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DOE OSTI2026

Testing and Expertise for Marine Energy (TEAMER) Program Support (CRADA Final Report)

Virginia Tech (VT) had previously developed a 50 kW AC to DC power converter that is specifically designed to improve the performance and efficiency of wave energy converters (WECs). Through this CRADA, NLR will test the VT power converter via a coupled dynamometer and power electronics test platform. The NLR test platform will be comprised of (1) a rotary dynamometer that will drive a VT provided gearbox and generator, (2) one or more DC regenerative power supplies that provide input power to and take power from the VT supplied power electronics, and (3) a data acquisition system for measurement. NLR will work with VT to develop a test plan, set up the test platform and integrate the test article, perform the testing, and assist in the data analysis.

16 TIDAL AND WAVE POWER↗

DOE OSTI2016

Emerging Connections: Quantum & Classical Optics Incubator Program Book

The Emerging Connections: Quantum & Classical Optics Incubator was a scientific meeting held in Washington, DC on 6-8 November 2016. This Incubator provided unique and focused experiences and valuable opportunities to discuss advances, challenges and opportunities regarding this important area of research. Quantum optics and classical optics have coexisted for nearly a century as two distinct, but consistent descriptions of light in their respective domains. Recently, a number of detailed examinations of the structure of classical light beams have revealed that effects widely thought to be solely quantum in origin also have a place in classical optics. These new quantum-classical connections are informing classical optics in meaningful ways specifically by expanding understanding of optical coherence. Simultaneously, relationships discovered with classical light beams now also serve as a vehicle to illuminate concepts that no longer solely belong to the quantum realm. Interference, polarization, coherence, complementarity and entanglement are a partial list of elementary notions that now appear to belong to both quantum and classical optics. The goal of this meeting was to bring emerging quantum-classical links into wider view and to indicate directions in which forthcoming and future work would promote discussion and lead to a more unified understanding of optics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

Dual Active Bridge based DC Transformer LabVIEW FPGA Control Code [SWR-16-25]

In the area of power electronics control, Field Programmable Gate Arrays (FPGAs) have the capability to outperform their Digital Signal Processor (DSP) counterparts due to the FPGA’s ability to implement true parallel processing and therefore facilitate higher switching frequencies, higher control bandwidth, and/or enhanced functionality. National Instruments (NI) has developed two platforms, Compact RIO (cRIO) and Single Board RIO (sbRIO), which combine a real-time processor with an FPGA. The FPGA can be programmed with a subset of the well-known LabVIEW graphical programming language. The candidate software implements complete control algorithms in LabVIEW FPGA for a DC Transformer (DCX) based on a dual active bridge (DAB). A DCX is an isolated bi-directional DC-DC converter designed to operate at unity conversion ratio, M, defined by where Vin is the primary-side DC bus voltage, Vout is the secondary-side DC bus voltage, and n is the turns ratio of the embedded high frequency transformer (HFX). The DCX based on a DAB incorporates two H-bridges, a resonant inductor, and an HFX to provide this functionality. The candidate software employs phase-shift modulation of the two H-bridges and a feedback loop to regulate the conversion ratio at unity. The software also includes alarm-handling capabilities as well as debugging and tuning tools. The software fits on the Xilinx Virtex V LX110 FPGA embedded in the NI cRIO-9118 FPGA chassis, and with a 40 MHz base clock, supports a modulation update rate of 40 MHz, and user-settable switching frequencies and synchronized control loop update rates of tens of kHz.

Source record↗

DOE OSTI2016

Development of the electron cooling simulation program for JLEIC

In the JLab Electron Ion Collider (JLEIC) project the traditional electron cooling technique is used to reduce the ion beam emittance at the booster ring, and to compensate the intrabeam scattering effect and maintain the ion beam emittance during collision at the collider ring. A new electron cooling process simulation program has been developed to fulfill the requirements of the JLEIC electron cooler design. The new program allows the users to calculate the electron cooling rate and simulate the cooling process with either DC or bunched electron beam to cool either coasting or bunched ion beam. It has been benchmarked with BETACOOL in aspect of accuracy and efficiency. In typical electron cooling process of JLEIC, the two programs agree very well and we have seen a significant improvement of computational speed using the new one. Being adaptive to the modern multicore hardware makes it possible to further enhance the efficiency for computationally intensive problems. The new program is being actively used in the electron cooling study and cooler design for JLEIC. We will present our models and some simulation results in this paper.

