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Developing scheduling benchmark tests for the Space Network
A set of benchmark tests were developed to analyze and measure Space Network scheduling characteristics and to assess the potential benefits of a proposed flexible scheduling concept. This paper discusses the role of the benchmark tests in evaluating alternative flexible scheduling approaches and defines a set of performance measurements. The paper describes the rationale for the benchmark tests as well as the benchmark components, which include models of the Tracking and Data Relay Satellite (TDRS), mission spacecraft, their orbital data, and flexible requests for communication services. Parameters which vary in the tests address the degree of request flexibility, the request resource load, and the number of events to schedule. Test results are evaluated based on time to process and schedule quality. Preliminary results and lessons learned are addressed.
Active rotor coning for a 25 MW downwind offshore wind turbine
A two-bladed downwind turbine system was upscaled from 13.2 MW to 25 MW by redesigning aerodynamics, structures, and controls. In particular, three 25-MW rotors were developed, and the final version is a fully redesigned model of the original rotor. Despite their radically large sizes, it was found that these 25-MW turbine rotors satisfy this limited set of structural design drivers at the rated condition and that larger blade lengths are possible with conewise load-alignment. In addition, flapwise morphing (varying the cone angle with a wind-speed schedule) was investigated to minimize mean and fluctuating blade root bending loads using steady inflow proxies for the maximum and lifetime damage equivalent load moments. Compared to the fixed coned rotor case, morphing can provide an Annual Energy Production (AEP) increase of 6%, and the maximum blade root flapwise bending moment increases 21% (still under the constraint, i.e., 10% of the ultimate moments) as a trade-off. The resulting series of 25-MW rotors can be a valuable baseline for further development and assessment of ultra-large-scale wind turbines.
Co-optimization of repairs and dynamic network reconfiguration for improved distribution system resilience
In this work, a post-disaster distribution system repair and restoration (DSRR) strategy is proposed to improve distribution system resilience. The DSRR strategy is formulated as a two-stage optimization. The first stage is a comprehensive co-optimization of repair crew scheduling, dynamic network reconfiguration, and distributed energy resource (DER) dispatch based on the forecast load profile. The goal is to minimize the accumulative operating cost caused by the load reduction payment as well as DER operating cost. In particular, since the number of available repair crews is usually smaller than the number of faulted lines after a disaster event, the DSRR strategy determines the optimal scheduling for repairing faulted lines. The second stage is a re-dispatch of the DER power output and load shedding based on the real-time load demand of each bus. The proposed algorithm is validated by case studies of the IEEE 33-bus and 123-bus test systems. We consider those scenarios in which faults occur in multiple heavy-loaded feeders. The simulation results demonstrate that the DSRR strategy effectively coordinate the repair scheduling, network reconfiguration and load shedding to minimize the operating cost.
Analysis of different operating strategies of thermal energy storage with radiant cooling system
Thermal energy storage systems in building cooling applications have been explored extensively as a peak load-shifting technology. Thermal energy storage performance has been recognized and studied from an energy cost-savings point of view because of peak-valley price differences, but not many studies have been conducted from an energy savings viewpoint. This study experimentally investigates the performance of the energy storage-retrofitted to a ceiling-type radiant cooling system. To study the performance, a water-based storage system was designed and developed for an academic office building equipped with a radiant cooling system. The water in the storage tank was cooled to a certain storage temperature in the nighttime, and the same water was used during the daytime for meeting the cooling load. Different combinations of charging and discharging schedules were analyzed. The key objective of the study was to achieve energy savings and energy-cost savings simultaneously. This objective was accomplished by identifying the major factors contributing to the energy consumption of the storage-retrofitted cooling system and devising novel operating strategies, leading to an enhanced energy savings potential. Two operating strategies comprising 24 operating scenarios were compared and the storage was used to dispatch the load for 3 hours of the day as a full storage unit. Results showed that in hot and dry climate conditions, using the storage with the radiant cooling system offered energy savings of 3% to 14%. The energy-cost analysis was also performed using a time-of-day electricity tariff plan. The energy-cost savings varied from 17.5% to 22.4% for these operating scenarios.
