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At least 55 records · Page 3

Soft Actor Critic Based Volt-VAR Co-optimization in Active Distribution Grids

Modern distribution networks are undergoing several technical challenges, such as voltage fluctuations, because of high penetration of distributed energy resources (DERs). This paper proposes a deep reinforcement learning (DRL)-based Volt VAR co-optimization technique for reducing voltage fluctuations as well as power loss under high penetration of DERs. In addition, the proposed approach minimizes the operational cost of the grid. A stochastic policy optimization based soft actor critic (SAC) agent is proposed to configure the optimal set-points of the reactive power outputs of the inverters. The performance of the proposed model is verified on the modified IEEE 34- and 123-bus systems and compared with a base case scenario with no reactive supply by inverters, and a local droop control approach. The results demonstrate that the proposed framework outperforms the conventional droop control method in improving the voltage profile, minimizing the network power loss, and reducing grid operational cost.

—Distribution grids, deep reinforcement learning, ↗

Femtosecond mega-electron-volt electron microdiffraction

To understand and control the basic functions of physical, chemical and biological processes from micron to nano-meter scale, an instrument capable of visualizing transient structural changes of inhomogeneous materials with atomic spatial and temporal resolutions, is required. One such technique is femtosecond electron microdiffraction, in which a short electron pulse with femtosecond-scale duration is focused into a micron-scale spot and used to obtain diffraction images to resolve ultrafast structural dynamics over a localized crystalline domain. In this letter, we report the experimental demonstration of time-resolved mega-electron-volt electron microdiffraction which achieves a 5 μm root-mean-square (rms) beam size on the sample and a 110 fs rms temporal resolution. Using pulses of 10k electrons at 4.2 MeV energy with a normalized emittance 3 nm-rad, we obtained high quality diffraction from a single 10 μm paraffin ( C 44 H 90 ) crystal. The phonon softening mode in optical-pumped polycrystalline Bi was also time-resolved, demonstrating the temporal resolution limits of the instrument. In conclusion, this new characterization capability will open many research opportunities in material and biological sciences.

36 MATERIALS SCIENCE↗

Sub-volt conversion of activated biochar and water for H 2 production near equilibrium via biochar-assisted water electrolysis

Sluggish water oxidation reactions limit water electrolysis for H 2 production, which can be alleviated by the use of carbon-based ma- terials like agricultural wastes as reducing agents. Biochar from such biomass can reduce equilibrium cell potentials at standard condi- tions from 1.23 V to 0.21 V by avoiding direct water splitting at the anode. However, some challenges hinder biochar oxidation, including poor biochar binding, electrode caking, and surface passivation. We find that enhanced C/O ratio, crystallinity, and negative zeta potential improve biochar oxidation kinetics at mod- erate temperatures. Smaller particle sizes and better mixing pre- vent electrode caking, enhancing biochar stability. Here, we report sub-volt biochar-coupled H 2 production, often referred to as a bio- char-assisted water electrolysis (BAWE), yielding 250 mA/g cat H 2 current at 100% Faradaic efficiency. Over 1 mA current was observed at a near-equilibrium cell potential of 0.2 V cell potential. Using a single-junction solar cell-powered BAWE, 15 mA H 2 is generated at 1 Sun, resulting in 4.8% solar-to-hydrogen efficiency, equivalent to 35% when the energy of H 2 relative to H 2 O (without biochar) is assumed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Observation of acceleration and deceleration in gigaelectron-volt-per-metre gradient dielectric wakefield accelerators

There is urgent need to develop new acceleration techniques capable of exceeding gigaelectron-volt-per-metre (GeV m –1 ) gradients in order to enable future generations of both light sources and high-energy physics experiments. To address this need, short wavelength accelerators based on wakefields, where an intense relativistic electron beam radiates the demanded fields directly into the accelerator structure or medium, are currently under intense investigation. One such wakefield based accelerator, the dielectric wakefield accelerator, uses a dielectric lined-waveguide to support a wakefield used for acceleration. Here we show gradients of 1.347±0.020 GeV m –1 using a dielectric wakefield accelerator of 15 cm length, with sub-millimetre transverse aperture, by measuring changes of the kinetic state of relativistic electron beams. We follow this measurement by demonstrating accelerating gradients of 320±17 MeV m –1 . As a result, both measurements improve on previous measurements by and order of magnitude and show promise for dielectric wakefield accelerators as sources of high-energy electrons.