Zhang, He↗

DOE OSTI2017

U.S. Renewables Portfolio Standards: 2017 Annual Status Report

Berkeley Lab’s annual status report on U.S. renewables portfolio standards (RPS) provides an overview of key trends associated with U.S. state RPS policies. The report, published in slide-deck form, describes recent legislative revisions, key policy design features, compliance with interim targets, past and projected impacts on renewables development, and compliance costs. The 2017 edition of the report presents historical data through year-end 2016 and projections through 2030. Key trends from this edition of the report include the following: -Evolution of state RPS programs: Significant RPS-related policy revisions since the start of 2016 include increased RPS targets in DC, MD, MI, NY, RI, and OR; requirements for new wind and solar projects and other major reforms to the RPS procurement process in IL; and a new offshore wind carve-out and solar procurement program in MA. -Historical impacts on renewables development: Roughly half of all growth in U.S. renewable electricity (RE) generation and capacity since 2000 is associated with state RPS requirements. Nationally, the role of RPS policies has diminished over time, representing 44% of all U.S. RE capacity additions in 2016. However, within particular regions, RPS policies continue to play a central role in supporting RE growth, constituting 70-90% of 2016 RE capacity additions in the West, Mid-Atlantic, and Northeast. -Future RPS demand and incremental needs: Meeting RPS demand growth will require roughly a 50% increase in U.S. RE generation by 2030, equating to 55 GW of new RE capacity. To meet future RPS demand, total U.S. RE generation will need to reach 13% of electricity sales by 2030 (compared to 10% today), though other drivers will also continue to influence RE growth. -RPS target achievement to-date: States have generally met their interim RPS targets in recent years, with only a few exceptions reflecting unique state-specific policy designs. -REC pricing trends: Prices for renewable energy certificates (RECs) used to meet general RPS obligations fell in most markets in 2016, as surplus RPS supplies emerged in many regions. Price trends for solar RECs were more varied, with a particularly pronounced drop in MD. -RPS compliance costs and cost caps: RPS compliance costs totaled $3.0 billion in 2015 (the most-recent year for which relatively complete data are available), which equates to 1.6% of average retail electricity bills in RPS states. Though total U.S. RPS compliance costs rose from 2014, future cost growth in most RPS states will be capped by cost containment mechanisms.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

New Simulations for Ion-Production and Back-Bombardment in GaAs Photo-guns

GaAs-based DC high voltage photo-guns used at accelerators with extensive user programs must exhibit long photocathode operating lifetime. Achieving this goal represents a significant challenge for proposed high average current facilities that must operate at tens of milliamperes or more. Specifically, the operating lifetime is dominated by ion back-bombardment of the photocathode from ionized residual gas. While numerous experiments have been performed to characterize the operating lifetime under various conditions, detailed simulations of the ion back-bombardment mechanism that explains these experiments are lacking. Recently, a new user routine was implemented using the code General Particle Tracer (GPT) to simulate electron impact ionization of residual beam line gas and simultaneously track the incident electron, the ejected electron, and the newly formed ion. This new routine was benchmarked against analytical calculations and then applied to experiments performed at the CEBAF injector at the Thomas Jefferson National Accelerator Facility to study the effectiveness of limiting ions from entering the cathode-anode gap using a positively biased anode. These simulations were performed using detailed 3D field maps produced with CST Microwave Studio describing the photo-gun electrostatics. Discussion of the experiment and the application of this new GPT routine to model the experiments will be presented at the workshop.

Yoskowitz, Joshua↗

DOE OSTI2020

The Heuristic Dynamic Programming Approach in Boost Converters

In this study, a heuristic dynamic programming controller is proposed to control a boost converter. Conventional controllers such as proportional-integral-derivative (PID) or proportional-integral (PI) are designed based on the linearized small-signal model near the operating point. Therefore, the performance of the controller during the start-up, the load change, or the input voltage variation is not optimal since the system model changes by varying the operating point. The heuristic dynamic programming controller optimally controls the boost converter by following the approximate dynamic programming. The advantage of the HDP is that the neural network-based characteristic of the proposed controller enables boost converters to easily cope with large disturbances. An HDP with a well-trained critic and action networks can perform as an optimal controller for the boost converter. To compare the effectiveness of the traditional PI-based and the HDP boost converter, the simulation results are provided.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2019

