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DOE OSTI2021

Stacked Low-Inertia Converter or Solid-State Transformer: Modeling and Model Predictive Priority-Shifting Control for Voltage Balance

This paper presents control challenges of stacked low-inertia converter (SLIC) or cascaded reduced dc-link solid-state transformer (SST) and proposes a novel model predictive priority-shifting (MPPS) control with implicit modulator and a discrete-time large-signal model for voltage balancing and dc-link regulation. Low-inertia converters, featuring small electrolytic capacitor-less dc links, dramatically reduce cost, size, and weight compared to conventional solutions. However, without a large dc-link buffer, the input and output are tightly coupled, leading to significant control challenges. The control becomes even more challenging with these converters stacked input-series output-parallel (ISOP) for medium-voltage (MV) grid, which causes coupling between the modules besides the coupling within each module. This paper analyzes the multi-objective, multi-degree of freedom control problem, using the modular soft-switching solid-state transformer (M-S4T) as an example of the SLIC. First, distribution of control efforts under controller saturation is critical because multiple control objectives can be conflicting, especially when the module voltages are unbalanced and are being restored. The MPPS can shift the priorities to address this issue. Second, due to the low inertia and high dc-link ripple, classic space vector pulse-width modulation (SVPWM), average model with small-ripple assumption, and control design based on small-signal model cannot accurately modulate, model, and control the nonlinear reduced dc link. Therefore, a discrete-time large-signal model of the M-S4T is established to derive the predictive control in the MPPS. The MPPS and the PI control are compared in MV simulations to show the issue of applying the PI to the SLIC and the effectiveness of the MPPS for voltage balancing and dc-link regulation in a deadbeat manner. Finally, the proposed control is tested on a 5 kV ISOP SiC SST prototype to verify priority shifting to address controller saturation issue and fast and robust voltage balancing.

14 SOLAR ENERGY↗

DOE OSTI2021

Robust Predictive Control for Modular Solid-State Transformer With Reduced DC Link and Parameter Mismatch

This paper presents the analysis and implementation of a predictive control method for dc-link regulation and voltage balance in a cascaded modular reduced dc-link solid-state transformer (SST). Passive components like bulky dc links limit the power density of power converters, especially medium-voltage (MV) SST. Reduced dc-link or low-inertia converters can dramatically reduce the size, cost, and weight by tolerating larger dc-link ripples and improve the reliability with electrolytic capacitor-less dc link. However, a small dc link leads to tight coupling between the input and the output stages, which is a challenge for control design. In stacked low-inertia converters (SLIC), the low-inertia converter modules are stacked for MV applications, resulting in coupling between the modules and making the control more challenging. A new model predictive control method which can achieve deadbeat regulation on the dc link without weighting factors has been proposed to address this novel problem. This paper focuses on analyzing the condition of the low-inertia dc link up to 80% ripple, the robustness of the control under parameter mismatches, high-order terms, and important implementation issues such as model-based sampling and computation delay compensation. Significantly, the high-order terms are introduced because of the large dc-link ripple. These high-order terms are unique to the SLIC and negligible in conventional high-inertia converters. A discrete-time large-signal model is built to capture the dc-link’s nonlinear dynamics, and the eigenvalues of a small-signal Jacobian matrix are analyzed with Floquet theory to evaluate stability, using the modular soft-switching solid-state transformer (M-S4T) as an example of the SLIC. Simulation and experimental results of an MVDC M-S4T verify the analysis and the predictive control method. Finally, the general application of the predictive control to low-inertia converters is compared against a conventional PI controller using a reduced dc-link active-front-end (AFE) rectifier as an example.

