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At least 91 records · Page 5

How Improved Forecasting Can Increase the Bulk Power System Value of Price-Responsive Electric Vehicle Managed Charging

Personal light-duty vehicle (LDV) electric vehicle managed charging (EVMC) can reduce power system costs by better aligning electric vehicle (EV) charging with locations and times of low energy cost or infrastructure use. The need to coordinate charging demand across thousands to millions of vehicles while preserving mobility service is a barrier to realizing the value of EVMC. Price-responsive dispatch mechanisms like time-of-use rates (TOU) and hourly real-time prices (RTP) are attractive compared to direct load control (DLC) because they only require one-way communications and local controls. However, increasing participation in price responsive mechanisms can induce costly-to-serve spikes in load and otherwise increase, rather than decrease, production costs. We quantify the ability of improved EVMC forecasting to sustain savings from price responsive mechanisms beyond the limit of 14% of LDVs actively participating observed in previous work. Perfect forecasting of price-responsive EV load makes TOU and RTP value-competitive with a low-error DLC formulation with up to 27% (within-week flexibility) to 45% or more (within-session flexibility) of LDVs participating in EVMC in an envisioned New England power system with 84% clean energy. Additional costs of implementing DLC should be no more than tens of dollars per vehicle-year if DLC is to be value-competitive with accurately forecast price-responsive EVMC for double-digit percentage shares of LDVs participating.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Control of Behind-the-Meter Resources for Enhancing the Resilience of Residential Buildings

There is increased concern about the impacts of frequent power outages, caused primarily by extreme weather conditions. With increasing behind-the-meter resources such as solar photovoltaics (PV), battery energy storage, and controllable loads, these resources - if properly coordinated - can meet critical loads even during an outage. Resilience building controls can coordinate and operate these resources to enhance the resiliency of buildings supporting critical loads for longer duration. In this paper, we present two resilience building controls: rule-based control and model predictive control (MPC). We simulated various scenarios considering different locations, seasons, outage types, and times of outages to evaluate the performance of resilience controls. The results show that MPC-based control can enhance resilience up to 65% compared to rule-based control. Similarly, PV self-consumption and occupant thermal comfort both increase during outages with MPC-based control.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗

Model-Free Building Temperature Control and Power Allocation Under Measurement Time Delays

Taking a step towards a greener planet has created an increased need for a higher integration of renewable energy resources into the electric grid. Nonetheless, the intermittency and uncertainty associated with renewable generation have slowed down this integration. Demand response (DR) has been recently adopted to address this challenge by utilizing demand side flexibility and enabling the participation of many grid-interactive efficient buildings (GEBs). However, existing DR methods require significant modeling and/or training efforts and are computationally expensive. To address the aforementioned issues, we propose a model-free control (MFC)-based strategy that is robust to the time delays in the temperature measurements of the thermostatically controlled loads (TCLs). It assigns to each GEB a local controller to maintain the TCLs’ temperatures within desired comfort levels, while the load aggregator (LA) allocates the assigned reference power provided by the distribution system operator (DSO) to support a specific grid service, such as demand peak reduction, load shifting, balancing supply and demand, and consuming the solar photovoltaic power locally. We investigate the effects of such loss of information on the local control action as well as on meeting the power allocation constraint. We conclude that, for an appropriate choice of design parameters, the proposed MFC controller is satisfactorily robust to measurement time delays.

Telsang, Bhagyashri↗

Synchronization and Rebound Effects in Residential Loads

Increasing fuel prices and capacity investment deferral place an increasing demand for peak reduction from distribution level systems. Residential and commercial devices, such as HVAC systems and water heaters, are increasingly involved in load control programs, and their use may generate synchronization and rebound effects, such as artificial peaks caused by device optimization. While there have been concerns over device synchronization, few studies quantify the extent of this effect with numerical values. In this study, we attempt to investigate whether control efforts result in device synchronization or rebound effects. We focus on three clustering methods – Ward’s clustering, Euclidean K-means, and Density-based spatial clustering of applications with noise – to evaluate the extent of synchronization of a fleet of water heaters and HVAC systems in Atlanta, Georgia. Our findings show that synchronization and rebound effects are present in the neighborhood’s water heaters, but none were found in the HVAC systems. Further, high usage water heaters are more susceptible to synchronization and rebound effects.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Lighting controls: not just for lighting anymore!