On the Path to Energy Independence and a Clean Power Future – LED Lighting Retrofit and Solar Power Generation for the CTUIR Science and Engineering Laboratory and Public Transit Center (Rev.1)

This project supports the goals of the Energy Policy for the Confederated Tribes of the Umatilla Indian Reservation (CTUIR) through the implementation of an energy efficiency measure (LED lighting retrofit) and construction of a fixed rack (stationary) ground-mounted solar photovoltaic (PV) array energy generation system. The project objective was to eliminate the net demand for grid-based utility energy at two tribal facilities: the CTUIR Field Station and the Public Transit Center (consisting of bus barn and maintenance shop buildings). A total of 332 lighting fixtures were retrofitted with high efficiency LEDs at the three buildings within the project scope. The solar PV array constructed adjacent to the Field Station (46330 Timine Way, Pendleton, OR 97801) has a nameplate capacity of 97.98 kW DC . The project was managed by staff from the CTUIR Energy & Environmental Sciences Program within the Department of Natural Resources and the final budget was $\$ $288,206. Data was collected during a 12 month monitoring period following construction of the aptly named Ántukš–Tín̓qapapt Solar PV Array and assessed to determine project results. During this time, the solar PV system generated 125,580 kWh of energy according to SolrenView solar PV system monitoring service. In contrast, the total realized utility energy and cost savings due to the project were estimated by comparing 24 months of consecutive utility billing data. Results of this comparison indicate that grid-based utility energy demand was reduced by 121,280 kWh, or roughly 80% of the total electricity consumed by both facilities. The cost savings associated with this energy demand reduction were $\$ $11,104 and a payback period of 5.7 years was estimated for recovering the CTUIR’s investment. However, it should be noted that these figures are not representative of the savings that could be obtained under normal, error-free (i.e. faultless) conditions. Several undesirable events occurred during the 12 month monitoring and evaluation period, the effects of which were quantified using available data so that results under a “Faultless Scenario” could be estimated. Annual energy and cost savings estimated for the Faultless Scenario were approximately 166,289 kWh and $\$ $15,225, respectively. These figures should prove to be more representative of the long-term average annual results achieved in response to the project and suggest a payback period closer to 4.5 years for the CTUIR.

14 SOLAR ENERGY↗

DOE OSTI2023

A Sequential Quadratic Programming Algorithm for Nonsmooth Problems with Upper- ${\boldsymbol{\mathcal{C}^2}}$ Objective

An optimization algorithm for nonsmooth nonconvex constrained optimization problems with upper- ${\boldsymbol{\mathcal{C}^2}}$ objective functions is proposed and analyzed. Upper- ${\boldsymbol{\mathcal{C}^2}}$ is a weakly concave property that exists in difference of convex (DC) functions and arises naturally in many applications, particularly certain classes of solutions to parametric optimization problems e.g., recourse of stochastic programming and projection onto closed sets. The algorithm can be viewed as an extension of sequential quadratic programming (SQP) to nonsmooth problems with upper- ${\boldsymbol{\mathcal{C}^2}}$ objectives or a simplified bundle method. It is globally convergent with bounded algorithm parameters that are updated with a trust-region criterion. The algorithm handles general smooth constraints through linearization and uses a line search to ensure progress. The potential inconsistencies from the linearization of the constraints are addressed through a penalty method. In conclusion, the capabilities of the algorithm are demonstrated by solving both simple upper- ${\boldsymbol{\mathcal{C}^2}}$ problems and a real-world optimal power flow problem used in current power grid industry practices.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Peak Power Reduction for HVAC Operations in Multi-unit Commercial Buildings

The load profiles of most commercial consumers are characterized by brief periods of very high power consumption followed by intervals of relatively lower demand. In order to flatten commercial load profiles, several power utilities in addition to billing energy consumption, levy a demand charge (DC) on the monthly peak demand. In this work, we consider the problem of joint optimization of energy costs (EC) and DC incurred by a multi-unit building which follows a demand response (DR) program. Despite the non-linear structure of the problem, we show how the optimal solutions can be obtained efficiently using linear programming. We evaluate the performance of the proposed power control scheme for various climate zones in the US. We show that depending on the ambient conditions and the prescribed tariff structure, our strategy can result in savings of up to nearly 19% compared to the baseline.

