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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Brick Schema Standardized Plug Load Control Strategies for Load Reduction: Preprint

Plug loads comprise a significant percentage of commercial building energy consumption. Applying intelligent controls to turn off plug loads when unused can provide dynamic load reduction and flexibility, which are key traits of grid-interactive efficient buildings. This capability is important for equitable decarbonization as it can enable disadvantaged communities to electrify buildings without costly upgrades to electrical infrastructure. In this work, we present the effectiveness of various control strategies along with the operational lessons that informed their design. During a three-year period, we operated over 600 smart outlets in 12 university office buildings. The attached plug loads consisted primarily of printers, TVs, water dispensers, and copiers. After recording baseline power measurements for one year, we designed plug load control (PLC) strategies for each plug load type, use, and for different risk tolerance levels because PLC can potentially be disruptive to daily work. We used the Brick Schema to facilitate the management of plug load locations and other metadata. For advanced controls, we integrated the smart plugs with heating, ventilation, and air conditioning (HVAC) systems through the campus building automation system. We found static schedules to be the least disruptive and most predictable for occupants, resulting in 38% and 66% energy savings in two studies. For printers, print server-triggered PLC produced 86% savings, the highest of all strategies with minimal occupant impact. Scheduling of water dispensers and digital signage TVs produced 49% and 70% savings respectively with opportunities to improve performance with the use of HVAC occupancy data.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
DOE OSTI2022

Multiport Control with Partial Power Processing in Solid-State Transformer for PV, Storage, and Fast-Charging Electric Vehicle Integration

This article proposes a multiport control method to enable partial power processing (PPP) in a medium-voltage (MV) multiport solid-state transformer (SST). MV multiport SSTs are promising in integrating low-voltage DC sources or loads such as solar photovoltaic, energy storage, and electric vehicles into smart grids without bulky line-frequency transformers. Compared to voltage-source SST, current-source (CS) SST features single-stage isolated bidirectional AC/AC, AC/DC, or DC/DC conversion using an inductive DC link. For a multiport CS SST, it is revealed in this article that the PPP capability can be enabled through the proposed control without extra hardware, different from the case of voltage-source converters where special hardware architecture is required for the PPP. With the PPP, most power exchange between LV ports is processed by only a fraction of the entire conversion stage, leading to reduced DC-link current, volume, loss, and improved efficiency. The proposed multiport PPP control scheme is analyzed to verify the advantages across a wide voltage and power range against conventional full power processing (FPP) multiport control, using the soft-switching solid-state transformer (S4T) with reduced conduction loss as an example. Comparative experimental results based on a SiC three-port S4T prototype verify the effectiveness of the proposed PPP scheme against the FPP scheme under both steady state and dynamic conditions. Here, the DC-link current reduction is measured to be more than 36%. Significantly, the proposed multiport PPP control scheme is generic and applicable to any hard-switching or soft-switching CS SSTs without extra hardware.

14 SOLAR ENERGY↗
DOE OSTI2021

Distributed, Intelligent Edge-Sensing for a Smarter Grid

The electric grid is undergoing major transformations and developments resulting in unprecedented levels of volatility, uncertainty, and stress on grid infrastructure. Smart sensors and methods aiding in advanced visibility and situational awareness are key for tackling these issues. In this work, a decentralized architecture is proposed, where sensing, local computation and control capability are embedded in the edge devices, communicating with a set of trusted 'data mules' in a 'delay-tolerant' manner, while functioning autonomously. This system has been designed and implemented as an overall platform – called Global Asset Monitoring, Management and Analytics (GAMMA) Platform intended to provide the backbone for a global array of sensors and actuators. Further, as a building block for advanced current sensing solutions, a smart, low-cost ‘clip-on’ current sensor based on PCB-embedded Rogowski coil has been developed. The sensor hosts a novel signal conditioning stage allowing an 'auto-tuning' feature, resulting in a universal current sensor design for measuring a wide range of currents, including faults for smart grid applications. Finally, the research proposes a method to instrument and monitor key parameters for the most common electric utility asset – the pole-top distribution transformer. The work done in this research enables scalable, edge-intelligent sensing solutions for monitoring grid infrastructure, allowing utility operators to gain advanced visibility in an economical way.