14 SOLAR ENERGY↗

DOE OSTI2021

New Modulation and Impact of Transformer Leakage Inductance on Current-Source Solid-State Transformer

This article presents a novel modulation scheme for device voltage stress mitigation and comprehensive analysis of the impact of transformer leakage inductance in a current-source solid-state transformer (SST). Different from dual active bridge (DAB) SST, the operation of the current-source SST is similar to that of a flyback converter. The device bridge on only one side of the transformer is active to store energy into or release energy from the magnetizing inductance which acts as a current-source dc link. Such flyback operation with reverse-blocking switches can lead to additional device voltage stress and incomplete zero-voltage switching (ZVS) on the current-source soft-switching solid-state transformer (S4T) under conventional modulation. A new modulation scheme is proposed to address this issue. Moreover, different from the DAB, the leakage inductance of the medium-frequency transformer (MFT) in the S4T is a parasitic element similar to that in a matrix SST and can cause additional device voltage stress. Though the resonant capacitors, originally added to achieve ZVS, can absorb and recycle the leakage energy in the S4T, these capacitors need to be increased with larger leakage inductances to limit the voltage stress. However, large resonant capacitors can result in more lost duty cycles and reduced efficiency. The impact of such leakage inductance on device voltage stress is analyzed comprehensively, which is critical to guide future research and design of the S4T. Experimental results from S4T prototypes for DC-DC, multiport AC-DC, and AC-AC conversion with 1:1 and 4:1 MFT comprehensively verify the proposed concepts. Lastly, a case study of a three-phase AC-AC S4T over a power range from 1 kVA to 100 kVA each module reveals that the MFT leakage inductance should be less than 1% of the magnetizing inductance for safe operation.

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DOE OSTI2022

Predictive Direct DC-Link Control for 7.2 kV Three-Port Low-Inertia Solid-State Transformer With Active Power Decoupling

Promising for applications including renewable energy and electric vehicle fast charging, a medium-voltage (MV) solid-state transformer (SST) typically has multiple modules series stacked, which requires the modules to be single phase. One critical issue of the single-phase SST is the double-line-frequency power ripple. Traditionally, large passives are used to buffer the ripple, resulting in significantly increased volume and cost. This article for the first time proposes active power decoupling (APD) for the SST and a predictive direct DC-link control method, using a current-source single-stage SST as an example. An electrolytic capacitor-less buffer port is used to absorb the ripple, which tolerates up to a 30% voltage ripple for small capacitance. The APD SST control is challenging. First, the current-source SST realizes isolation, DC link, and multiport in a single stage. Second, different from conventional SSTs or APD converters, the low-inertia DC link in this SST has a 40% switching ripple, which is difficult to stabilize. To address the control challenge, a direct DC-link control architecture and a predictive control method are proposed. Simulation and experimental results verify the proposed control method on an MV SiC modular soft-switching solid-state transformer (M-S4T) prototype. Here, the proposed APD reduces the SST volume by 53.8%. Importantly, the proposed concept is not limited to the M-S4T but is generic to other SSTs or APD converters.

14 SOLAR ENERGY↗

DOE OSTI2022

DC-Link Current Minimization Control for Current Source Converter-Based Solid-State Transformer

This article proposes a fast predictive control method and a small DC-link inductor to minimize the DC-link current in current-source converter (CSC)-based solid-state transformer. The DC-link current minimization can significantly reduce power loss and improve efficiency. The challenge of this problem is on improving both steady-state and dynamic performance. PI control methods and large DC-link inductors are conventionally used in the CSC but have limited dynamic performance. A model predictive control (MPC) method is proposed to achieve switching-cycle-level settling time, and the DC-link inductor is sized for 40% ripple to enable fast current change. Importantly, this article also proposes to minimize the DC-link current by varying the current even within a line cycle under single-phase load to improve the steady-state performance, in contrast with the reduction to a constant value in the literature. The proposed MPC features a constant switching frequency without weighting factors. The MPC does not have a high computational burden and is implemented in a regular digital controller for a prototype of soft-switching solid-state transformer (S4T) with reduced conduction loss. The effectiveness of the proposed method has been experimentally verified on the SiC S4T prototype during steady-state and dynamics under different multiport power flow conditions up to 2 kV peak. Here, the DC-link current in the experiments is close to the minimum current with a short zero-vector duration, which further verifies the performance of the proposed method.

