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At least 1,711 records · Page 95

The Application of an Evolutionary Programming Process to a Simulation of the ETEX Large-Scale Airborne Dispersion Experiment

Abstract Airborne tracer simulations are typically performed using a dispersion model driven by a high-resolution meteorological model. Besides solving the dynamic equations of momentum, heat, and moisture on the resolved model grid, mesoscale models must account for subgrid-scale fluxes and other unresolved processes. These are estimated through parameterization schemes of eddy diffusion, convection, and surface interactions, and they make use of prescribed parameters set by the user. Such “free” model parameters are often poorly constrained, and a range of plausible values exists for each. Evolutionary programming (EP) is a process to improve the selection of the parameters. A population of simulations is first run with a different set of parameter values for each member, and the member judged most accurate is selected as the “parent” of a new “generation.” After a number of iterations, the simulations should approach a configuration that is best adapted to the atmospheric conditions. We apply the EP process to simulate the first release of the 1994 European Tracer Experiment (ETEX) project, which comprised two experiments in which a tracer was released in western France and sampled by an observing network. The EP process is used to improve a simulation of the RAMS mesoscale weather model, with weather data collected during ETEX being used to “score” the individual members according to how well each simulation matches the observations. The meteorological simulations from before and after application of the EP process are each used to force a dispersion model to create a simulation of the ETEX release, and substantial improvement is observed when these are validated against sampled tracer concentrations.

54 ENVIRONMENTAL SCIENCES↗

Progress in the Development of a Class of Efficient Low Dissipative High Order Shock-capturing Methods

In a series of papers, Olsson (1994, 1995), Olsson & Oliger (1994), Strand (1994), Gerritsen Olsson (1996), Yee et al. (1999a,b, 2000) and Sandham & Yee (2000), the issue of nonlinear stability of the compressible Euler and Navier-Stokes Equations, including physical boundaries, and the corresponding development of the discrete analogue of nonlinear stable high order schemes, including boundary schemes, were developed, extended and evaluated for various fluid flows. High order here refers to spatial schemes that are essentially fourth-order or higher away from shock and shear regions. The objective of this paper is to give an overview of the progress of the low dissipative high order shock-capturing schemes proposed by Yee et al. (1999a,b, 2000). This class of schemes consists of simple non-dissipative high order compact or non-compact central spatial differencings and adaptive nonlinear numerical dissipation operators to minimize the use of numerical dissipation. The amount of numerical dissipation is further minimized by applying the scheme to the entropy splitting form of the inviscid flux derivatives, and by rewriting the viscous terms to minimize odd-even decoupling before the application of the central scheme (Sandham & Yee). The efficiency and accuracy of these scheme are compared with spectral, TVD and fifth- order WENO schemes. A new approach of Sjogreen & Yee (2000) utilizing non-orthogonal multi-resolution wavelet basis functions as sensors to dynamically determine the appropriate amount of numerical dissipation to be added to the non-dissipative high order spatial scheme at each grid point will be discussed. Numerical experiments of long time integration of smooth flows, shock-turbulence interactions, direct numerical simulations of a 3-D compressible turbulent plane channel flow, and various mixing layer problems indicate that these schemes are especially suitable for practical complex problems in nonlinear aeroacoustics, rotorcraft dynamics, direct numerical simulation or large eddy simulation of compressible turbulent flows at various speeds including high-speed shock-turbulence interactions, and general long time wave propagation problems. These schemes, including entropy splitting, have also been extended to freestream preserving schemes on curvilinear moving grids for a thermally perfect gas (Vinokur & Yee 2000).

Yee, H. C.↗

Relaxation dynamics in quantum dissipative systems: The microscopic effect of intramolecular vibrational energy redistribution