For the last few years, networked lighting controls (NLCs) have promised significant energy savings beyond what is achieved through a basic LED retrofit. At the same time, NLCs can substantially increase the cost and complexity of the lighting retrofit. And as lighting system wattage declines because of the increasing efficiency of LEDs, advanced controls have less lighting energy to save and the cost-effectiveness of the NLC investment decreases. But NLCs can be leveraged to achieve significant energy savings and value by enhancing control of other building systems. Integrating NLC with control of heating, ventilation and air conditioning (HVAC), plug load control, space utilization, and grid services all enhance the value of your NLC investment. There are already a few NLC products on the market that are capable of providing these enhanced benefits. Manufacturers and entrepreneurs are working hard to expand the impact of these products. But does system interoperability work? Can it be deployed at scale? Slipstream, NEEA and Pacific Northwest National Laboratory (PNNL) have all been attempting to answer these questions in recent pilot projects and describe the outcomes in this paper.

Hackel, Scott↗

Energy Efficiency Package for Tenant Fit-Out: Laboratory Testing and Validation of Energy Savings and Indoor Environmental Quality

Approximately 40% of the total U.S. office floor space of 1.5 billion sq.m (16 billion sq.ft.) is leased space occupied by tenants. Tenant fit-out presents a key opportunity to incorporate energy efficiency within the real estate business cycle. We designed a package of energy efficiency measures tailored to the scope of a tenant fit-out. This tenant fit-out package (TFP) includes advanced lighting and heating, ventilating and air-conditioning (HVAC) controls as core measures, with ceiling fans, automated shading, and plug load controls as additional optional measures. We conducted laboratory testing of six configurations of the package to evaluate energy savings, indoor environmental quality, and identify installation, commissioning, and operational issues. Combined savings for HVAC, lighting, and plug loads ranged from 33–40%. Lighting savings ranged from 69–83%, and HVAC savings from 20–40%. The laboratory testing also revealed some minor but tractable challenges with installation and commissioning of HVAC controls. Overall, the results demonstrate that significant savings can be realized in existing office buildings by incorporating relatively low-risk, proven measures at the time of a tenant fit-out.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Comprehensive Margin Assessment of the ASME Section III, Division 5, Class A Primary Load Design Rules

This report provides a comprehensive margin assessment of the ASME Section III, Division 5, Subsection HB, Subpart B rules for the design of high temperature reactor components against load controlled stress limits. These rules, often called the Code primary load design rules, provide protection against creep rupture and plastic collapse under steady conditions. The method adopted here is to compare the deterministic ASME design life, according to the primary load design rules, against the expected, statistical service life of the component, considering creep rupture as the relevant failure mode. The report provides the design margin of the ASME rules in terms of the probability of premature failure -- the probability that the component fails in service before reaching the ASME design life. To complete this assessment, the report describes the development of a statistical creep life assessment procedure accounting for variations in the component loading, material creep rate, and the material rupture time. This includes a novel method for correlating creep rupture data using a Gaussian process accounting for heat-to-heat variation in the Larson-Miller time-temperature parameter. The report applies the complete margin assessment process to quantify the design margin inherent in the ASME primary load design rules as a function of temperature for relevant component geometries and materials. The overall conclusion is that the ASME rules are conservative, providing designs with very small probability of premature failure, but some optimization of the Code design rules is possible to provide a more uniform design margin.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Stochastic Pricing Game for Aggregated Demand Response Considering Comfort Level