14 SOLAR ENERGY↗

DOE OSTI2021

EMOS (Energy Management Optimization System) [SWR-21-46]

EMOS software performs a real-time hierarchal optimal control for energy systems like multi-port electric vehicles charging site with distributed energy resources (DERs) and energy storage systems (ESSs). It gathers information in real-time from electric vehicles, power grid, and DERs, solves a multi-objective energy management optimization problem, and output setpoint for chargers, ESS converters, DERs converters, and grid converters. The software incorporates a novel integration of two control tasks: a) An Energy Management Optimization (EMO), which is the brain of EMOS controller that gathers information in real-time from EVs [e.g., battery size, state-of-charge (SOC), desired SOC, and charge acceptance curve], grid (e.g., electricity price, allowed feeder capacity, ramp rate limit, and reactive power), and DERs (e.g., prediction for solar generation for PV systems). It solves a control optimization problem in real-time to find optimal setpoint for ESSs power dispatch, EVs charging rate, and grid inverters. The objectives are to (1) minimize the charging cost considering grid energy, demand charges, and battery energy, (2) minimize charging time to meet fast charging criterion, (3) keep high energy level on ESSs at the end of an operating period, while satisfying constraints related to grid, EVs, and power converters. b) Real-Time Energy Management System (RT-EMS) is a rule-based algorithm that has faster response than EMO. It receives optimal setpoint from EMO and actual measurements from the system and modify the setpoint to compensate for any fast disturbance in the system, until a new optimum solution is received. Fast disturbances may include vehicle connect/disconnect, unpredicted variation in DERs profiles, variation in grid voltage, errors in PV generation prediction, and others. In addition, RT-EMS regulates voltage at point of common coupling (PCC) by managing reactive power of grid converters.

Mohamed, Ahmed↗

DOE OSTI2021

Model America - data and models of every U.S. building

The 5-year goal of the 'Model America' concept was to generate a model of every building in the United States. This data repository delivers on that goal. Oak Ridge National Laboratory (ORNL) has developed the Automatic Building Energy Modeling (AutoBEM) software suite to process multiple types of data, extract building-specific descriptors, generate building energy models, and simulate them on High Performance Computing (HPC) resources. For more information, see AutoBEM-related publications (bit.ly/AutoBEM). There were 125,714,640 buildings detected in the United States and this dataset contains 122,930,327 (97.8%) buildings which resulted in a successful simulation. Future, annual updates have been proposed that may include additional buildings, data improvements, or other algorithmic enhancements. This dataset of 122.9 million buildings includes: Models (state_county.zip) - OpenStudio (v3.1.0) and EnergyPlus (v9.4) building energy models. Please note that the download requires the free Globus Connect Personal (https://www.globus.org/globus-connect-personal); Each model has approximately 3,000 building input descriptors that can be extracted. Please see the EnergyPlus(v9.4) 2,784-page Input/Output Reference Guide (https://energyplus.net/sites/all/modules/custom/nrel_custom/pdfs/pdfs_v9.4.0/InputOutputReference.pdf) for everything that can be retrieved or simulated from these models. These models were derived from the following metadata, which is not included in this dataset: 1. ID - unique building ID 2. County - county name 3. State - state name 4. CZ - ASHRAE Climate Zone designation 5. Clim_Zone - text label of climate zone 6. est_year - estimated year of construction 7. est_commercial - estimated building type (0=residential, 1=commercial) 8. Centroid - building center location in latitude/longitude (from Footprint2D) 9. Footprint2D - building polygon of 2D footprint (lat1/lon1_lat2/lon2_...) 10. Height - building height (meters) 11. Area2D - footprint area (ft2) 12. BuildingType - DOE prototype building designation (IECC=residential) as implemented by OpenStudio-standards 13. WWR_surfaces - percent of each facade (pair of points from Footprint2D) covered by fenestration/windows (average 14.5% for residential, 40% for commercial buildings) 14. NumFloors - number of floors (above-grade) 15. Area - estimate of total conditioned floor area (ft2) 16. Standard - building vintage. These models are made free and openly available in hopes of stimulating any simulation-informed use case. Data is provided as-is with no warranties, express or implied, regarding fitness for a particular purpose. We wish to thank our sponsors which include Oak Ridge National Laboratory (ORNL) Laboratory Directed Research and Development (LDRD), U.S. Dept. of Energy's (DOE) Building Technologies Office (BTO), Office of Electricity (OE), Biological and Environmental Research (BER), and National Nuclear Security Administration (NNSA). This research used resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357. Please cite as: New, Joshua R., Adams, Mark, Bass, Brett, Berres, Anne, and Clinton, Nicholas (2021). 'Model America - data and models of every U.S. building. [Data set].' Constellation, doi.ccs.ornl.gov/ui/doi/339, April 14, 2021