We investigate the effect of inter-mode coupling on the vibrational relaxation dynamics of molecules in weak dissipative environments. The simulations are performed within the reduced density matrix formalism in the Markovian regime, assuming a Lindblad form for the system-bath interaction. The prototypical two-dimensional model system representing two CO molecules approaching a Cu(100) surface is adapted from an ab initio potential, while the diatom-diatom vibrational coupling strength is systematically varied. In the weak system-bath coupling limit and at low temperatures, only first order non-adiabatic uni-modal coupling terms contribute to surface-mediated vibrational relaxation. Since dissipative dynamics is non-unitary, the choice of representation will affect the evolution of the reduced density matrix. Two alternative representations for computing the relaxation rates and the associated operators are thus compared: the fully coupled spectral basis, and a factorizable ansatz. The former is well-established and serves as a benchmark for the solution of Liouville-von Neumann equation. In the latter, a contracted grid basis of potential-optimized discrete variable representation is tailored to incorporate most of the inter-mode coupling, while the Lindblad operators are represented as tensor products of one-dimensional operators, for consistency. This procedure results in a marked reduction of the grid size and in a much more advantageous scaling of the computational cost with respect to the increase of the dimensionality of the system. The factorizable method is found to provide an accurate description of the dissipative quantum dynamics of the model system, specifically of the time evolution of the state populations and of the probability density distribution of the molecular wave packet. The influence of intra-molecular vibrational energy redistribution appears to be properly taken into account by the new model on the whole range of coupling strengths. It demontrates that most of the mode mixing during relaxation is due to the potential part of the Hamiltonian and not to the coupling among relaxation operators.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Building Battery Energy Storage System Performance Data into an Economic Assessment

Economic assessments of battery energy storage systems (BESSs) rely on optimal dispatch methods to capture temporal interdependency of BESS operations and coupling among different grid applications. Many existing BESS economic assessment studies are based on a simplified first-order scalar model using BESS nameplate numbers. Such a method cannot accurately capture varying capabilities and nonlinear dynamics of a BESS, leading to inaccurate assessment results. This paper presents a practical implementation of performance data into the economic assessment of the BESSs recently developed within the Snohomish Public Utility District system in Washington State. Extensive testing conducted over multiple seasons is used to assess the technical performance and develop high-fidelity models of the BESSs. A dynamic programming algorithm is proposed to optimally dispatch the BESSs and assess the potential benefits from stacked value streams. The proposed method can be adapted for the economic assessment of other BESSs with different applications.

Wu, Di↗

Probabilistic Look-ahead Contingency Analysis Integrated with GE EMS Tool

This report documents implementation of the smart sampling-based probabilistic look-ahead contingency analysis algorithm, the integration with General Electric (GE) Grid Solutions’ commercial energy management system (EMS) tool, and the case study results using real world data from the Bonneville Power Administration (BPA).The probabilistic look-ahead contingency analysis algorithm incorporates forecast errors of renewable energy and load into contingency analysis functions to enable a predictive capability with a more complete picture, revealing the potential violations that are not normally detected by traditional deterministic approaches. To test its performance under practical environments, the probabilistic look-ahead contingency analysis algorithm has been integrated with the dominant GE EMS tool as a proof-of-concept for a seamless integration. To meet the output format of GE EMS tool, an extreme value distribution (EVD) algorithm is newly adapted to analyze the GE EMS’s violation-only output. Real world data from BPA are used to test its performance, and the results clearly show the effectiveness of the developed algorithm and improved situational awareness. This effort is an example of successful technology transition and cooperation under a real-world environment because it is a joint effort from department of energy, a national laboratory, a commercial vendor, and a large utility.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Simulating single-particle dynamics in magnetized plasmas: The RMF code

The RMF (Rotating Magnetic Field) code is designed to calculate the motion of a charged particle in a given electromagnetic field. It integrates Hamilton’s equations in cylindrical coordinates using an adaptive predictor-corrector double-precision variable-coefficient ordinary differential equation solver for speed and accuracy. RMF has multiple capabilities for the field. Particle motion is initialized by specifying the position and velocity vectors. Here, the six-dimensional state vector and derived quantities are saved as functions of time. A post-processing graphics code, XDRAW, is used on the stored output to plot up to 12 windows of any two quantities using different colors to denote successive time intervals. Multiple cases of RMF may be run in parallel and perform data mining on the results. Recent features are a synthetic diagnostic for simulating the observations of charge-exchange-neutral energy distributions and RF grids to explore a Fermi acceleration parallel to static magnetic fields.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Assessment of Preconditioner for a USM3D Hierarchical Adaptive Nonlinear Method (HANIM) (Invited)