Kulkarni, Shreyas Bhalchandra↗
DOE OSTI2022

A hybrid architecture for volt-var control in active distribution grids

Modern active distribution grids are characterized by the increasing penetration of distributed energy resources (DERs). The proper coordination and scheduling of a large numbers of these small-scale and spatially distributed DERs is necessary, and warrants the use of novel distributed approaches. In this paper, we propose a hybrid volt-var control architecture for the distribution grid, which leverages existing centralized and local approaches to planning, decision making, and control, and augments it with distributed optimization and distributed control for DER management. First, we propose a convex model to describe the power physics of distribution grids of meshed topology and unbalanced structure, based on current injection and McCormick Envelopes. Second, we employ the distributed proximal atomic coordination (PAC) algorithm to coordinate DERs to provide voltage support. We implement volt-var optimization by optimally coordinating DERs including PV smart inverters and demand response. We present results using the IEEE-34 bus network, using real data from a distribution feeder in Hawaii, to model load and PV generation. Different levels of DER penetration and objective functions are simulated. Finally, our results show the need for the coordination of DERs to improve voltage profiles, even in networks with existing voltage control devices. Further, we show the need for flexible reactive power capabilities to achieve desired grid performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Guest Editorial Special Section on Advanced Medium-Voltage Power Electronics for Grid Interactive Applications

Medium-voltage power electronics (MVPE) plays essential roles in power grid modernization and links the MV distribution grid with low-voltage consumers and prosumers. Various MVPE devices, such as solid-state transformers or circuit breakers, inverter-based resources, power flow controllers, etc., bring the benefits of voltage conversion and power regulation in small footprint, power quality and efficiency improvements, and enhancements of grid controllability, flexibility, stability, and resilience. The MVPE also makes it possible for sustainable energy systems, such as solar/wind farms and energy storage generating facilities, to directly access to MV grids without multistage conversions. With their intrinsic intelligence and communications, MVPE enables many new smart grid functions and applications, e.g., dc interconnections and electric vehicle charging, which were not envisioned by traditional power grids otherwise. In addition, the integration of physical power processing units with cyber components forms a cyber-physical system, which is essential for long-term sustainability, development, and environmental preservation. Nonetheless, technical challenges on MVPE device reliability, scalable and efficient converter topologies, control stability, large-scale modeling and simulation, to name a few, need to be addressed and advanced to the next level. In conclusion, this Special Section on Advanced MV Power Electronics for Grid Interactive Applications in IEEE Transactions on Power Electronics (TPEL) provides an insight on some of the recent advances in MVPE and emerging challenges and potential solutions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Demonstration of Utility Managed Smart Charging for Multiple Benefit Streams (Final Report)

In the summer of 2020, the U.S. Department of Energy (DOE) awarded funding to Exelon’s Maryland utilities—Baltimore Gas and Electric (BGE), Delmarva Power & Light (DPL), and Potomac Electric Power Company (Pepco)—to implement the Smart Charge Management (SCM) pilot. This initiative aimed to design and implement managed electric vehicle (EV) charging strategies, evaluate the grid impacts of EV charging, and assess the utilities' ability to control EV load based on real-time grid conditions. The SCM pilot explored four aspects for continued improvement: (1) cybersecurity and managed charging functionality testing of two vendor platforms—WeaveGrid (telematics-based) and Shell Recharge Solutions (network-based)—which pursued charge scheduling and optimization through distinct approaches; (2) an analysis by Argonne National Laboratory (ANL) modeling team of three potential SCM enrollment scenarios within BGE and Pepco service territories over the next decade to assess future scalability; (3) employing customer engagement strategies, including surveys and a responsive pricing approach; and (4) the launch and implementation of pilots in Exelon’s Maryland territories in collaboration with WeaveGrid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Challenges and Opportunities in Decarbonizing the U.S. Energy System

The United States has pledged to develop a 100% carbon-free electric power system by 2035 and a net-zero-emissions economy by 2050. While important advancements have been made in the scale, performance, and economics of clean energy technologies, meeting the nation's ambitious goals will not only require their deployment at scale, but also additional innovation and effective integration of different solutions. Technological developments across the broad suite of low-carbon energy solutions are advancing rapidly, with ongoing innovations in renewable electricity generation, industrial processes, and energy-saving technologies and services, including LED lighting, induction heating, electric vehicles, energy storage solutions, and mobility as a service, plus smart devices, controls, and more efficient and smart buildings. Combining renewable electricity with biotic and abiotic pathways to produce chemicals, fuels, and materials promises to deliver new solutions. Grid-interactive buildings and communities, integrating transportation infrastructure and vehicles, are likely to be significant components of any zero-carbon energy strategy. Low-carbon industrial manufacturing will also make strong contributions to a net-zero economy. While the technical prospects appear promising, variations in the state of infrastructure, jurisdictional and social equity, pollution, economic and socio-cultural constraints, energy resource availability, and supply chain dynamics found in different locations present a range of challenges and demand customized solutions. This paper provides a critical review and offers new insights into the technical, infrastructure, analytic, political, and economic challenges faced in translating the nation's ambitious net-zero-emissions goals into feasible and reliable implementation action plans.