Techno-Economic Assessment of Residential Heat Pump Integrated with Thermal Energy Storage
Phase change material (PCM)-based thermal energy storage (TES) can provide energy and cost savings and peak demand reduction benefits for grid-interactive residential buildings. Researchers established that these benefits vary greatly depending on the PCM phase change temperature (PCT), total TES storage capacity, system configuration and location and climate of the building. In this study, preliminary techno-economic performance is reported for a novel heat pump (HP)-integrated TES system using an idealized approach. A simplified HP-TES was modeled for 1 year of space heating and cooling loads for a residential building in three different climates in the United States. The vapor compression system of the HP was modified to integrate with TES, and all heat transfer to and from the TES was mediated by the HP. A single PCM was used for heating and cooling, and the PCT and TES capacity were varied to observe their effects on the building’s energy consumption, peak load shifting and cost savings. The maximum reduction in electric consumption, utility cost and peak electric demand were achieved at a PCT of 30 °C for New York City and 20 °C for Houston and Birmingham. Peak energy consumption in Houston, New York City, and Birmingham was reduced by 47%, 53%, and 70%, respectively, by shifting peak load using a time-of-use utility schedule. TES with 170 MJ storage capacity allowed for maximum demand shift from on-peak to off-peak hours, with diminishing returns once the TES capacity equaled the daily building thermal loads experienced during the most extreme ambient conditions.
COVID-19 pandemic ramifications on residential Smart homes energy use load profiles
The COVID-19 pandemic has significantly affected people’s behavioral patterns and schedules because of stay-at-home orders and a reduction of social interactions. Therefore, the shape of electrical loads associated with residential buildings has also changed. In this paper, we quantify the changes and perform a detailed analysis on how the load shapes have changed, and we make potential recommendations for utilities to handle peak load and demand response. Our analysis incorporates data from before and after the onset of the COVID-19 pandemic, from an Alabama Power Smart Neighborhood with energy-efficient/smart devices, using around 40 advanced metering infrastructure data points. This paper highlights the energy usage pattern changes between weekdays and weekends pre– and post–COVID-19 pandemic times. The weekend usage patterns look similar pre– and post–COVID-19 pandemic, but weekday patterns show significant changes. We also compare energy use of the Smart Neighborhood with a traditional neighborhood to better understand how energy-efficient/smart devices can provide energy savings, especially because of increased work-from-home situations. HVAC and water heating remain the largest consumers of electricity in residential homes, and our findings indicate an even further increase in energy use by these systems.
Linear Quadratic Tracking Design for a Generic Transport Aircraft with Structural Load Constraints
When designing control laws for systems with constraints added to the tracking performance, control allocation methods can be utilized. Control allocations methods are used when there are more command inputs than controlled variables. Constraints that require allocators are such task as; surface saturation limits, structural load limits, drag reduction constraints or actuator failures. Most transport aircraft have many actuated surfaces compared to the three controlled variables (such as angle of attack, roll rate & angle of side slip). To distribute the control effort among the redundant set of actuators a fixed mixer approach can be utilized or online control allocation techniques. The benefit of an online allocator is that constraints can be considered in the design whereas the fixed mixer cannot. However, an online control allocator mixer has a disadvantage of not guaranteeing a surface schedule, which can then produce ill defined loads on the aircraft. The load uncertainty and complexity has prevented some controller designs from using advanced allocation techniques. This paper considers actuator redundancy management for a class of over actuated systems with real-time structural load limits using linear quadratic tracking applied to the generic transport model. A roll maneuver example of an artificial load limit constraint is shown and compared to the same no load limitation maneuver.
Network reconfiguration and distributed energy resource scheduling for improved distribution system resilience
Electric utility companies work to restore as much load as possible after power outages caused by extreme weather events. In this paper, an outage management strategy is proposed to enhance distribution system resilience through network reconfiguration and distributed energy resources (DERs) scheduling. After a line fault, the proposed algorithm can identify radial network topology based on the rank of the incidence matrix. The reconfiguration is implemented by switching tie lines and sectionalizing lines. With the new network topology, an optimal DER scheduling problem is solved to minimize the accumulative cost for dispatchable DER operation and load reduction. Finally, the optimal topology that minimizes the accumulative cost is selected from all radial topologies. The computational workload is relatively low because only linear programming needs to be solved. Using the case studies of the IEEE 69-bus and IEEE 123-bus systems, we consider the worst-case scenarios in which faults occur in the upstream feeder. The simulation results demonstrate that the proposed strategy allows for a relatively high percentage of the load to remain in service after line faults. Furthermore, compared with microgrid-formation approaches, the proposed strategy has advantages when applied to the distribution systems with several normally-open tie lines and low DER penetration.