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DOE OSTI2023

Control development and sizing analysis for a 5th generation district heating and cooling network using Modelica

5th generation district heating and cooling system (5GDHC) are a relatively new concept. They use a single district loop near ambient temperature to provide heating and cooling. This paper improves on the modelling and control of a 5GDHC system called the reservoir network. The study updates the sewage heat exchanger plant model to more realistically represent seasonal changes, uses refined pump models with variable efficiency, introduces a ground coupled district pipe model to consider the inertia of the district network and implements a new control strategy for geothermal storage and sewage heat exchanger. The new approach reduced operating costs, mainly due to pumping cost for storage, sewage heat exchanger plant and distribution pump, while increasing the overall robustness of the approach in different sizing conditions. Thanks to the new controller, the pumping consumption was reduced by 21% with respect to the original baseline. Furthermore, the new control makes the system take better advantage of design changes, when reducing borehole field size and increasing the sewage heat exchanger size, the pumping energy savings become 29% with respect to the original baseline. Lastly, borehole field temperature stability was analyzed through 40 years of simulation.

Zanetti, Ettore↗

DOE OSTI2020

Power-to-Gas Tool: User's Guide

PNNL, working in collaboration with ITM Power and HG&E, has developed a suite of products to support analysis of P2G in Massachusetts. These products include: (a) P2G model that can be accessed at eset.pnnl.gov, (b) P2G system valuation report that describes in detail the methodology underpinning the P2G model and presents the results of 82 scenarios run using the model, and (c) a P2G model user’s guide. This user’s guide accompanies the other products and is designed to simplify the experience of each user, providing useful instructions while guiding users as they input data and interpret results.

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DOE OSTI2021

Cyberguardians & Stem Warriors Career Center: March 31, 2021 Report

As part of the Cyberguardians and STEM Warriors project, the Cyberguardians Career Center serves to provide military veterans and other qualified individuals with career advancement opportunities. The Cyberguardians Career Center is a job board where graduates of the Cyberguardians program may view and apply for open positions in the DER industry.

14 SOLAR ENERGY↗

DOE OSTI2021

Stabilizing the Power System in 2035 and Beyond: Evolving from Grid-Following to Grid-Forming Distributed Inverter Controllers (Final Technical Report)

Under existing grid operations, large synchronous generators provide sufficient rotational inertia to form a rigid backbone for the bulk power system. With photovoltaics (PV) forecasted to provide more than 600 GW of generation by 2050 under the U.S. Department of Energy’s SunShot Initiative objectives, however, it is clear that power electronic inverters will play a dominant role in future systems, and low-inertia stability must be ensured to maintain system reliability. Today, the risks to system stability can be observed on geographically small islands, such as Hawaii, which contain a relatively large amount of installed PV. These risks stem from a fundamental shortcoming of contemporary control strategies—existing inverter controllers cannot guarantee grid stability. Given that future power systems driven by sustainable resources will be characterized by low inertia, locations such as Hawaii provide a glimpse into the obstacles facing future power systems. Considering these challenges, the aim of this project was to develop and demonstrate distributed inverter controllers that enable the reliable control of low-inertia power systems with hundreds of gigawatts of integrated PV.

14 SOLAR ENERGY↗

DOE OSTI2021

North American Renewables Integration Study (NARIS): Cooperative Research and Development Final Report, CRADA Number CRD-16-00633

The goal of the study is to help inform and assist power system planning entities, electricity system operators, government energy agencies, legislators and regulators to better understand the planning, engineering, operational, and economic implications of integrating large amounts of wind, solar and hydro energy into the Canadian, US and Mexican electrical systems.