Raza Naqvi, Syed A.↗

DOE OSTI2022

Feasible region-based heuristics for optimal transmission switching

In this paper, we develop a optimal transmission switching (OTS) heuristic based on DC optimal power flow (OPF) and assess the efficacy of the approach when implemented within AC OPF. Traditional formulations of the OTS problem can result in hundreds or thousands of binary variables for large networks, making the OTS problem challenging to solve on fast timescales even for relatively small networks. Here, we identify which constraints and therefore which variables are constraining the DC OPF feasible region, and rank them based on their impact on the cost function. We develop a heuristic algorithm which iteratively removes these constraints and solves a series of standard DC OPF problems. The heuristic is tested on a variety of PGlib networks and the results show that the algorithm can provide substantial cost decreases without having to solve any mixed integer programs. Additionally, we provide insights about the OTS problem, including identifying scenarios outside congestion where OTS can prove useful. Lastly, the performance of the DC-based heuristic is shown when the line switching decisions are implemented within AC OPF.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Strain-concentration for fast, compact photonic modulation and non-volatile memory

A critical figure of merit (FoM) for electro-optic (EO) modulators is the transmission change per voltage, d T / d V . Conventional approaches in wave-guided modulators maximize d T / d V via a high EO coefficient or longer light-material interaction lengths but are ultimately limited by material losses and nonlinearities. Optical and RF resonances improve d T / d V at the cost of spectral non-uniformity, especially for high- Q optical cavity resonances. Here, we introduce an EO modulator based on piezo-strain-concentration of a photonic crystal cavity to address both trade-offs: (i) it eliminates the trade-off between d T / d V and waveguide loss—i.e., enhancement of the resonance tuning efficiency d v c / d V for the fixed EO coefficient, waveguide length, and cavity Q —and (ii) at high DC strains it exhibits a non-volatile (NV) cavity tuning Δ v c ,NV for passive memory and programming of multiple devices into resonance despite fabrication variations. The device is fabricated on a scalable silicon nitride-on-aluminum nitride platform. We measure d v c / d V =177±1MHz/V, corresponding to Δ v c =40±0.32GHz for a voltage spanning ±120V with an energy consumption of δ U /Δ v c =0.17nW/GHz. The modulation bandwidth is flat up to ω BW,3dB /2 π =3.2±0.07MHz for broadband DC-AC and 142±17MHz for resonant operation near a 2.8 GHz mechanical resonance. Optical extinction up to 25 dB is obtained via Fano-type interference. Strain-induced beam-buckling modes are programmable under a “read-write” protocol with a continuous, repeatable tuning range of 5±0.25GHz, allowing for storage and retrieval, which we quantify with mutual information of 2.4 bits and a maximum non-volatile excursion of 8 GHz. Using a full piezo-optical finite-element-model (FEM) we identify key design principles for optimizing strain-based modulators and chart a path towards achieving performance comparable to lithium niobate-based modulators and the study of high strain physics on-chip.

Wen, Y. Henry (ORCID:0009000685423628)↗

DOE OSTI2020

Comparison of Optimal Energy Management Strategies Using Dynamic Programming, Model Predictive Control, and Constant Velocity Prediction

Due to the recent advancements in autonomous vehicle technology, future vehicle velocity predictions are becoming more robust which allows fuel economy (FE) improvements in hybrid electric vehicles through optimal energy management strategies (EMS). A realworld highway drive cycle (DC) and a controls-oriented 2017 Toyota Prius Prime model are used to study potential FE improvements. We proposed three important metrics for comparison: (1) perfect full drive cycle prediction using dynamic programming, (2) 10-second prediction horizon model predictive control (MPC), and (3) 10-second constant velocity prediction. These different velocity predictions are put into an optimal EMS derivation algorithm to derive optimal engine torque and engine speed. The results show that the constant velocity prediction algorithm outperformed the baseline control strategy but underperformed the MPC strategy with an average 1.58% and 2.45% of FE improvement with highway and city-highway DC. Also, using a 10-second prediction window MPC strategy provided FE improvement results close to the full drive cycle prediction case. MPC has the potential to achieve 60%-65% and 70% - 80% of global FE improvement over highway and city-highway DC respectively.