Downwind coning concept rotor for a 25 MW offshore wind turbine
The size of offshore wind turbines over the next decade is expected to continually increase due to reduced balance of station costs per MW and also the higher wind energy at increased altitudes that can lead to higher capacity factors. However, there are challenges that may limit the degree of upscaling which is possible. In this paper, a two-bladed downwind turbine system is upscaled from 13.2 MW to 25 MW, by redesigning aerodynamics, structures, and controls. In particular, three 25 MW rotors have been developed: V1 is the upscaled model, V2 is a partial redesigned model, and V3 is a fully redesigned model. Despite their radically large sizes, it is found that these 25 MW turbine rotors satisfy this limited set of design drivers at the rated condition and that larger blade lengths are possible with cone-wise load-alignment. In addition, flapwise morphing (varying the cone angle with a wind-speed schedule) is investigated in terms of minimizing mean and fluctuating root bending loads using steady inflow proxies for the maximum and damage equivalent load moments. The resulting series of 25 MW rotors, which are the largest ever designed, can be a useful baseline for additional development and assessment.
US 2023/0182605 A1 Network constraint energy management system for electric vehicle depot charging and scheduling
Network constraint energy management system for electric vehicle (EV) depot charging and scheduling. In an embodiment, a power schedule is received from an economic dispatch application for a charging depot comprising EV charging station(s) and distributed energy resource(s). The power schedule may be simulated on a distribution network model of the charging depot, according to load flow analysis, to determine whether any grid-code violations occur. In response to the detection of violation(s), a constraint may be generated for each violating node, and the economic dispatch application may be re-executed with the constraint(s) to produce a new power schedule, until no violations are detected. When not all load demand can be satisfied by the power schedule, a charging schedule may be adjusted to ensure that critical energy requirements are satisfied. The final power and charging schedules may be used to schedule and control power generation and charging in the charging depot.
Autonomous power expert system
The Autonomous Power Expert (APEX) system was designed to monitor and diagnose fault conditions that occur within the Space Station Freedom Electrical Power System (SSF/EPS) Testbed. APEX is designed to interface with SSF/EPS testbed power management controllers to provide enhanced autonomous operation and control capability. The APEX architecture consists of three components: (1) a rule-based expert system, (2) a testbed data acquisition interface, and (3) a power scheduler interface. Fault detection, fault isolation, justification of probable causes, recommended actions, and incipient fault analysis are the main functions of the expert system component. The data acquisition component requests and receives pertinent parametric values from the EPS testbed and asserts the values into a knowledge base. Power load profile information is obtained from a remote scheduler through the power scheduler interface component. The current APEX design and development work is discussed. Operation and use of APEX by way of the user interface screens is also covered.
Bayesian Structural Time Series for Behind-the-Meter Photovoltaic Disaggregation
Distributed photovoltaic (PV) generation often occurs ``behind the meter": a grid operator can only observe the net load, which is the sum of the gross load and distributed PV generation. This lack of observability poses a challenge to system operation at both bulk level and distribution level. The lack of real-time or near-future disaggregated estimates of gross load and PV generation will lead to over scheduling of energy production and regulation reserves, reliability constraints violations, wear and tear of controller devices, and potentially cascading failures of a system. In this paper we propose the use of a Bayesian Structural Time Series (BSTS) model with local solar irradiance measurements to disaggregate the summed PV generation and gross load signals at a downstream measurement site. BSTSs are a highly expressive model class that blends classic time series models with the powerful Bayesian state space estimation framework. Disaggregation is done probabilistically, which automatically quantifies the uncertainties of the estimated PV generation and gross load consumption. Depending on the data availability in real-time, it can be used to disaggragate PV and gross load at customer site, or can be used at the feeder level. In this paper, we focus on solving the problem at feeder level. We compare the performance of a BSTS model as well as a handful of state-of-the-art methods on a Pecan Street AMI dataset, using the National Solar Radiation Database (NSRDB) to estimate local irradiance.
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.
MRT 7365: Power flow physics and key physics phenomena
The Z accelerator at Sandia National Laboratories conducts z-pinch experiments at 26 MA in support of DOE missions in stockpile stewardship, dynamic materials, fusion, and other basic sciences. Increasing the current delivered to the z-pinch would extend our reach in each of these disciplines. To achieve increases in current and accelerator efficiency, a fraction of Z’s shots are set aside for research into transmission-line power flow. These shots, with supporting simulations and theory, are incorporated into this Advanced Diagnostics milestone report. The efficiency of Z is reduced as some portion of the total current is shunted across the transmission-line gaps prior to the load. This is referred to as “current loss”. Electrode plasmas have long been implicated in this process, so the bulk of dedicated power-flow experiments are designed to measure the plasma environment. The experimental analyses are enhanced by simulations conducted using realistic hardware and Z voltage pulses. In the same way that diagnostics are continually being improved for sensitivity and resolution, the modeling capability is continually being improved to provide faster and more realistic simulations. The specifics of the experimental hardware, diagnostics, simulations, and algorithm developments are provided in this report. The combined analysis of simulation and data confirms that electrode plasmas have the most detrimental impact on current delivery. Experiments over the last three years have tested the theoretical current-loss mechanisms of enhanced ion current, plasma gap closure, and Hall-related current. These mechanisms are not mutually exclusive and may be coincident in the final feed as well as in upstream transmission lines. The final-feed geometries tested here, however, observe lower-density plasmas without dominant ion currents which is consistent with a Hall-related current. The picture of plasma formation and transport formed from experiment and simulation is informing hardware designs being fielded on Z now and being proposed for the Next-Generation Pulsed Power (NGPP) facility. In this picture, the strong magnetic fields that heat the electrodes above particle emission thresholds also confine the charged particles near the surface. Some portion of the plasmas thus formed is transported into the transmission-line gap under the force of the electric field, with aid from plasma instabilities. The gap plasmas are then transported towards the load by a cross-field drift, where they accumulate and contribute to a likely Hall-related cross-gap current. The achievements in experimental execution, model validation, and physical analysis presented in this report set the stage for continued progress in power flow and load diagnostics on Z. The planned shot schedule for Z and Mykonos will provide data for extrapolation to higher current to ensure the predicted performance and efficiency of a NGPP facility.
