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DOE OSTI2023

Deep-Learning-Based Koopman Modeling for Online Control Synthesis of Nonlinear Power System Transient Dynamics

Power system stability and control have become more challenging due to the increasing uncertainty associated with renewable generation. Here, the performance of conventional control is highly driven by the physics-based offline-developed dynamic models that can deviate from the actual system characteristics under different operating conditions and/or configurations. Data-driven approaches based on online measurements can be a better solution to addressing these issues by capturing real-time operation conditions. This article describes a novel fully data-driven probabilistic framework to derive a linear representation of postcontingency grid dynamics and online prescribe control based on the derived model to enhance transient stability. The complex nonlinear power system dynamics is approximated by a linear model by using multiple neural network modules that infer distributions of the observations and introducing a Koopman layer to sample possible Koopman linear models from the inferred distributions. The trained model features linearity that can be easily incorporated into the existing linear control design paradigm and ease the controller design process. The effectiveness of Koopman-based control designs is validated through comparative case studies, which demonstrate increased prediction accuracy and control performance when applied to a power system with heterogeneous generator dynamics.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2013

Distributed Hierarchical Control Architecture for Transient Dynamics Improvement in Power Systems

In this paper, a novel distributed hierarchical coordinated control architecture is proposed for large scale power systems. The newly considered architecture facilitates frequency restoration and power balancing functions to be decoupled and implemented at different levels. At the local level, decentralized robust generator controllers are designed to quickly restore frequency after large faults and disturbances in the system. The controllers presented herein are shown to improve transient stability performance, as compared to conventional governor and excitation control. At the area level, Automatic Generation Control (AGC) is modified and coordinates with the decentralized robust controllers to reach the interchange schedule in the tie lines. The interaction of local and zonal controllers is validated through detailed simulations.

Marinovici, Laurentiu D.↗
DOE OSTI2017

A Survey of Distributed Optimization and Control Algorithms for Electric Power Systems

Historically, centrally computed algorithms have been the primary means of power system optimization and control. With increasing penetrations of distributed energy resources requiring optimization and control of power systems with many controllable devices, distributed algorithms have been the subject of significant research interest. Here, this paper surveys the literature of distributed algorithms with applications to optimization and control of power systems. In particular, this paper reviews distributed algorithms for offline solution of optimal power flow (OPF) problems as well as online algorithms for real-time solution of OPF, optimal frequency control, optimal voltage control, and optimal wide-area control problems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Multi-Time Scale Coordinated Control and Scheduling of Inverter-Based TCLs With Variable Wind Generation

To address microgrid tie flow errors caused by wind generation variability, here we propose and develop a multi-time scale coordinated control and scheduling strategy for inverter-based thermostatically controlled loads (TCLs). First, in hour-time scale, inverter-based TCLs with adjusting temperature set-point are modeled as virtual generators to compensate tie flow deviations in the day-ahead plan. Next, in minute-time scale, virtual batteries representing operating behaviors of inverter-based TCLs with frequency control are scheduled determined by the control of virtual generators in hour-time scale. The virtual batteries are scheduled to smooth out tie flow errors corresponding to day-ahead plan and hour-time scale schedules. The multi-time scale control methods are coordinated to employ the response potential of inverter-based TCLs and response curve-based methods are proposed to control inverter-based TCLs considering the customer privacy. The multi-time scale stochastic schedules which are based on response curves of inverter-based TCLs are coordinated to accommodate wind generation variability. Simulation results demonstrate that the microgrid tie flow errors are effectively mitigated by the proposed multi-time scale coordinated control and scheduling of inverter-based TCLs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