43 PARTICLE ACCELERATORS↗

A novel nondestructive diagnostic method for mega-electron-volt ultrafast electron diffraction

Abstract A real-time, nondestructive, Bragg-diffracted electron beam energy, energy-spread and spatial-pointing jitter monitor is experimentally verified by encoding the electron beam energy and spatial-pointing jitter information into the mega-electron-volt ultrafast electron diffraction pattern. The shot-to-shot fluctuation of the diffraction pattern is then decomposed to two basic modes, i.e., the distance between the Bragg peaks as well as its variation (radial mode) and the overall lateral shift of the whole pattern (drift mode). Since these two modes are completely decoupled, the Bragg-diffraction method can simultaneously measure the shot-to-shot energy fluctuation from the radial mode with 2·10 −4 precision and spatial-pointing jitter from the drift mode having wide measurement span covering energy jitter range from 10 −4 to 10 −1 . The key advantage of this method is that it allows us to extract the electron beam energy spread concurrently with the ongoing experiment and enables online optimization of the electron beam especially for future high charge single-shot ultrafast electron diffraction (UED) and ultrafast electron microscopy (UEM) experiments. Furthermore, real-time energy measurement enables the filtering process to remove off-energy shots, improving the resolution of time-resolved UED. As a result, this method can be applied to the entire UED user community, beyond the traditional electron beam diagnostics of accelerators used by accelerator physicists.

43 PARTICLE ACCELERATORS↗

Femtosecond gas-phase mega-electron-volt ultrafast electron diffraction

The development of ultrafast gas electron diffraction with nonrelativistic electrons has enabled the determination of molecular structures with atomic spatial resolution. It has, however, been challenging to break the picosecond temporal resolution barrier and achieve the goal that has long been envisioned—making space- and-time resolved molecular movies of chemical reaction in the gas-phase. Recently, an ultrafast electron diffraction (UED) apparatus using mega-electron-volt (MeV) electrons was developed at the SLAC National Accelerator Laboratory for imaging ultrafast structural dynamics of molecules in the gas phase. The SLAC gas-phase MeV UED has achieved 65 fs root mean square temporal resolution, 0.63 Å spatial resolution, and 0.22 Å−1 reciprocal-space resolution. Such high spatial-temporal resolution has enabled the capturing of real-time molecular movies of fundamental photochemical mechanisms, such as chemical bond breaking, ring opening, and a nuclear wave packet crossing a conical intersection. In this paper, the design that enables the high spatial-temporal resolution of the SLAC gas phase MeV UED is presented. The compact design of the differential pump section of the SLAC gas phase MeV UED realized five orders-of-magnitude vacuum isolation between the electron source and gas sample chamber. The spatial resolution, temporal resolution, and long-term stability of the apparatus are systematically characterized.

74 ATOMIC AND MOLECULAR PHYSICS↗

Liquid-phase mega-electron-volt ultrafast electron diffraction

The conversion of light into usable chemical and mechanical energy is pivotal to several biological and chemical processes, many of which occur in solution. To understand the structure–function relationships mediating these processes, a technique with high spatial and temporal resolutions is required. Here, we report on the design and commissioning of a liquid-phase mega-electron-volt (MeV) ultrafast electron diffraction instrument for the study of structural dynamics in solution. Limitations posed by the shallow penetration depth of electrons and the resulting information loss due to multiple scattering and the technical challenge of delivering liquids to vacuum were overcome through the use of MeV electrons and a gas-accelerated thin liquid sheet jet. To demonstrate the capabilities of this instrument, the structure of water and its network were resolved up to the 3rd hydration shell with a spatial resolution of 0.6 Å; preliminary time-resolved experiments demonstrated a temporal resolution of 200 fs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Photodissociation of aqueous I3− observed with liquid-phase ultrafast mega-electron-volt electron diffraction

Developing femtosecond resolution methods for directly observing structural dynamics is critical to understanding complex photochemical reaction mechanisms in solution. We have used two recent developments, ultrafast mega-electron-volt electron sources and vacuum compatible sub-micron thick liquid sheet jets, to enable liquid-phase ultrafast electron diffraction (LUED). We have demonstrated the viability of LUED by investigating the photodissociation of tri-iodide initiated with a 400 nm laser pulse. This has enabled the average speed of the bond expansion to be measured during the first 750 fs of dissociation and the geminate recombination to be directly captured on the picosecond time scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A terahertz pump mega-electron-volt ultrafast electron diffraction probe apparatus at the SLAC Accelerator Structure Test Area facility

Here, we describe a new experimental setup capable of measuring structural dynamics following intense terahertz excitation. This system, developed at the SLAC Accelerator Structure Test Area facility, uses a high-energy ultrafast laser to produce intense terahertz pulses and femtosecond electron bunches that are accelerated to mega-electron-volt kinetic energies. The focused terahertz pulses have electric fields in excess of 600 kV/cm, and the resulting structural dynamics can be followed by electron diffraction. We also present some examples demonstrating its implementation where interactions between the THz pulses and the electron bunch are used to characterize the spatial and temporal characteristics of the THz field.