14 SOLAR ENERGY↗

DOE OSTI2021

Opportunities and Challenges to Capturing Distributed Battery Value via Retail Utility Rates and Programs

Distributed battery deployment is increasing with advanced metering, control, and communication technologies, leaving electric utilities with an under-utilized, flexible grid resource in aggregate. Rates can reflect locational and temporal prices while utility incentive-based programs allow DERs to provide direct grid services. However, utilities must balance accurately reflecting dynamic grid conditions versus simple and feasible design that encourages customer participation. Currently, most rates and incentive-based programs are simple, but as penetration of DER and advanced controls increase, dynamic designs could become prevalent. Utilities could encourage providing multiple services to optimize distributed battery dispatch and value streams, however, challenges persist when stacking services across distribution and bulk systems. A DER committed to multiple discrete services concurrently necessitates coordination between operators and a clear hierarchy of commitments. One way to address this is to separate commitments by time or capacity. For services that follow cyclic, predictable patterns, or those that are peak driven with predictability, an operator could ensure sufficient state of charge for participation, leaving time where a distributed battery could otherwise provide different services by segmenting participation temporally. To provide continuous or unexpected services, a battery operator may use state of charge management to reserve some percentage of the battery and segment participation by capacity. Macroeconomic trends, load patterns, generation profiles, and grid configurations drive variation in value and the subsequent implications for utility offerings and how a customer might participate. As distributed battery adoption increases, both regulators and utilities will need to ensure no adverse grid impacts and encourage provision of societal value beyond the customer domain.

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DOE OSTI2021

A Non-Invasive Approach for Elucidating the Spatial Distribution of In-Situ Stress in Deep Subsurface Geologic Formations Considered for CO 2 Storage (Final Report)

The primary objectives of this project were to: develop a new, non-invasive method to define the orientation and magnitude of in-situ stresses in deep geologic formations (depths that exceed 1500 meters) considered for carbon dioxide (CO 2 ) sequestration; to demonstrate the method at a real field site; and, to extend current technical capabilities and reduce costs of acquiring information about deep-stress fields. This investigation was segmented into five tasks, including Project Management (Task 1) and four technical tasks (Tasks 2 through 5). The results of the technical tasks are described in this document.

02 PETROLEUM↗

DOE OSTI2022

Influence of Hybridization on the Capacity Value of PV and Battery Resources

Utility-scale systems that combine solar photovoltaic and battery (PV+battery) technologies are growing in popularity on the U.S. bulk power system. The business case for PV+battery systems depends on both their ability to reduce costs and their ability to generate value synergies associated with the provision of energy, capacity, and ancillary services. Capacity value can constitute a significant portion of the value PV+battery hybrids provide to the grid (e.g., through avoided or deferred capacity) and receive through revenues. Throughout this report, we define capacity value as the monetary value of a plant's contribution towards the planning reserve margin, which ultimately depends on market rules and structures. PV+battery hybrids do not always fit into current market structures because of the interactions between the PV and battery components. Unique considerations for the capacity value of PV+battery hybrids include the disparate nature of participation models for PV and battery technologies in existing market rules and the potential influence of a shared interconnection capacity; limitations imposed by a shared inverter; limited ability to charge the battery in advance of capacity events if charging must be sourced from the coupled PV; and challenges or uncertainties associated with co-optimizing the operations of the PV and battery components. Grid operators are currently considering how market structures can be modified to optimally determine the capacity value provided by PV+battery systems, and the rules of how they are integrated into markets are still being written. As with any resource, poorly designed rules could increase the cost of energy and reduce system reliability, while well-designed rules could allow markets to receive the full benefits hybrid systems can offer without overcompensating them for the services they provide. Well-designed rules for PV+battery systems must consider the unique aspects listed above, while leveraging the commonalities with existing resource types. In this report, we summarize the technical capability and market rules that influence the capacity value of PV+battery systems. We further discuss the potential tradeoffs between computational complexity and accuracy for the various ways in which grid operators can credit PV+battery systems for capacity. Finally, we describe markets for capacity, survey current wholesale market rules applying to PV+battery systems, and provide a snapshot of the current regulatory landscape for PV+battery systems.