Enhancements to the previously reported mixed-element USM3D Hierarchical Adaptive Nonlinear Iteration Method (HANIM) framework have been made to further improve robustness, efficiency, and accuracy of computational fluid dynamic simulations. The key enhancements include a multi-color line-implicit preconditioner, a discretely consistent symmetry boundary condition, and a line-mapping method for the turbulence source term discretization. The USM3D iterative convergence for the turbulent flows is assessed on four configurations. The configurations include a two-dimensional (2D) bump-in-channel, the 2D NACA 0012 airfoil, a three-dimensional (3D) bump-in-channel, and a 3D hemisphere cylinder. The Reynolds Averaged Navier Stokes (RANS) solutions have been obtained using a Spalart-Allmaras turbulence model and families of uniformly refined nested grids. Two types of HANIM solutions using line- and point-implicit preconditioners have been computed. Additional solutions using the point-implicit preconditioner alone (PA) method that broadly represents the baseline solver technology have also been computed. The line-implicit HANIM shows superior iterative convergence in most cases with progressively increasing benefits on finer grids.

Pandya, Mohagna J.↗

Composite Socio-Technical Systems: A Method for Social Energy Systems

In order to model and study the interactions between social on technical systems, a systemic method, namely the composite socio-technical systems (CSTS), is proposed to incorporate social systems, technical systems and the interaction mechanism between them. A case study on University of Denver (DU) campus grid is presented in paper to demonstrate the application of the proposed method. In the case study, the social system, technical system, and the interaction mechanism are defined and modelled within the framework of CSTS. Distributed and centralized control and management schemes are investigated, respectively, and numerical results verifies the feasibility and performance of the proposed composite system method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Developing Frequency Stability Constraint for Unit Commitment Problem Considering High Penetration of Renewables: Preprint

As zero-carbon electricity systems become the trend of future grid, the system inertia provided by conventional synchronous generators (SGs) keeps decreasing. The resultant lower system inertia will inevitably cause frequency stability problem, especially in the first few seconds after disturbance. To address this challenge, this paper proposes a frequency stability unit commitment constraint considering the fast frequency responses (FFRs) from inverter-based resources (IBRs). Thus, this paper first analyzes a frequency nadir differential equation that considers SG governor model and three kinds of FFR provided by IBRs. A system frequency nadir estimation framework is developed with consideration of various conventional SG and IBR models. The accuracy of this frequency estimation framework is validated by largest N-1 contingency simulation result of a real island system. Then, the adaptive inertia frequency stability unit commitment constraint is derived from sensitivity analysis method. Finally, we demonstrate the effectiveness of our developed constraints with one year day-ahead unit commitment results of the real island system.

fast frequency response↗

The SURE House (Solar Decathlon 2015)