In recent years, demand response (DR) has been explored as a fundamental strategy for demand-side management due to its advantages in mediating intermittency of renewable energy generation, load shifting, etc. To engage customers in DR programs, several deterministic price-based DR strategies have been developed and implemented. However, the stochastic weather conditions and occupants' consumption behaviors often make the deterministic solution less robust to uncertainties. In this paper, with the consideration of the uncertainties, a stochastic Stackelberg game is proposed to model the price-demand negotiation between a distributed system operator and load aggregators, where the virtual battery constraints are extracted from the building thermostatically controlled loads (TCLs)‘ characteristics to guarantee comfortable TCLs' levels. Following the negotiation, a priority-based control method is used to allocate the optimal aggregated power DR profile at the building level and track the power signal. Several groups of experiments have demonstrated the effectiveness and robustness of the stochastic solutions.

Chen, Yang↗

Data-Driven Linear Parameter-Varying Modeling and Control of Flexible Loads for Grid Services: Preprint

Flexible loads have great potential to improve the power grid's flexibility and stability. To effectively control large ensembles of heterogeneous loads, reliable models thereof are required. The paper presents a data-driven modeling and control approach to manage flexible loads for providing grid services. We leverage a linear parameter-varying autoregressive moving average (LPV-ARMA) model to describe the aggregate load response, where the parameters in the model are used to capture external environment impacts (e.g., weather). A gain-scheduling feedback controller is then developed to adapt to environmental variations. This data-driven approach can be easily applied to different types of loads in various environmental conditions. In addition to the ensemble controller, distributed load controllers are designed to deliver grid services, while maintaining the quality of service of inherent load tasks. We demonstrate the work on the IEEE 37-node distribution system for real-time power regulation services through control of thermostatically controlled loads.

control↗

Al–W gradient density materials—Processing and dynamic ramp compression

Materials with high-density gradients are desired for controlling loading paths in dynamic compression, important for studying material properties in extreme conditions and inertial confinement fusion. The large density difference between Al and W makes them ideal choices for producing gradient density materials, but their extremely different melting temperatures make them challenging to fabricate simultaneously. We report a method for producing Al–W porosity-free materials with a fourfold increase in density (2.7–11 g/cm 3 ) across the composition range, from Al-rich to W-rich, without intermetallic phase formation. This was achieved by understanding the aluminum-dominated densification behavior and examining the influence of pressure and temperature on the densification of Al–W composites. Dynamic compression experiments conducted with the Al–W gradient density material produced shock ramp compressions as expected based on the designed composition, and the performed hydrodynamics simulations showed excellent agreement with experimental results. The results demonstrate that current activated pressure-assisted densification allows for the easy and rapid fabrication of gradient density materials with significant density gradients and tailored compositions, facilitating precise control of the loading paths. These materials have the potential to create customized pressure drives for advancing the fields of material science in extreme environments and dynamic compression.

Alloys↗

Data-Driven Linear Parameter-Varying Modeling and Control of Flexible Loads for Grid Services

Flexible loads have great potential to improve the electric grid's flexibility and stability. To effectively control large ensembles of heterogeneous loads, reliable models thereof are required. This paper presents a data-driven modeling and control approach to manage flexible loads for providing grid services. We leverage a linear parameter-varying autoregressive moving average (LPV-ARMA) model to describe the aggregate load response, where the parameters in the model are used to capture external environmental impacts (e.g., weather). A gain-scheduling feedback controller is then developed to adapt to environmental variations. This data-driven approach can be easily applied to different types of loads in various environmental conditions. In addition to the ensemble controller, distributed load controllers are designed to deliver grid services, while maintaining the quality of service of inherent load tasks. We demonstrate the work on the IEEE 37-node distribution system for real-time power regulation services through control of thermostatically controlled loads.