CONTROLLED END GAS AUTO IGNITION WITH EXHAUST GAS RECIRCULATION ON A STOICHIOMETRIC, SPARK IGNITED, NATURAL GAS ENGINE

The goal of this study is to address fundamental limitations to achieving diesel-like efficiencies in heavy duty on-highway natural gas (NG) engines. Engine knock and misfire are barriers to pathways leading to higher efficiency engines. This study explores enabling technologies for development of high efficiency stoichiometric, spark ignited, natural gas engines. These include design strategies for fast and stable combustion and higher dilution tolerance. Additionally, advanced control methodologies are implemented to maintain stable operation between knock and misfire limits. To implement controlled end- gas autoignition (C-EGAI) strategies a Combustion Intensity Metric (CIM) is used for ignition control with the use of a Woodward large engine control module (LECM). Tests were conducted using a single cylinder, variable compression ratio, cooperative fuel research (CFR) engine with baseline conditions of 900 RPM, engine load of 800 kPa indicated mean effective pressure (IMEP), and stoichiometric air/fuel ratio. Exhaust gas recirculation (EGR) tests were performed using a custom EGR system that simulates a high pressure EGR loop and can provide a range of EGR rates from 0 to 40%. The experimental measurements included the variance of EGR rate, compression ratio, engine speed, IMEP, and CIM. These five variables were optimized through a Modified Box- Benken design Surface Response Method (RSM), with brake efficiency as the merit function. A positive linear correlation between CIM and f-EGAI was identified. Consequently, CIM was used as the feedback control parameter for C-EGAI. As such, implementation of C-EGAI effectively allowed for the utilization of high EGR rates and CRs, controlling combustion between a narrower gap between knock and lean limits. The change from fixed to parametric ignition timing with CIM targeted select values of f-EGAI with an average coefficient of variance (COV) of peak pressure of 5.4. The RSM efficiency optimization concluded with operational conditions of 1080 RPM, 1150 kPa IMEP, 10.55:1 compression ratio, and 17.8% EGR rate with a brake efficiency of 21.3%. At this optimized point of peak performance, a f-EGAI for C-EGAI was observed at 34.1% heat release due to auto ignition, a knock onset crank angle value of 10.3° aTDC and ignition timing of - 24.7° aTDC. This work has demonstrated that combustion at a fixed f-EGAI can be maintained through advanced ignition control of CIM without experiencing heavy knocking events.

Cooperative Fuel Research Engine, Auto Ignition, E↗
DOE OSTI2014

Control algorithms for dynamic attenuators

Purpose: The authors describe algorithms to control dynamic attenuators in CT and compare their performance using simulated scans. Dynamic attenuators are prepatient beam shaping filters that modulate the distribution of x-ray fluence incident on the patient on a view-by-view basis. These attenuators can reduce dose while improving key image quality metrics such as peak or mean variance. In each view, the attenuator presents several degrees of freedom which may be individually adjusted. The total number of degrees of freedom across all views is very large, making many optimization techniques impractical. The authors develop a theory for optimally controlling these attenuators. Special attention is paid to a theoretically perfect attenuator which controls the fluence for each ray individually, but the authors also investigate and compare three other, practical attenuator designs which have been previously proposed: the piecewise-linear attenuator, the translating attenuator, and the double wedge attenuator. Methods: The authors pose and solve the optimization problems of minimizing the mean and peak variance subject to a fixed dose limit. For a perfect attenuator and mean variance minimization, this problem can be solved in simple, closed form. For other attenuator designs, the problem can be decomposed into separate problems for each view to greatly reduce the computational complexity. Peak variance minimization can be approximately solved using iterated, weighted mean variance (WMV) minimization. Also, the authors develop heuristics for the perfect and piecewise-linear attenuators which do not requirea priori knowledge of the patient anatomy. The authors compare these control algorithms on different types of dynamic attenuators using simulated raw data from forward projected DICOM files of a thorax and an abdomen. Results: The translating and double wedge attenuators reduce dose by an average of 30% relative to current techniques (bowtie filter with tube current modulation) without increasing peak variance. The 15-element piecewise-linear dynamic attenuator reduces dose by an average of 42%, and the perfect attenuator reduces dose by an average of 50%. Improvements in peak variance are several times larger than improvements in mean variance. Heuristic control eliminates the need for a prescan. For the piecewise-linear attenuator, the cost of heuristic control is an increase in dose of 9%. The proposed iterated WMV minimization produces results that are within a few percent of the true solution. Conclusions: Dynamic attenuators show potential for significant dose reduction. A wide class of dynamic attenuators can be accurately controlled using the described methods.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2014