Patel, Amol Arvind↗

DOE OSTI2020

Comparison of Optimal Energy Management Strategies Using Dynamic Programming, Model Predictive Control, and Constant Velocity Prediction

Due to the recent advancements in autonomous vehicle technology, future vehicle velocity predictions are becoming more robust which allows fuel economy (FE) improvements in hybrid electric vehicles through optimal energy management strategies (EMS). A real- world highway drive cycle (DC) and a controls-oriented 2017 Toyota Prius Prime model are used to study potential FE improvements. We proposed three important metrics for comparison: (1) perfect full drive cycle prediction using dynamic programming, (2) 10-second prediction horizon model predictive control (MPC), and (3) 10-second constant velocity prediction. These different velocity predictions are put into an optimal EMS derivation algorithm to derive optimal engine torque and engine speed. The results show that the constant velocity prediction algorithm outperformed the baseline control strategy but underperformed the MPC strategy with an average 1.58% and 2.45% of FE improvement with highway and city-highway DC. Also, using a 10-second prediction window MPC strategy provided FE improvement results close to the full drive cycle prediction case. MPC has the potential to achieve 60%-65% and 70% - 80% of global FE improvement over highway and city-highway DC respectively.

Patel, Amol Arvind↗

DOE OSTI2024

Case Study: Increasing Solar Participation Among LIHEAP and WAP Clients in DC

The DC Department of Energy and Environment (DOEE) administers Solar for All, Low Income Home Energy Assistance Program (LIHEAP), and Weatherization Assistance Program (WAP). This case study discusses the partnerships between these programs to increase low-income participation in Solar for All.

community solar↗

DOE OSTI2017

Variable-Speed Screw Chiller, Sidney Yates Building, Washington, DC

This report captures the findings from an evaluation ORNL performed on a new chiller technology as part of GSA's Proving Ground Program. Note: Appendices B&C were removed from this report while the author looks for a way to insert them without consuming over 200MB of file size.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2019

BTMS Testing Section

Cell testing is an important part of understanding the performance and life capabilities of stateof- the art energy storage technologies, particularly with respect to the distinct technical and functional requirements posed by the BTMS program. The baseline requirements for BTMS are loosely defined as a 1MWh BTMS system supporting six 350kW DC fast charging stations with no load profile defined. In order to test energy storage components and systems against these requirements, test procedures must be created that begin to address fundamental questions concerning the balance between cell performance and lifetime to minimize BTMS station cost and maximize station life. System usage scenarios are concurrently being developed with testing of baseline cells intended to illustrate their capabilities relative to a broad set of initial system assumptions. The results from these early performance tests and aging procedures will produce both slow and accelerated cycle-life aging information through a mix of empirical observations and modeling.

25 ENERGY STORAGE↗

DOE OSTI2016

Direct Current as an Integrating Platform for ZNE Buildings with EVs and Storage: DC Direct Systems – A Bridge to a Low Carbon Future?

Cost effective zero net energy (ZNE) schemes exist for many types of residential and commercial buildings. Yet, today’s alternating current (AC) based ZNE designs may be as much as 10% to 20% less efficient, more costly, and more complicated than a design based on direct current (DC) technologies. An increasing number of research organizations and manufacturers are just starting the process of developing products and conducting research and development (R&D) efforts. These early R&D efforts indicate that the use of DC technologies may deliver many energy and non-energy benefits relative to AC-based typologies. DC ZNE schemes may provide for an ideal integrating platform for natively DC-based onsite generation, storage, electric vehicle (EV) charging and end-use loads. Emerging empirical data suggest that DC end-use appliances are more efficient, simpler, more durable, and lower cost. DC technologies appear to provide ratepayers a lower cost pathway to achieve resilient ZNE buildings, and simultaneously yield a plethora of benefits. This paper draws from the current research effort entitled "Direct Current as an Integrating and Enabling Platform," co-led by the Lawrence Berkeley National Laboratory (LBNL), the California Institute for Energy and the Environment (CIEE), the Electric Power Research Institute (EPRI) and funded under the California Energy Commission’s Energy Program Investment Charge (CEC EPIC). The first phase of this EPIC research is focused on assembling and summarizing known global performance information on DC and DC-AC hybrid end-use appliances and power systems. This paper summarizes the information and insights gained from this research effort.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