61 RADIATION PROTECTION AND DOSIMETRY↗

Load Mitigating Feedback Control of WECs

This report outlines the development of load-mitigating feedback control for wave energy converters. A simple, self-tuning multi-objective controller is demonstrated in simulation for a 3-DOF (surge, heave, pitch) point absorber. In previous work, the proposed control architecture has been shown to be effective in experiment for a variety of device archetypes for the single objective of the maximization of electrical power capture: here this architecture is extended to reduce device loading as well. In particular, PTO actuation forces and the minimization of fatigue damage (determined from the sum of wave-exerted and PTO forces) are considered as additional objectives for the self-tuning controller. This controller is demonstrated for two similar, but distinct systems: one described by the identified linear models from physical testing of the WaveBot device, and another based upon a WEC-Sim simulation that expands upon boundary element method data from the WaveBot device. In both cases, because the power surface is consistently fairly flat in the vicinity of control parameters that maximize power capture in contrasting sea-states, it is found to be generally possible to mitigate either fatigue damage or PTO load. However, PTO load is found to conflict with fatigue damage in some sea-states, limiting the efficacy of control objectives that attempt to mitigate both simultaneously. Additionally, coupling between the surge and pitch DOFs also limits the extent to which fatigue damage can be mitigated for both DOFs in some sea-states. Because control objectives can be considered a function of the sea-state (e.g., load mitigation may not be a concern until the sea is sufficiently large) a simple transition strategy is proposed and demonstrated. This transition strategy is found to be effective with some caveats: firstly, it cannot circumvent the aforementioned objective contradictions. Secondly, this objective transition is too slow to act as a system constraint, and objective thresholds must thus be considered quite conservatively. Improvement of the adjustment strategy is demonstrated through the addition of an integral term. Selection of well-performing transition parameters can be a function of sea-state. While a simple selection procedure is proposed, it is non-optimal, and a more robust selection procedure is suggested for future work.

16 TIDAL AND WAVE POWER↗

Integrating Electric Vehicle Charging Infrastructure into Commercial Buildings and Mixed-Use Communities: Design, Modeling, and Control Optimization Opportunities: Preprint

This paper discusses modeling and field studies of controlled EV charging that have been performed with the goal of minimizing requirements for infrastructure upgrades, minimizing building peak demand charges, and maximizing the use of on-site generation. We present a large-scale workplace charging pilot of a demand-controlled scheduled EV charging system with over 250 active daily commuters, successfully demonstrating management of aggregate charging power to avoid new infrastructure investments, mitigate peak demand charges, and provide cost-effective workplace charging to users. In addition to understanding opportunities for demand management, integrating these controllable loads into the energy modeling process for new buildings will also be necessary. This paper then presents an example energy modeling process that evaluates the potential effects of EV charging on building load profiles and infrastructure requirements for a mixed-use community. Finally, we discuss an illustration of how EV charging can be controlled to be synergistic with other building loads and distributed generation.

buildings↗

Factors Influencing Grid-connected Heat Pump Water Heater Performance in the Southeast U.S.

Grid-connected heat pump water heaters (HPWH) can shift electrical load while minimizing impacts to hot water availability for occupants. This capability provides a flexible grid resource to utilities seeking to manage peak loads Such load control also can feasibly improve renewable utilization within the utility electric production mix, for instance using off-peak generation during periods with high renewable energy generation. It also offers lower electric bills to customers through increased energy efficiency of HPWH and cuts greenhouse gas emissions. In particular, the Southeast U.S. due to its high penetration of electric water heating presents a promising opportunity for grid-connected HPWHs. This paper builds upon the results of an extensive HPWH load shifting field study conducted in 51 occupied homes in Florida using EcoPort technology (Butzbaugh et al, 2022). In 2022, only an initial evaluation was available. Here, long term load results are available as well as examination of various control strategies and influences. Analysis is conducted for HPWH energy use and load shifting performance based on home occupancy (i.e., low and high) and water heater location (i.e., conditioned and unconditioned) across different temperature profiles. An unexpected outcome of this analysis was the poor performance of HPWHs located in conditioned spaces, possibly because of inadequate air volume from improper installation. We did find higher demand reductions from 2-hour load ups and slightly improved for critical peak signals in the afternoon control periods. As expected, higher occupancy households showed great load reductions.