SU-E-T-199: How Number of Control Points Influences the Dynamic IMRT Plan Quality and Deliverability

Purpose: To study the influence of number of control points on plan quality and deliverability. Methods: Five previously treated patients of carcinoma of rectum were selected. Planning target volume (PTV) and organs at risk (OARs) i.e. bladder and bowel were contoured. Dynamic IMRT plans (6MV, 7-fields, 45Gy/25 fractions and prescribed at 95% isodose) were created in Eclipse (Varian medical system, Palo Alto, CA) treatment planning system (TPS) for Varian CL2300C/D linear-accelerator. Base plan was calculated with 166 control points, variable mode (Eclipse Default). For generating other plans, all parameters were kept constant, only number of control points (Fixed mode) was varied as follows: 100, 166 and 200. Then, plan quality was analyzed in terms of maximum and mean dose received by the PTV and OARs. For plan deliverability, TPS calculated fluence was verified with I’matriXX (IBA Dosimetry, Germany) array and compared with TPS dose-plane using gamma index criteria of 3% dose difference and 3mm distance to agreement (DTA). Total number of monitor units (MU) required to deliver a plan was also noted. Results: The maximum variation for the PTV maximum with respect to eclipse default control point (166) was 0.28% (0.14Gy). Similarly, PTV mean varied only up to 0.22 %( 0.11Gy). Bladder maximum and bladder mean varied up to 0.51% (0.24Gy) and 0.16% (0.06Gy). The variation for the bowel maximum and bowel mean was also only 0.39% (0.19Gy) and 0.33% (0.04Gy). Total MU was within 0.32 % (4MU). Average gamma pass rate using different control points for five patients are 98.75±0.33%, 99.37±0.09%, 99.29±0.12%, 98.14±0.13% and 99.25±0.14% respectively. Conclusion: Slight variation (<1%) in PTV and OARs maximum and mean doses was observed with varying number of control points. Monitor unit was also not varied much. Reducing number of control points did not showed any comprise in plan deliverability in terms of gamma index pass rate.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Framework for Multi Layer Control in Python (FMLC) v1.0

This package is developed as a backend for multi-layer and multi-time domain controller. One example are controller based on [Model Predictive Control] (MPC) where different modules with different time constants have to be coordinated to allow optimal control. In a simple example, the Weather Forecast must be acquired and processed, the MPC is computed, and finally the control is applied. All these modules typically run on the same time step (Time step: 5 minutes), but are different instances within the framework. The framework allows parallelization using the `multiprocessing` module. However, another real-time controller (Time step: 1 second) must be applied to react on instant system disturbances beyond the MPC time step. Last, a supervisory MPC controller (Time step: 1 hour) might be added to ensure global optimality.

Gehbauer, Christoph↗
DOE OSTI2026

Supervisory Control and Data Acquisition for Electrochemical Separation Experimentation

The Python-based program is a laboratory automation tool designed to control and monitor electrochemical systems. The tool was developed for capacitive deionization (CDI) experiments, but it can be used for any system that requires controlled voltage or current segments and multi-parameter monitoring. The program integrates hardware components to run user-defined experimental parameters, providing operational control of a programmable power supply, peristaltic pump, and data acquisition devices. Currently, the program is structured with a workflow that includes an initialization (or pre-run) phase, a main loop, and a post-experiment stabilization (or post-run) phase. The initialization phase prepares and stabilizes the cell, ensuring that the electrodes and solution reach a baseline state before the experiment begins. The main loop consists of multiple voltage segments that repeat, controlling the experiment while recording key parameters such as time, voltage, current, pH, and conductivity. Finally, the post-experiment stabilization phase allows the system to stabilize after the experiment, returning the cell and solution to equilibrium conditions before ending the sequence. The program is designed with four variations, each tailored to different experimental needs. All variations include both the initialization and post-experiment stabilization stages, which run for a set amount of time, voltage, current, and flow rate before and after the main experiment block. The main loop runs for a set number of cycles, as defined by the user input, and each cycle is composed of 2 or 4 segments. The 4 program variations are described as follows: Program 1: The main program includes 2 segments. Each segment is defined to have a set duration, flow rate, voltage, and current. This program measures conductivity, flow rate, voltage, and current. Program 2: The main program expands Program 1 to include 4 segments. Each segment has a specified duration, flow rate, voltage, and current. Like Program 1, it measures conductivity, flow rate, voltage, and current. Program 3: The main program consists of 2 segments, each defined by time, flow rate, voltage, and current. In addition to conductivity, flow rate, voltage, and current, Program 3 collects pH and temperature data through a 4-channel data acquisition device. Program 4: This program independently controls two channels of a multi-channel power supply simultaneously. While conductivity can only be measured for one cell at a time, the dual-channel control makes it possible to operate two cells simultaneously under different voltage/current conditions. The main program includes 2 segments.For each program, all measurements are automatically logged and integrated into a single Excel output file. Data are displayed in numerical format and plotted, both in real time, to track system performance. A key feature of the program is its ability to synchronize all outputs so that every measurement shares a single timestamp, ensuring accurate alignment of voltage, current, pH, conductivity, and pH data.By combining hardware control, real-time monitoring, and unified data collection, this program significantly reduces manual workload and minimizes errors, making it a reliable platform for researchers, engineers, and laboratory technicians conducting CDI experiments, among other electrochemical tests.