Coastal towns and cities across the Northeastern US, with their high population density, aged utility infrastructure, and unique geography, are increasingly vulnerable to climate change related storm events. In October 2012 superstorm Sandy highlighted the fragility of our current coastal building types and made clear the need for a new model of design and construction which works to understand and mitigate these weaknesses. Dramatic changes in public policy, championed by both The Federal Emergency Management Agency (FEMA) and the National Flood Insurance Program (NFIP) are driving the rebuilding of these shore communities, often resulting in costly renovations, un-sustainable neighborhood configurations and in direct conflict with concurrent government policies such as The American with Disabilities Act (ADA). The SURE HOUSE demonstrates a series of new design solutions to these conflicting public policies and environmental imperatives. At Stevens Institute of Technology, the 2015 Solar Decathlon started with the challenge: Can we design a home for coastal New Jersey that dramatically reduces its energy use while protecting itself from the realities of a changing, more extreme climate? The SURE HOUSE merges the iconic 20th century shore home with 21st century building science. Utilizing innovative renewable energy technologies, a ‘Passive House’ level building envelope, and rugged glass-fiber-composite materials to flood-proof the home, the SURE HOUSE is a high-performance, net-zero-energy home, armored against extreme weather, designed for the contemporary lifestyle of the Jersey Shore and other vulnerable coastal communities. SUSTAINABLE At Stevens, we recognize that energy use in the home and workplace is directly connected to the growing problem of climate change. Reducing our energy consumption by designing higher performing, compact homes that are both functional, comfortable and desirable is the first critical step towards a modern, sustainable architecture for New Jersey and beyond. This is what informed the architectural design of the house. Configured about a compact form, thickly insulated and air-sealed walls eliminate thermal bridging and minimize energy losses while advanced glazing brings in free solar heat during the winter months. As a result of these passive design strategies, the SURE HOUSE has a greatly reduced carbon footprint requiring 91% less energy than a typical New Jersey home. Photovoltaic (PV) arrays on both the rooftop and operable shutters easily provide energy in excess of the home’s modest demands. The Stevens team considers a truly sustainable home in the era of climate change, one that prioritizes low energy use, and integrates right-sized renewable generation to supply the home’s needs. Low consumption, low production. RESILIENT In October of 2012, Hurricane Sandy wreaked havoc along the east coast of the US. In New Jersey alone there was an estimated 29.4 billion dollars in damages, 346,000 homes affected, and almost two and a half million people left without power, in some cases for over 10 days. Recovery from this storm and associated flooding is ongoing to this day, as many New Jersey homeowners grapple with the large costs of rebuilding and struggle to adapt to complicated new home building regulations. Damage from this storm to Hoboken, the home of the Stevens Institute of Technology’s campus, and to the New Jersey shore was extensive and many students on the SURE HOUSE team were directly affected by this historic event. The Stevens design team recognizes that in a world of more frequent and stronger storms, the ability to absorb and adapt to change is more important than ever. Successfully weathering the next storm and its aftermath is one of the primary goals in the design of the SURE HOUSE prototype. The SURE HOUSE introduces unique ‘dry flood-proofing’ methods to residential construction. Innovative wall and floor flood-proofing, utilizing durable composite sheathing materials adapted from the boating industry, were developed by the student team to render the SURE House’s building envelope flood proof up to the FEMA AE 6/7 Zone (+ 6/7 feet of water above sea-level). Designed and fabricated utilizing glass-fiber composite materials, the custom storm shutter system serves to protect the large glazed openings of the home from both air-borne debris impact and water infiltration during a storm event while also providing deterrence from the vandalism that often occurs in the aftermath of a calamitous event. During extended power outages, a ‘resilient’ solar array is capable of supplying critical amounts of energy and hot water to the home, without the use of battery storage or grid infrastructure. PV Description AC GRID-TIED PV SYSTEM The SURE HOUSE solar system consists of two distinct arrays, the grid-tied rooftop array which produces AC Powerand the shutter-mounted array which converts DC power generated by the modules directly into usable heat for the domestic hot water (DHW). The roof-mounted AC grid-tied array is comprised of three strings, two 11 module strings connected to an SMA SB 5000TL-US-223 inverter and a single 10 module string equipped and an SMA SB 3000TL-US-22 central inverter. All modules for the rooftop AC array are LG MonoX 2804 watt solar panels, chosen for their durability and efficiency. Inverter sizing and string size are optimized to the electrical characteristics of the chosen PV modules and the desired energy production, see Appendix 5B. The SURE HOUSE is projected to produce 12,353 kWh per year to meet 6,157 kWh per year of estimated consumption. Solar modules for the two AC grid-tied sub arrays are mounted on the main roof surface of the SURE HOUSE with a 10 degree tilt angle using a partially-ballasted polyethylene roof mounting system made by Renusol, which is particularly suited to the corrosive salt air of a coastal environment. This method was chosen for its installation simplicity and to limit detrimental roof penetrations. The 10 degree tilt optimizes the energy generated per roof area at a lower price, see Appendix 5A, and ensures that there is minimal wind uplift. DC SOLAR ELECTRIC DOMESTIC HOT WATER The SURE HOUSE’s approach to sustainable and resilient domestic hot water (DHW) consists of a unique, custom engineered DC solar electric hot water system. Employing the use of Advanced Energy’s DC electric PV heater (DCPVH)5 to heat domestic water well beyond the draw temperature, the SURE HOUSE is able to obtain a remarkably high solar fraction of 75% or more. The custom modified 80 gallon Vaughn DHW tank acts as a large solar ‘battery’ that stores heat energy in the form of hot water at almost 150 degrees, harvesting energy when the sun is out for use later in the day or overnight. The system, which uses electricity rather than heated fluid, is distinct from traditional ‘solar thermal’ systems by eliminating the dangers and associated maintenance issues of fluid based systems. By forgoing the use of external fluid loops, overheated solar collectors and pipes are not an issue for the SURE HOUSE system which never needs any yearly or seasonal flushing. In weather conditions where the integrated DCPVH unit cannot produce enough hot water via solar energy alone, the Vaughn hot water tank comes factory made with an AC powered 2.6 COP heat pump and a AC heating coil that serve as back-up heating elements. The DCPVH is powered by a DC array consisting of 10 custom-made Solbian by PVilion 180 watt, monocrystalline, flexible solar modules6. The Solbian modules are directly mounted to the top half of the operable storm shutters on the south façade of the SURE HOUSE. The SURE HOUSE team worked closely with PVillion, a PV system designer specializing in flexible architectural photovoltaics, to design an adhesive system that works with the glass-fiber storm shutter surface in a reliable manner over an extended period. Because this system operates in DC-only mode and never connects to the municipal power grid, the system can continue to create hot water safely and effectively even during grid disruption events. This hot water, and the energy stored within it, could be used for a range of activities including washing and cooking to more elaborate hydronic heating systems as desired. See Appendix 6 for system engineering, sizing and modeling.