Space station automation of common module power management and distribution
The purpose is to automate a breadboard level Power Management and Distribution (PMAD) system which possesses many functional characteristics of a specified Space Station power system. The automation system was built upon 20 kHz ac source with redundancy of the power buses. There are two power distribution control units which furnish power to six load centers which in turn enable load circuits based upon a system generated schedule. The progress in building this specified autonomous system is described. Automation of Space Station Module PMAD was accomplished by segmenting the complete task in the following four independent tasks: (1) develop a detailed approach for PMAD automation; (2) define the software and hardware elements of automation; (3) develop the automation system for the PMAD breadboard; and (4) select an appropriate host processing environment.
Development of a Countermeasure to Enhance Postflight Locomotor Adaptability
Astronauts returning from space flight experience locomotor dysfunction following their return to Earth. Our laboratory is currently developing a gait adaptability training program that is designed to facilitate recovery of locomotor function following a return to a gravitational environment. The training program exploits the ability of the sensorimotor system to generalize from exposure to multiple adaptive challenges during training so that the gait control system essentially learns to learn and therefore can reorganize more rapidly when faced with a novel adaptive challenge. We have previously confirmed that subjects participating in adaptive generalization training programs using a variety of visuomotor distortions can enhance their ability to adapt to a novel sensorimotor environment. Importantly, this increased adaptability was retained even one month after completion of the training period. Adaptive generalization has been observed in a variety of other tasks requiring sensorimotor transformations including manual control tasks and reaching (Bock et al., 2001, Seidler, 2003) and obstacle avoidance during walking (Lam and Dietz, 2004). Taken together, the evidence suggests that a training regimen exposing crewmembers to variation in locomotor conditions, with repeated transitions among states, may enhance their ability to learn how to reassemble appropriate locomotor patterns upon return from microgravity. We believe exposure to this type of training will extend crewmembers locomotor behavioral repertoires, facilitating the return of functional mobility after long duration space flight. Our proposed training protocol will compel subjects to develop new behavioral solutions under varying sensorimotor demands. Over time subjects will learn to create appropriate locomotor solution more rapidly enabling acquisition of mobility sooner after long-duration space flight. Our laboratory is currently developing adaptive generalization training procedures and the associated flight hardware to implement such a training program during regular inflight treadmill operations. A visual display system will provide variation in visual flow patterns during treadmill exercise. Crewmembers will be exposed to a virtual scene that can translate and rotate in six-degrees-of freedom during their regular treadmill exercise period. Associated ground based studies are focused on determining optimal combinations of sensory manipulations (visual flow, body loading and support surface variation) and training schedules that will produce the greatest potential for adaptive flexibility in gait function during exposure to challenging and novel environments. An overview of our progress in these areas will be discussed during the presentation.
A Decision Support Framework for Grid-Aware Electric Bus Charge Scheduling
While there are many advantages to electric public transit vehicles, they also pose new challenges for fleet operators. One key challenge is defining a charge scheduling policy that minimizes operating costs and power grid disruptions while maintaining schedule adherence. An uncoordinated policy could result in some buses running out of charge before completing their trip, while a grid agnostic policy might incur higher energy costs or cause an adverse impact on the grid’s distribution system. We present a grid aware decision-theoretic framework for electric bus charge scheduling that accounts for energy price, grid load, and bus status. The framework connects environmental models for traffic (SUMO) and the electric grid (GridLAB-D) to a planner, which evaluates bus charging decisions with regard to their long-term effect on grid reliability and cost. The framework has been evaluated on a simulation of Richland, WA’s bus and grid network, and compared to greedy methods.