Valentino, Lauren [Argonne National Laboratory (AN↗
DOE OSTI2022

Silicon nitride stress-optic microresonator modulator for optical control applications

Modulation-based control and locking of lasers, filters and other photonic components is a ubiquitous function across many applications that span the visible to infrared (IR), including atomic, molecular and optical (AMO), quantum sciences, fiber communications, metrology, and microwave photonics. Today, modulators used to realize these control functions consist of high-power bulk-optic components for tuning, sideband modulation, and phase and frequency shifting, while providing low optical insertion loss and operation from DC to 10s of MHz. In order to reduce the size, weight and cost of these applications and improve their scalability and reliability, modulation control functions need to be implemented in a low loss, wafer-scale CMOS-compatible photonic integration platform. The silicon nitride integration platform has been successful at realizing extremely low waveguide losses across the visible to infrared and components including high performance lasers, filters, resonators, stabilization cavities, and optical frequency combs. Yet, progress towards implementing low loss, low power modulators in the silicon nitride platform, while maintaining wafer-scale process compatibility has been limited. Here we report a significant advance in integration of a piezo-electric (PZT, lead zirconate titanate) actuated micro-ring modulation in a fully-planar, wafer-scale silicon nitride platform, that maintains low optical loss (0.03 dB/cm in a 625 µm resonator) at 1550 nm, with an order of magnitude increase in bandwidth (DC - 15 MHz 3-dB and DC - 25 MHz 6-dB) and order of magnitude lower power consumption of 20 nW improvement over prior PZT modulators. The modulator provides a >14 dB extinction ratio (ER) and 7.1 million quality-factor (Q) over the entire 4 GHz tuning range, a tuning efficiency of 162 MHz/V, and delivers the linearity required for control applications with 65.1 dB·Hz 2/3 and 73.8 dB·Hz 2/3 third-order intermodulation distortion (IMD3) spurious free dynamic range (SFDR) at 1 MHz and 10 MHz respectively. We demonstrate two control applications, laser stabilization in a Pound-Drever Hall (PDH) lock loop, reducing laser frequency noise by 40 dB, and as a laser carrier tracking filter. This PZT modulator design can be extended to the visible in the ultra-low loss silicon nitride platform with minor waveguide design changes. This integration of PZT modulation in the ultra-low loss silicon nitride waveguide platform enables modulator control functions in a wide range of visible to IR applications such as atomic and molecular transition locking for cooling, trapping and probing, controllable optical frequency combs, low-power external cavity tunable lasers, quantum computers, sensors and communications, atomic clocks, and tunable ultra-low linewidth lasers and ultra-low phase noise microwave synthesizers.