circular economy↗
DOE OSTI2020

Managing time-substitutable electricity usage using dynamic controls

A predictive-control approach allows an electricity provider to monitor and proactively manage peak and off-peak residential intra-day electricity usage in an emerging smart energy grid using time-dependent dynamic pricing incentives. The daily load is modeled as time-shifted, but cost-differentiated and substitutable, copies of the continuously-consumed electricity resource, and a consumer-choice prediction model is constructed to forecast the corresponding intra-day shares of total daily load according to this model. This is embedded within an optimization framework for managing the daily electricity usage. A series of transformations are employed, including the reformulation-linearization technique (RLT) to obtain a Mixed-Integer Programming (MIP) model representation of the resulting nonlinear optimization problem. In addition, various regulatory and pricing constraints are incorporated in conjunction with the specified profit and capacity utilization objectives.

Ghosh, Soumyadip↗
DOE OSTI2023

Chapter 32 - Power Grid Resilience

The new energy paradigm is altering the current power grid trend from synchronous generator reliant system toward power-electronics-based distributed energy resources (DERs). The resilient operation of modern power grid is highly dependent upon cyber and physical reliable operation of DERs. Power grid resilience broadly refers to the ability of the grid to be robust to eventualities and singularities that may disrupt the continuity of reliable power flow. This could involve resilience related to the physical system but more recently, the focus on cyber resilience has been evolving rapidly especially given the burgeoning growth of distributed generation and power-electronics-based DERs under smart grid and given that such threats to reliable operation do not have to evolve localized to where the physical asset is. Commonly, in power grids dominated by DERS, control and energy management are structured at a multitime scale multilayer fashion: (i) primary control layer at microseconds time scale, (ii) secondary control layer at millisecond time scale, and (iii) tertiary control layer at seconds to minutes time scale. The cyber-related issues that may affect the power grid resilience can be introduced in through primary, secondary, and tertiary control layers. The failure of each of these control layers may impact the reliable and resilient operation of the overall network and cause widespread failures which leads to unintended blackouts. As such, this chapter focuses on cyber-related resilience issues in primary control layer, secondary control layer, tertiary control layer, wide area/utility control, and anomaly detection and resilient communication.

anomaly detection↗
DOE OSTI2021

Cyber-Power Co-Simulation for End-to-End Synchrophasor Network Analysis and Applications

The resiliency, reliability and security of the next generation cyber-power smart grid depend upon efficiently leveraging advanced communication and computing technologies. Also, developing real-time data-driven applications is critical to enable wide-area monitoring and control of the cyber-power grid given high-resolution data from Phasor Measurement Units (PMUs). North American Synchrophasor Initiative Network (NASPlnet) provides guidance for PMU data exchanges. With the advancement in networking and grid operation, it is necessary to evaluate the performance of different data flow architectures suggested by NASPInet and analyze the impact on applications. Therefore, we need a cyber-power co-simulation framework that supports very large-scale co-simulation capable of running in parallel, high-performance computing platforms and capturing real-life network behavior. This work presents an end-to-end automated and user-driven cyber-power co-simulation using NS3 to model communication networks, GridPACK to model the power grid, and HELICS as a co-simulation engine. Comparative analysis of latency in synchrophasor networks and a performance evaluation of a power system stabilizer application utilizing PMU data in an IEEE 39 bus test system is presented using this cosimulation testbed.

Mustafa, Hussain M.↗
DOE OSTI2025

DistOPF: Advanced Solutions for Distribution Optimal Power Flow Analysis - DistOPF v0.2 Documentation

To achieve an affordable and reliable energy system, research on power distribution system is often focused on integration of distributed generators, energy storage solution, EV charging, smart meters, and other advanced assets that may benefit from or require more advanced control and optimization techniques. Despite this focus on advanced distribution system topics, early researchers and grid scientists often start from scratch when developing optimization programs for power distribution systems. This report introduces DistOPF, a Python package that consolidates years of research into a versatile and modular tool. DistOPF provides researchers with essential capabilities to solve distribution system Optimal Power Flow (OPF) problems using standard network models. Additionally, it offers a platform to benchmark both new and existing algorithms against established test systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Functional Assessment of Shell Recharge Solutions' SKY™ Platform OpenADR Capability