14 SOLAR ENERGY↗

Limiting Data Friction by Reducing Data Download Using Spatiotemporally Aligned Data Organization Through STARE

Current data processing practice limits the volume and variety of relevant geoscience data that can practically be applied to important problems. File archives in centralized data centers are the principal means by which Earth Science data are accessed. This approach, however, requires laborious search, retrieval, and eventual customization/adaptation for the data to be used. Such fractionation makes it even more difficult to share outcomes, i.e. research artifacts and data products, hampering reusability and repeatability, since end users generally have their own research agenda and preferences as well as scarce resources. Thus, while finding and downloading data files from central data centers are already costly for end users working in their own field, using data products from other disciplines rapidly becomes prohibitive. This curtails scientific productivity, limits avenues of study, and endangers quality and reproducibility. The Spatio-Temporal Adaptive Resolution Encoding (STARE) is a unifying scheme that facilitates the indexing, access, and fusion of diverse Earth Science data. STARE implements an innovative encoding of geo-spatiotemporal information, originally developed for aligning datasets with diverse spatiotemporal characteristics in an array database. The spatial component of STARE recursively quadfurcates a root polyhedron, producing a hierarchical scheme for addressing geographic locations and regions. The temporal component of STARE uses conventional date-time units as an indexing hierarchy. The additional encoding of spatial and temporal resolution information in STARE enables comparisons and conditional selections across diverse datasets. Moreover, spatiotemporal set-operations, e.g. union and intersection, are mapped to efficient integer operations with STARE. Applied to existing data models (point, grid, spacecraft swath) and corresponding granules, STARE indexes provide a streamlined description usable as geo-spatiotemporal metadata. When coupled with large scale, distributed hardware and software, STARE-based data access reduces pre-analysis data preparation costs by offering a convenient means to align different datasets spatiotemporally without specialized effort in parallel computing or distributed data management.

Kuo, Kwo-Sen↗

Extended magnetohydrodynamics with embedded particle-in-cell simulation of Ganymede's magnetosphere

Here, we have recently developed a new modeling capability to embed the implicit particle–in–cell (PIC) model iPIC3D into the Block–Adaptive–Tree–Solarwind–Roe–Upwind–Scheme magnetohydrodynamic (MHD) model. The MHD with embedded PIC domains (MHD–EPIC) algorithm is a two–way coupled kinetic–fluid model. As one of the very first applications of the MHD–EPIC algorithm, we simulate the interaction between Jupiter's magnetospheric plasma and Ganymede's magnetosphere. We compare the MHD–EPIC simulations with pure Hall MHD simulations and compare both model results with Galileo observations to assess the importance of kinetic effects in controlling the configuration and dynamics of Ganymede's magnetosphere. We find that the Hall MHD and MHD–EPIC solutions are qualitatively similar, but there are significant quantitative differences. In particular, the density and pressure inside the magnetosphere show different distributions. For our baseline grid resolution the PIC solution is more dynamic than the Hall MHD simulation and it compares significantly better with the Galileo magnetic measurements than the Hall MHD solution. The power spectra of the observed and simulated magnetic field fluctuations agree extremely well for the MHD–EPIC model. The MHD–EPIC simulation also produced a few flux transfer events (FTEs) that have magnetic signatures very similar to an observed event. The simulation shows that the FTEs often exhibit complex 3–D structures with their orientations changing substantially between the equatorial plane and the Galileo trajectory, which explains the magnetic signatures observed during the magnetopause crossings. The computational cost of the MHD–EPIC simulation was only about 4 times more than that of the Hall MHD simulation.