Wang, Jiawei (ORCID:0000000257965220)↗
DOE OSTI2020

Joint Optimization of Well Completions and Controls for CO 2 Enhanced Oil Recovery and Storage

CO 2 storage through CO 2 enhanced oil recovery (EOR) is considered as one of the technologies to help promote larger scale deployment of CO 2 storage because of associated economic benefits through oil recovery, 45Q tax credits and the utilization of existing infrastructure. The objective of this study is to demonstrate how optimal reservoir management and operation strategies (including well completions and controls) can be used to optimize both CO 2 storage and oil recovery. The optimization problem was focused on jointly estimating the well completions (i.e., fraction of injection/production well perforations in each reservoir layer) and CO 2 injection/oil production controls that maximize the net present value (NPV) in a CO 2 EOR and storage operation. We utilized the newly developed StoSAG algorithm, one of the most efficient optimization algorithms in the reservoir management community, to solve the optimization problem. The performance of joint optimization approach was compared with the performance of well control only optimization approach. In addition, the performance of co-optimization of CO 2 storage and oil recovery approach was compared with the performances of maximization of only CO 2 storage and maximization of only oil recovery approaches. The optimization results showed that a joint optimization of well completions and well controls can achieve an 8.84% higher final NPV than the one obtained from the optimization of only well controls. It was observed that the NPV incremental for joint optimization is mainly due to the fact that the optimal well completions and controls approach results in efficient CO 2 storage and oil production from different reservoir layers depending on the differences in individual layer properties. Comparison of co-optimization (i.e., maximization of NPV) and maximization of only CO 2 storage or only oil recovery showed that the co-optimization and maximization of only oil recovery result in significantly higher final NPV than that obtained through maximization of only CO 2 storage approach while maximization of only CO 2 storage can achieve significantly higher CO 2 storage in the reservoir compared to the other two scenarios. The similar results for co-optimization and maximization of oil production are obtained because of the difference in oil revenue compared to CO 2 storage tax credit. To the best of our knowledge, this is the first study in oil/gas industry and CO 2 storage community to perform joint optimization of well completions and well controls in the fields. We expect that the proposed optimization framework will be a useful and efficient tool for field engineers to optimally manage CO 2 EOR projects to maximize revenue through oil recovery as well as CO 2 storage by taking advantage of the new 45Q tax law.

Artificial intelligence↗
DOE OSTI2015

Development of a First-of-a-Kind Deterministic Decision-Making Tool for Supervisory Control System

Decision-making is the process of identifying and choosing alternatives where each alternative offers a different approach or path to move from a given state or condition to a desired state or condition. The generation of consistent decisions requires that a structured, coherent process be defined, immediately leading to a decision-making framework. The overall objective of the generalized framework is for it to be adopted into an autonomous decision-making framework and tailored to specific requirements for various applications. In this context, automation is the use of computing resources to make decisions and implement a structured decision-making process with limited or no human intervention. The overriding goal of automation is to replace or supplement human decision makers with reconfigurable decision- making modules that can perform a given set of tasks reliably. Risk-informed decision making requires a probabilistic assessment of the likelihood of success given the status of the plant/systems and component health, and a deterministic assessment between plant operating parameters and reactor protection parameters to prevent unnecessary trips and challenges to plant safety systems. The implementation of the probabilistic portion of the decision-making engine of the proposed supervisory control system was detailed in previous milestone reports. Once the control options are identified and ranked based on the likelihood of success, the supervisory control system transmits the options to the deterministic portion of the platform. The deterministic multi-attribute decision-making framework uses variable sensor data (e.g., outlet temperature) and calculates where it is within the challenge state, its trajectory, and margin within the controllable domain using utility functions to evaluate current and projected plant state space for different control decisions. Metrics to be evaluated include stability, cost, time to complete (action), power level, etc. The integration of deterministic calculations using multi-physics analyses (i.e., neutronics, thermal, and thermal-hydraulics) and probabilistic safety calculations allows for the examination and quantification of margin recovery strategies. This also provides validation of the control options identified from the probabilistic assessment. Thus, the thermal-hydraulics analyses are used to validate the control options identified from the probabilistic assessment. Future work includes evaluating other possible metrics and computational efficiencies.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Load Control System Reliability