14 SOLAR ENERGY↗

DOE OSTI2022

Electric Grid Blackstart: Trends, Challenges, and Opportunities

This report studies the expected future state of the grid and recommends actions that can be taken to increase grid resiliency, improve system modeling, perform more extensive studies, enhance training activities, and perform industry outreach for the purpose of the blackstart capabilities of power systems. The report is a revised version of PNNL-29118.

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DOE OSTI2021

Secure Communications Concept and API Concept for Integrating XENDEE Positronix with TESLA PowerPack System at Site 300 (Final Deliverable)

The CleanStart DERMS project focuses on the management of Distributed Energy Resources (DER) for enhanced distribution grid resilience. The demonstration site has changed from Riverside Public Utility to the LLNS Site 300 DERS demonstration site. This project has so far focused only on device level controllers and local area controllers. These controllers potentially lack the ability to perform supervisory control and grid interactive control functions, essential for grid-level optimal DER management. This project seeks to close that gap in development of secure communication concept and appropriate Application Programming Interfaces (API) to enable integration with DERs, device level and local area controllers, such as Distributed Energy Resources Management System (DERMS).

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DOE OSTI2022

Ultra High-Temperature Magnetic Bearing System for s-CO 2 Turbines/Expanders. Phase II Final Report

The goal of this project is to design and construct of a prototype of ultra-high temperature permanent magnet (UHT–PM), which provides the force to pull the spinning shaft towards the target position in the magnetic bearing (MB) clearance circle. This project will develop a PM biased MB system, that is actively cooled to the 550°C maximum operating temperature limit of PMs. The MB test environment will include 700°C, 40krpm and 4,000 psi requirements to advance the supercritical carbon dioxide (sCO 2 ) and other types of Brayton power cycle systems. The proposed novel MBs combine PMs for supplying the bias field and electromagnets for supplying the control field, both in UHT conditions. The choice of material is the UHT Sm-Co PMs (US patent 6,451,132) due to their significantly better thermal stability. The 6-pole homopolar design permits uninterrupted force delivery via a redundant control capability (US patent 7,429,811) even if 3 poles were to fail. The Phase I efforts was to focus on development and demonstration of component technologies and detailed design of full scale components and a demonstrator test rig for use in Phase II. UHT–PMs were produced and used in the MB actuator. The operating environment of the EEC-T550 Sm-Co magnet material could be extended by implementing active cooling. Electromagnetic coils imbedded in the MB provide forces to stabilize the shaft position at the target via sensing and control stages. Shaft position sensors enable to identify the present position of the spinning shaft relative to its desired target position in the MB clearance circle (air gap). Auxiliary bearings will be installed to provide a backup support system in the event that power to the MB fails or there is a fault in a device providing current to the MB coils. For control, reliability and safety reasons the sensors and auxiliary bearings are typically located as close as possible to the MBs, which exposes them to the same environmental conditions. Development of only the actuator for the UHT environment is an inadequate approach to complete integration of the MB system in the turbine/expander. Therefore the UHT sensor and auxiliary bearing were designed and developed along with the actively cooled, UHT-PM actuator development. Although shaft position sensors are commercially available (Kaman) they may cost up to $10k per channel, and a full 5 axis magnetic suspension is best implemented with up to 20 sensors. Once successfully completed, this project will significantly extend the operating environment capability for turbomachinery applications such as nuclear power, concentrated solar thermal, fossil fuel, geothermal, and shipboard propulsion. The further advancement of UHT-PM-MB will also strengthen the US position in PM technology, which is presently heavily dominated by China. The UHT Sm-Co magnet material that will be utilized in the proposed work has been developed exclusively by the project proposer. Many actuators, motors, generators and other MB applications will greatly benefit from the proposed work.

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