42 ENGINEERING↗

Real-time Simulation of Coordinated Sub-Transmission Volt-Var Control Tool under High Distributed PV Penetration

With the rapid penetration of intermittent solar photovoltaic (PV) and other distributed energy resources (DER) into the grid, and subsequent changes in power flow patterns in both distribution and sub-transmission, voltage regulation is becoming a major challenge. It is prudent to leverage PV and DER to provide ancillary services to the grid, such as voltage regulation. Recently, a quasi-static, coordinated real-time sub transmission volt-var control algorithm (CReST-VCT) was developed for voltage regulation under high PV penetration by dispatching the reactive power settings of the shunt devices and PV inverters. The algorithm was validated offline, on a quasistatic study. Such quasi-static dispatching algorithms cannot guarantee its performance for highly nonlinear dynamical power systems. In this paper the performance of the algorithm is validated with a real time nonlinear dynamic simulation of a modified IEEE 118 bus system in Opal-RT. The real time simulation is used to emulate the actual system operation, providing a more realistic testing environment for CReST-VCT. The dispatch and control signals are communicated between the power system (Opal solver) and the control center (GAMS solver) in real-time with a MODBUS bridge. The results demonstrate i) system is stable with the new dispatch points ii) significant improvement in system-wide voltage profiles compared to an uncontrolled scenario. Another significant contribution of the work is developing a framework for dispatchable, long duration dynamic simulations that can be leveraged for market/dispatch studies.

CReST-VCT, Opal-RT, Volt/Var Control, renewable in↗

Quantum Reinforcement Learning for Volt-VAR Control in Power Distribution Systems

Volt-VAR control (VVC) is crucial in active distribution networks for optimizing voltage profiles and minimizing network losses. While traditional deep reinforcement learning (DRL) algorithms exhibit promise for VVC, they often require extensive computational resources to handle such a high-dimensional problem. As a potential solution, quantum reinforcement learning (QRL) algorithms integrate the computational capabilities of quantum computing into the DRL framework. However, existing QRL algorithms struggle with complex VVC problems due to the limitations of current quantum hardware. To bridge this gap, this paper proposes an innovative QRL algorithm featuring an end-to-end architecture that integrates a classical autoencoder, variational quantum circuits (VQCs), and classical post-processing layers. This design efficiently compresses high-dimensional grid states, enabling VQCs to leverage quantum advantages while producing multiple control device outputs tailored for VVC tasks. Numerical studies on three representative distribution systems verify the effectiveness and scalability of the proposed QRL algorithm, and demonstrate its enhanced performance over classical approaches with only approximately 1% of the parameters. Additionally, the robustness of our developed algorithm is validated through noisy quantum environments.

97 MATHEMATICS AND COMPUTING↗

Load Modeling with Smart Meter Data for Advanced Volt-VAR Optimization Applications

This paper demonstrates the creation of time-varying, end-use electric load models with electric meter data for use by advanced, model-based volt-VAR optimization (VVO) control schemes. VVO has been shown to reduce energy consumption and peak demand in the electric distribution system. Modern VVO systems use power flow models to make control decisions. In order to make optimal decisions, these models must contain accurate load models. To improve these load models, this work uses active power, reactive power, and voltage magnitude measurements from advanced metering infrastructure (AMI) in a simulated distribution feeder to create electric load models for each customer meter. Three different modeling approaches are discussed, and their effectiveness is measured by comparing the optimality of VVO solutions with a base case. The results show that the models derived from AMI data can accurately represent some end-use load behavior like total energy costs, but lose accuracy when considering more dynamic system behavior like voltage violations over small time intervals. This work helps to advance state-of-the-art, model-based VVO by providing a data-driven modeling technique which acknowledges that optimal distribution system control requires a treatment of the system which is dependent on time, voltage, and system conditions.