This report summarizes the results of the Load Control System Reliability project (DOE Award DE-FC26-06NT42750). The original grant was awarded to Montana Tech April 2006. Follow-on DOE awards and expansions to the project scope occurred August 2007, January 2009, April 2011, and April 2013. In addition to the DOE monies, the project also consisted of matching funds from the states of Montana and Wyoming. Project participants included Montana Tech; the University of Wyoming; Montana State University; NorthWestern Energy, Inc., and MSE. Research focused on two areas: real-time power-system load control methodologies; and, power-system measurement-based stability-assessment operation and control tools. The majority of effort was focused on area 2. Results from the research includes: development of fundamental power-system dynamic concepts, control schemes, and signal-processing algorithms; many papers (including two prize papers) in leading journals and conferences and leadership of IEEE activities; one patent; participation in major actual-system testing in the western North American power system; prototype power-system operation and control software installed and tested at three major North American control centers; and, the incubation of a new commercial-grade operation and control software tool. Work under this grant certainly supported the DOE-OE goals in the area of “Real Time Grid Reliability Management.”

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Microgrid Controller and Advanced Distribution Management System Survey Report

A microgrid controller, which serves as the heart of a microgrid, is responsible for optimally managing the distributed energy resources, energy storage systems, and responsive demand and for ensuring the microgrid is being operated in an efficient, reliable, and resilient way. As the market for microgrids has blossomed in recently years, many vendors have released their own microgrid controllers to meet the various needs of different microgrid clients. However, due to the absence of a recognized standard for such controllers, vendor-supported microgrid controllers have a range of functionalities that are significantly different from each other in many respects. As a result the current state of the industry has been difficult to assess. To remedy this situation the authors conducted a survey of the functions of microgrid controllers developed by vendors and national laboratories. This report presents a clear indication of the state of the microgrid-controller industry based on analysis of the survey results. The results demonstrate that US Department of Energy funded research in microgrid controllers is unique and not competing with that of industry.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

A comparison of WEC control strategies

The operation of Wave Energy Converter (WEC) devices can pose many challenging problems to the Water Power Community. A key research question is how to significantly improve the performance of these WEC devices through improving the control system design. This report summarizes an effort to analyze and improve the performance of WEC through the design and implementation of control systems. Controllers were selected to span the WEC control design space with the aim of building a more comprehensive understanding of different controller capabilities and requirements. To design and evaluate these control strategies, a model scale test-bed WEC was designed for both numerical and experimental testing (see Section 1.1). Seven control strategies have been developed and applied on a numerical model of the selected WEC. This model is capable of performing at a range of levels, spanning from a fully-linear realization to varying levels of nonlinearity. The details of this model and its ongoing development are described in Section 1.2.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2018

Embedded Sensors and Controls to Improve Component Performance and Reliability - Final Report

Oak Ridge National Laboratory has researched embedded instrumentation and controls (I&C) for extreme environments under the Department of Energy, Office of Nuclear Energy's Nuclear Energy Enabling Technology program. Advanced sensors and controls have the potential to dramatically increase the performance and efficiency of nuclear reactor components, however, the extreme environments of exiting and advanced reactor designs limit the options for sensors, actuators, and control designs. To address two of the extreme environment challenges to embedded I&C, the focus of this research is to fill technology gaps needed for electromagnetic systems that can operate at temperatures greater than 700 C in corrosive environments. A magnetically suspended, canned-rotor pump was chosen for the embedded I&C development platform because it is a system with a practical need in industry and because the sensors, actuators, and embedded I&C technologies needed to successfully build this platform will be widely applicable to any high-temperature components that utilize electromagnetic interactions. This design also eliminates the need for pump seals and mechanical bearings which are the main sources of pump failures and maintenance costs. During the project a conceptual design for the high-temperature magnetically suspended pump was developed and analyzed for manufacturability and reliability. Specifications for the materials, control system, sensors, mechanical performance, high-temperature wiring, and electromagnetic properties were developed for the conceptual design. The canned rotor design of the high-temperature pump presents unique fluid force characteristics arising from the thin fluid channel between the rotor and stator. A model of the fluid forces was developed and the impact of these forces on the stability and performance of magnetic bearing controllers was studied. Then a room temperature bench-scale magnetic testbed was designed and fabricated for testing the performance of sensors and electromagnetic actuators, modern control design techniques, closed-loop system identification, state estimation, and model uncertainty. Finally, a loop-scale testbed with submerged magnetic bearings was designed and fabricated. This testbed will be used to analyze the stability and performance of control system designs in response to the nonlinear and cross-coupling fluid effects between the shaft axes of motion, rotordynamics, gyroscopic effects, and impeller disturbances.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Dual-Zone Solar Control Indoor Shade: Demonstration at the Ronald V. Dellums Federal Building and U.S. Courthouse, 1301 Clay Street, Oakland, California and the Lawrence Berkeley National Laboratory Advanced Windows Testbed, Berkeley, California