The project’s overall objective is to research, develop, and conduct a wide-scale demonstration of a utility smart charge management (SCM) system to develop optimal managed charging structures for grid value, evaluate the impact of EV charging on local distribution utility operations, and evaluate the utilities’ ability to control electronic vehicle (EV) charging load based on grid conditions. This report covers Argonne’s validation testing in the first period of the project, the objective of which was to determine the current managed charging functionality of the EVSE hardware, the network and the vehicle telematics software solution and understand gaps that need to be addressed prior to a large-scale demonstration.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Fairness-Aware Distributed Energy Coordination for Voltage Regulation in Power Distribution Systems

The accelerating deployment of solar photovoltaics into low-voltage distribution networks can cause reverse power flow and overvoltage problems. However, if coordinated properly, the real and reactive power flexibility of these resources enables distribution operators to manage their networks more efficiently. Existing literature is rich in droop-based control (Volt-Watt and Volt-VAr) and optimization-based distributed energy coordination for four-quadrant control of photovoltaics to prevent overvoltage issues. While optimal coordination can effectively mitigate overvoltage, it tends to treat resources at sensitive parts of the grid unfairly. Here, to address this concern, we propose a distributed optimal power flow formulation that incorporates fairness in curtailing photovoltaic generation and utilizes the reactive power capability of smart inverters. The proposed distributed formulation allows for scalable resource aggregation that can be leveraged to achieve fairness within a certain segment of the grid and/or fairness across the entire network. Fair curtailment of photovoltaic systems is demonstrated with aggregation at each of two layers in a distribution network: 1) area-level fairness and 2) feeder-level fairness. To explore the trade-off between fairness and optimal utilization, the fairness-aware control actions are compared against the performance of a centralized controller that aims to maximize the aggregate PV generation without incorporating fairness. Simulation results show that introducing area-level fairness increased curtailment by 0.0101 percentage points and feeder-level fairness increased curtailment by 0.0458 percentage points compared to a fairness-agnostic control.

Poudel, Shiva↗
DOE OSTI2021

Power Converter Topologies for Electrolyzer Applications to Enable Electric Grid Services

Hydrogen electrolyzers, with their operational flexibility, can be configured as smart dynamic loads which can provide grid services and facilitate the integration of more renewable energy sources into the electrical grid. However, to enable this ability, the electrolyzer system should be able to control both active and reactive power in coordination with the low-level controller of the electrolyzer via the power electronics system interface between the utility grid and electrolyzer. This paper discusses power converter topologies and the control scheme of this power electronics interface for electrolyzer applications to enable electricity grid services. For the sake of unity, in this paper, we consider the power converter system interfacing the utility grid at the line-to-line root mean square (RMS) value of 480 VAC-60 Hz and supplying to the 3500 A-750 kW PEM electrolyzer stack.

electrolyzer↗
DOE OSTI2022

Development of a water source heat pump hardware-in-the-loop (HIL) testing facility for smart building applications

Over the last decade, the global fight against climate change through electrification has led to an increase in research on building heating, ventilation, and air conditioning (HVAC) systems that utilize intelligent control algorithms to provide demand-side grid service while maintaining the thermal comfort of building occupants. As the pivotalpoint between building electricity consumption and indoor thermal comfort, high-efficiency electrical heatpumps are at the center of these emerging studies, and various grid-interactive and occupant-comfort control algorithms have been developed for them. The impact of these algorithms on the heatpump operation andperformance under different weather, building load, and grid requests calls for investigation and verification via experimental tests with actual heat pumps integrated with real-time building and grid responses. This study presents a Water-Source Heat Pump Hardware-in-The-Loop (HIL) Test Facility developed with the capability to perform such tests. The hardware configuration for this testfacility introduces a hydronic system that emulates the conditions for the heat pump water-side, and a duct system that emulates conditions for the heat pump airside. Both data acquisition and emulator control are implemented through the National Instruments (NI) LabVIEW software running on an NI PXIplatform. The HIL mechanism based on the hardware-software integration that allows the testbed to communicate with a generic simulation environment is also discussed. Currently, the test facility setup includes a single heatpump and virtual building model in EnergyPlus coupled with an occupant behavioral model in MATLAB. Preliminary test results of the current setup demonstrate the building load emulator's ability to track the simulated gone temperature with a Root Mean Square Deviation (RSME) below 0.12°C (0.216°F). An uncertainty analysis based on sensor accuracies shows that the heat pump coefficient of performance (COP) can be measured with a relative uncertainty of 10.4% in cooling and 3.7% in heating. Apartfrom the current testing on a single heat pump, the test facility also provides the flexibility to include additional heat pumps to form a heat pump cluster, as well as coupling the heat pump with active thermal storage to provide enhanced demandflexibility.