Thayer, Brandon L.↗

A VSM-Based DER Dispatch MINLP for Volt-VAR Control in Unbalanced Power Distribution Systems

This paper presents an optimal dispatch algorithm to coordinate customer-owned controllable loads and smart solar inverters with utility-owned voltage regulators and capacitors to meet voltage control objectives. The optimization problem is formulated as a mixed-integer nonlinear programming (MINLP) problem. A voltage sensitivity matrix (VSM) is used to linearize the effect of control actions on the voltage at customer nodes when solving the MINLP. The VSM is recalculated at each time step to improve the computational accuracy. Both discrete switching actions of the capacitor and VRs and the continuous adjustment of real and reactive power from load and smart inverters are considered in the MINLP volt-var problem formulation. The objective function minimizes the cost of all control actions and the magnitude of voltage fluctuations from the previous time period. Constraints ensure that the voltage at each node is maintained within ANSI limits and the feeder power factor is controlled within the desired range. The algorithm is tested using an actual 3-phase unbalanced distribution feeder model. Simulation results demonstrate that the proposed algorithm is computationally feasible on real circuits and improves voltage control while minimizing operational costs.

McEntee, Catie↗

Bi-Level Volt-VAR Optimization to Coordinate Smart Inverters with Voltage Control Devices

Conservation voltage reduction (CVR) uses voltage control to reduce customer power demand and help improve the operational efficiency of the electric power distribution system. With the advent of advanced distribution management systems (ADMS), the underlying data and control-rich platform can be utilized to enable a centralized Volt-VAR optimization (VVO) scheme that includes smart inverter controls along with legacy voltage control devices such as voltage regulators and capacitor banks to ensure a maximum CVR benefit. The objective of this paper to present a VVO approach that controls system’s legacy voltage control devices and coordinates their operation with smart inverter control. An optimal power flow (OPF) formulation is proposed by developing linear and nonlinear power flow approximations for a three-phase unbalanced electric power distribution system. A bi-level VVO approach is proposed where, Level-1 optimizes the control of legacy devices and smart inverters using a linear approximate three-phase power flow. In Level-2, the control parameters for smart inverters are adjusted to obtain an optimal and feasible solution by solving the approximate nonlinear OPF model. Level-1 is modeled as a Mixed Integer Linear Program (MILP) while Level-2 as a Quadratically Constrained Quadratic Program (QCQP). The proposed approach is validated using IEEE test cases and the results demonstrate the applicability of the framework in achieving the CVR objective.

Jha, Rahul Ranjan↗

Distributionally Robust Decentralized Volt-Var Control With Network Reconfiguration

Here, this paper presents a decentralized volt-var optimization (VVO) and network reconfiguration strategy to address the challenges arising from the growing integration of distributed energy resources, particularly photovoltaic (PV) generation units, in active distribution networks. To reconcile control measures with different time resolutions and empower local control centers to handle intermittency locally, the proposed approach leverages a two-stage distributionally robust optimization; decisions on slow-responding control measures and set points that link neighboring subnetworks are made in advance while considering all plausible distributions of uncertain PV outputs. We present a decomposition algorithm with an acceleration scheme for solving the proposed model. Numerical experiments on the IEEE 123 bus distribution system are given to demonstrate its outstanding out-of-sample performance and computational efficiency, which suggests that the proposed method can effectively localize uncertainty via risk-informed proactive timely decisions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Connectivity-enhanced route selection and adaptive control for the Chevrolet Volt

The National Renewable Energy Laboratory and General Motors evaluated connectivity-enabled efficiency enhancements for the Chevrolet Volt. A high-level model was developed to predict vehicle fuel and electricity consumption based on driving characteristics and vehicle state inputs. These techniques were leveraged to optimize energy efficiency via green routing and intelligent control mode scheduling, which were evaluated using prospective driving routes between tens of thousands of real-world origin/destination pairs. The overall energy savings potential of green routing and intelligent mode scheduling was estimated at 5% and 3%, respectively. Furthermore, these represent substantial opportunities considering that they only require software adjustments to implement.

30 DIRECT ENERGY CONVERSION↗

Development of High Electronic Quality CdTe Films Required for 1 Volt V OC CdTe Cells

The main goal of this project was to develop an understanding of the role of point defects and demonstrate control of the doping process in thin films of CdTe, using a deposition process that can create conditions favorable for extrinsic (mainly group V) dopant incorporation. The project’s two key objectives were to demonstrate: (a) doping concentrations in p-CdTe above 10 16 cm -3 , and (b) lifetimes greater than 2 ns. Device modeling suggests that both these conditions are required to achieve V OC ’s of 1.0 Volt in thin film CdTe cells a long-sought objective of the CdTe thin film community. The process utilized for the deposition of the CdTe thin films is unique in that it can be used to create Cd- or Te-rich conditions (or stoichiometric) in order to favor the formation of certain native defects (i.e. Cd or Te vacancies). All significant accomplishments clearly pointed to the impact of deposition conditions on the formation of defects in CdTe thin films.

14 SOLAR ENERGY↗