Standard window shades are used to control sunlight, glare, window heat gains, and daylight. The challenge with conventional shades is that once the shades are lowered to reduce discomfort, daylight is reduced, which, in turn, increases the need for electric lighting. View is also obstructed, reducing the occupants’ connection to the outdoors. The strategy of subdividing the window wall and admitting daylight from above and controlling sunlight and view through the lower aperture can yield significant energy and peak demand savings over conventional shading systems, and improve the daylight quality of the indoor environment. This study evaluated a dual zone solar control (DZSC) shade with an upper, automated, horizontal, venetian blind with concave-up, matte white slats and a lower, manually operated, roller shade made of a transparent, reflective film. The automatic controls were designed to adjust the upper slat angle to maximize daylight to the room interior. The lower shade, when lowered, provided an unobstructed view to the outdoors. For the qualitative analysis, the DZSC shades were installed on windows in the southeast half of one floor in the Ronald V. Dellums Federal Building and U.S. Courthouse or hereafter referred to as the Oakland Federal Building (OFB) in Oakland, California. The position of the DZSC shades were observed and recorded periodically. Surveys were issued to occupants in the private offices and open plan workstations affected by the shades. For the quantitative analysis, the DZSC shades were installed in the south-facing windows of thermally isolated, fully instrumented, test chambers in the Advanced Windows Testbed at the Lawrence Berkeley National Laboratory (LBNL) in Berkeley, California. Measurements of window heat loads, daylight illuminance and environmental conditions related to visual and thermal comfort were collected over a six-month, solstice-to-solstice period. The performance of the DZSC shade was compared to fabric roller shades and venetian blinds since these are the two most common types of shades used in both commercial and Federal buildings. Several DZSC design permutations were evaluated: 1) manual or automated control of the upper louver system (“man” or “auto”) and 2) tinted or silvered reflective film for the lower shade (“Gray-Gray (GG)” or “Gray-Silver (GS)”1). The automated, reflective shade (auto-GS) reduced dimmable fluorescent lighting energy use by 51% and window cooling load by 13-15% compared to a conventional fabric roller shade with dual-pane, spectrally selective, low-e windows during the summer period (winter period was not measured). Qualitative analysis revealed that the auto-GS shade was preferred by 80% of the survey respondents compared to the existing vertical fabric blinds with single-pane, tinted windows in the occupied building. Survey results indicated that visual discomfort was reduced and thermal discomfort was also reduced during warm or hot weather. Occupants expressed greater satisfaction with the unobstructed view. Installation and commissioning of the DZSC shades was fairly straightforward with some minor problems due to inadequate installation instructions and improper wiring. A few occupants expressed dissatisfaction with the automatic controls for the upper louvers due to visual discomfort, erroneous control, and motor noise.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

A Domain-Specific Language for High-Consequence Control Software

While most software development for control systems is directed at what the system is supposed to do (i.e., function), high-consequence controls must account for what the system is not supposed to do (i.e., safety, security and reliability requirements). A Domain Specific Language (DSL) for high-consequence digital controls is proposed. As with similar tools for the design of controls, the DSL will have plug-in modules for common controller functions. However, the DSL will also augment these modules with attendant "templates" that aid in the proof of safety, security and reliability requirements, not available in current tools. The object is to create a development methodology that makes construction of high-assurance control systems as easy as controls that are designed for function alone.

97 MATHEMATICS AND COMPUTING↗