Fenaughty, Karen↗

Model predictive control for matrix converter operating in current control mode with load current estimation

A matrix converter system operating in current control mode is provided. The matrix converter includes a switching matrix coupled between a low voltage side and a high voltage side, wherein the matrix converter is coupled at its low voltage side to a generator for receiving an input power including an input current and transforming the input power into an output power at its high voltage side, wherein a load is coupled to the high voltage side. The control system includes a load observer and a model predictive controller (MPC). The load observer is configured to estimate a load current that flows to the load from the high voltage side of the matrix converter as a function of a switching state of the switching matrix, an output voltage output at the high voltage side of the matrix converter, and the input current. The MPC is configured to select the switching state of the switching matrix to meet one or more control objectives defined by minimization of a multi-objective function that tracks the output voltage and the input current using the estimated load current.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Modeling and Control of Cascaded Bridgeless Multilevel Rectifier Under Unbalanced Load Conditions

The goal of this project is to model and control a novel unidirectional cascaded multilevel bridgeless rectifier as an active front end in medium and high voltage applications. This topology has many advantages over a conventional cascaded H-bridge rectifier, such as lower implementation cost, higher reliability, and greater flexibility with similar power quality.The steady-state mathematical model is used to develop a method for the voltage balancing of dc cells. Power factor analysis is discussed to achieve unity power factor using fully controlled hbridge cells. Power loss, efficiency, and cost comparison studies between the traditional cascaded H-Bridge converter and the proposed bridgeless converter demonstrate the advantages. A novel control strategy is proposed to achieve dc voltage balancing, fast and robust grid synchronization and power factor correction under unbalanced load conditions. Simulation and experimental results validate the models and control method.

Cascaded Bridgeless Rectifier, Power factor analys↗

Model-Free Control of Grid-Interactive Efficient Buildings Under Communication Time Delays

Grid-interactive efficient buildings (GEBs) have recently been used to enhance the reliability and stability of the electric grid through demand response (DR) programs. However, most existing DR control strategies require accurate modeling of the various building thermostatically controlled loads (TCLs) and are computationally expensive. To address these challenges, a model-free control (MFC)-based strategy has recently been introduced for coordinating and controlling GEBs. MFC is a data-enabled control strategy that is computationally efficient and does not require the analytical models of the various building equipment. In this paper, we numerically investigate the impact of communication time delays on the performance of MFC in maintaining the TCLs' temperatures within the desired comfort levels while meeting the assigned power allocation constraint.

Telsang, Bhagyashri [University of Tennessee, Knox↗

Supporting cost-effective watershed management strategies for Chesapeake Bay using a modeling and optimization framework

Extensive efforts to adaptively manage nutrient pollution rely on Chesapeake Bay Program’s (Phase 6) Watershed Model, called Chesapeake Assessment Scenario Tool (CAST), which helps decision-makers plan and track implementation of Best Management Practices (BMPs). We describe mathematical characteristics of CAST and develop a constrained nonlinear BMP-subset model, software, and visualization framework. This represents the first publicly available optimization framework for exploring least-cost strategies of pollutant load control for the United States’ largest estuary. The optimization identifies implementation options for a BMP subset modeled with load reduction effectiveness factors, and the web interface facilitates interactive exploration of >30,000 solutions organized by objective, nutrient control level, and for ~200 counties. We assess framework performance and demonstrate modeled cost improvements when comparing optimization-suggested proposals with proposals inspired by jurisdiction plans. Stakeholder feedback highlights the framework’s current utility for investigating cost-effective tradeoffs and its usefulness as a foundation for future analysis of restoration strategies.

54 ENVIRONMENTAL SCIENCES↗