to cost surprises and schedule overruns. As a culmination to research into the status and requirements of small hydropower interconnection across the United States, this paper presents the best practices for setting interconnection standards that can improve the process for small hydropower developers. As part of the analysis, the interconnection costs are compared between small hydropower, solar, and wind. The analysis of the small hydropower interconnection landscape across the United States was carried out by Pacific Northwest National Laboratory (PNNL) and Oak Ridge National Laboratory (ORNL) with support from the U.S. Department of Energy Water Power Technologies Office. The research team was guided by a Technical Advisory Group (TAG) and gleaned data from publicly available sources, such as the HydroSource database (ORNL 2020) and interconnection queues hosted by utilities, balancing authorities, independent system operators (ISOs), and regional transmission organizations (RTOs). The results of this work are shared in a series of papers detailing the state of small hydropower in the United States (“Small Hydropower Interconnections: Small Hydropower in the United States”), the variety of state interconnection processes to connect power generators with the grid (“Small Hydropower Interconnections: State Interconnection Processes”), and an analysis of the interconnection processes (“Small Hydropower Interconnections: Analysis of Interconnection Processes”). In this, the final paper in the series, best practices for interconnection processes (“Small Hydropower Interconnections: Best Practices”) are identified from the solar energy and distributed wind energy industries that are transferrable to small hydropower development. This information will help overcome barriers to future small hydropower development.

13 HYDRO ENERGY↗
DOE OSTI2022

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

Residential buildings consume 4.4 quads of electricity annually, approximately 37% of the total electricity consumption in the United States. This represents a vast resource that can be used for demand management and other ancillary services. This project aims to develop a robust, scalable hierarchical transactional control mechanism incorporating elements of model-free control (MFC) and game theory to harness buildings to provide ancillary services to the grid. This approach is being taken to address the challenges of incorporating traditional transactional control schemes into existing buildings. The challenges include small individual building sizes requiring aggregation of many buildings, unpredictable energy usage that makes model identification difficult, and satisfying the sensitive occupant comfort constraints. In the proposed approach, by separating the control mechanism into two layers above and below the load aggregator, MFC can be used below the aggregator to modulate flexible building loads in response to pricing signals with guaranteed performance. This allows the burden of identifying an accurate model of the system to be shifted to the above-aggregator layer, where fluctuations in individual building usage have less impact on predicted building system behavior. Game theory concepts can then be used to determine pricing curves and control signals among regional aggregators. Managing this control in a game-theoretic approach will allow us to build in financial incentives that increase customer engagement. Additionally, the usage of MFC necessitates less burdensome computational and communication requirements, thus, it is easily deployable on small, embedded devices. In a broader sense, developing a strategy capable of effectively incorporating residential and small commercial buildings will allow greater throughput of existing and emerging grid services in addition to future transactive energy grid management methods. Using MFC within a hierarchical control architecture will allow the shifting of existing forecasting challenges to an aggregate level, where dynamics are slower and more predictable. This will enable a smooth interface between the grid services requests of utilities and the reliable control required by participating buildings. MFC, which supports distributed control architecture, permits a scalable solution that can be deployed to neighborhood-size systems as well as individual buildings. This project focuses on three objectives: (1) developing the mathematical framework, algorithm toolkit, and software toolset of the two-layer transactive control testbed; (2) developing a scalable solution for application over many residential and small-size commercial buildings with sparse distributed communication; and (3) field testing and implementation on hardware of the control strategies developed in the previous two objectives. The research and development activities are focused and designed to be impactful within the relevant 2025 targets timeframe. An open-source control framework for exploiting variability and dispatchability of building loads will be delivered as the outcome of the project. This capability enables greater participation of loads in electricity markets and ancillary services that are both useful for the utility and financially beneficial for building owners.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