Calfa, Caleb↗
NASA NTRS1993

Optical beam forming techniques for phased array antennas

Conventional phased array antennas using waveguide or coax for signal distribution are impractical for large scale implementation on satellites or spacecraft because they exhibit prohibitively large system size, heavy weight, high attenuation loss, limited bandwidth, sensitivity to electromagnetic interference (EMI) temperature drifts and phase instability. However, optical beam forming systems are smaller, lighter, and more flexible. Three optical beam forming techniques are identified as applicable to large spaceborne phased array antennas. They are (1) the optical fiber replacement of conventional RF phased array distribution and control components, (2) spatial beam forming, and (3) optical beam splitting with integrated quasi-optical components. The optical fiber replacement and the spatial beam forming approaches were pursued by many organizations. Two new optical beam forming architectures are presented. Both architectures involve monolithic integration of the antenna radiating elements with quasi-optical grid detector arrays. The advantages of the grid detector array in the optical process are the higher power handling capability and the dynamic range. One architecture involves a modified version of the original spatial beam forming approach. The basic difference is the spatial light modulator (SLM) device for controlling the aperture field distribution. The original liquid crystal light valve SLM is replaced by an optical shuffling SLM, which was demonstrated for the 'smart pixel' technology. The advantages are the capability of generating the agile beams of a phased array antenna and to provide simultaneous transmit and receive functions. The second architecture considered is the optical beam splitting approach. This architecture involves an alternative amplitude control for each antenna element with an optical beam power divider comprised of mirrors and beam splitters. It also implements the quasi-optical grid phase shifter for phase control and grid amplifier for RF power. The advantages are no SLM is required for this approach, and the complete antenna system is capable of full monolithic integration.

Wu, Te-Kao↗
DOE OSTI2022

End-to-end Analytics for Grid Arch Design & All-hazard Assessment

Resiliency, reliability, and security of the next-generation smart grid depend upon leveraging advanced communication and computing technologies, integrating them with physical power systems, and developing real-time, fast, data-based applications to help in wide-area monitoring and control of the grid. Using a high sampling data rate from phasor measurement units (PMUs) to develop applications has opened the door to achieving the next-generation grid requirements. The North American Synchrophasor Initiative Network (NASPlnet) was developed in 2007-09 to create a standard and guide for PMU data exchanges. With the advancement in both networking and grid requirements, it is necessary to evaluate the performance of different NASPInet versions and their impact on applications. Therefore, we need a cyber-power cosimulation framework that supports very large-scale co-simulation capable of running in parallel, high-performance computing platforms and capturing real-life network behavior. This work presents a cyber-physical co-simulation testbed using NS3 to model the communication network, GridPACK to model the power grid, and HELICS as a co-simulation engine. Comparative analysis of latency in synchrophasor networks and a performance evaluation of a power system stabilizer application based on PMU data in an Institute of Electrical and Electronics Engineers 39-bus test system is presented using this co-simulation testbed.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Intelligent Control of Thermal Energy Storage in the Manufacturing Sector for Plant-Level Grid Response

Industrial facilities are seeking new strategies that help in providing savings mechanisms for demand charges. Demand charges are the charges incurred by industrial facilities as a result of power usage. Thermal energy storage has advanced significantly with lots of new applications, garnering the interest of many industrial facilities. These applications could be used to shave the industrial facilities’ peak electric demand and reduce their demand charges. This paper aims to demonstrate the efficacy of thermal energy storage in reducing demand charges and highlight new developments in the integration of smart control systems with thermal energy storage. The study compares energy consumption and peak demand for a facility equipped with and without thermal energy storage tanks using a fixed schedule for charging and discharging. Additionally, the paper examines the impact of incorporating a smart controller to determine when to charge and discharge the tank based on the facility’s real-time power usage and a given setpoint. The results indicate cost savings from the use of thermal energy storage tanks under two proposed scenarios, reflected in the reduced cost of power consumption for the studied facility. The incorporation of a smart controller with the thermal energy storage tank in the facility studied could provide estimated savings of 3.3% per year of power consumption charges, without considering the contribution of any incentives. The estimated savings provided by the fixed schedule scenario are 2.7% per year.

25 ENERGY STORAGE↗