79 ASTRONOMY AND ASTROPHYSICS↗

Grid-Interactive Multi-Zone Building Control Using Reinforcement Learning with Global-Local Policy Search

In this paper, we develop a grid-interactive multi-zone building controller based on a deep reinforcement learning (RL) approach. The controller is designed to facilitate building operation during normal conditions and demand response events, while ensuring occupants comfort and energy efficiency. We leverage a continuous action space RL formulation, and devise a two-stage global-local RL training framework. In the first stage, a global fast policy search is performed using a gradient-free RL algorithm. In the second stage, a local fine-tuning is conducted using a policy gradient method. In contrast to the state-of-the-art model predictive control (MPC) approach, the proposed RL controller does not require complex computation during real-time operation and can adapt to nonlinear building models. We illustrate the controller performance numerically using a five-zone commercial building.

30 DIRECT ENERGY CONVERSION↗

Grid-Interactive Multi-Zone Building Control Using Reinforcement Learning with Global-Local Policy Search: Preprint

In this paper, we develop a grid-interactive multi-zone building controller based on a deep reinforcement learning (RL) approach. The controller is designed to facilitate building operation during normal conditions and demand response events, while ensuring occupants comfort and energy efficiency. We leverage a continuous action space RL formulation, and devise a two-stage global-local RL training framework. In the first stage, a global fast policy search is performed using a gradient-free RL algorithm. In the second stage, a local fine-tuning is conducted using a policy gradient method. In contrast to the state-of-the-art model predictive control (MPC) approach, the proposed RL controller does not require complex computation during real-time operation and can adapt to non-linear building models. We illustrate the controller performance numerically using a five-zone commercial building.

30 DIRECT ENERGY CONVERSION↗

Adaptive building load control to enable high penetration of solar photovoltaic generation

This paper investigates the ability of a collection of deferrable heating, ventilation and air conditioning (HVAC) loads to directly emulate energy storage devices (ESD), that is, to absorb any low frequency fluctuations in solar generation. We find the optimal number of aggregated HVAC loads to absorb solar fluctuation in the same frequency band based on frequency analysis. To guarantee quality of service in afleet of residential buildings, an optimization problem is formed to compute optimal schedule of the HVAC loads considering temperature comfort band and available solar generation. By minimizing the tracking error between solar generation and total consumption, the proposed method also quantifies the minimum capacity of ESD (battery or fly-wheel) . The simulation results show that the proposed techniques are able to achieve good solar tracking performance as well as obtain a minimal ESD capacity. Therefore, we show that most of the renewable generation can be consumed locally through an intelligent coordination of HVAC loads, their impacts on the grid would be minimal and the required ESD capacity can be minimized.

Dong, Jin↗

An Adaptive Mesh Algorithm: Mesh Structure and Generation

The purpose of Adaptive Mesh Refinement is to minimize spatial errors over the computational space not to minimize the number of computational elements. The additional result of the technique is that it may reduce the number of computational elements needed to retain a given level of spatial accuracy. Adaptive mesh refinement is a computational technique used to dynamically select, over a region of space, a set of computational elements designed to minimize spatial error in the computational model of a physical process. The fundamental idea is to increase the mesh resolution in regions where the physical variables are represented by a broad spectrum of modes in k-space, hence increasing the effective global spectral coverage of those physical variables. In addition, the selection of the spatially distributed elements is done dynamically by cyclically adjusting the mesh to follow the spectral evolution of the system. Over the years three types of AMR schemes have evolved; block, patch and locally refined AMR. In block and patch AMR logical blocks of various grid sizes are overlaid to span the physical space of interest, whereas in locally refined AMR no logical blocks are employed but locally nested mesh levels are used to span the physical space. The distinction between block and patch AMR is that in block AMR the original blocks refine and coarsen entirely in time, whereas in patch AMR the patches change location and zone size with time. The type of AMR described herein is a locally refi ned AMR. In the algorithm described, at any point in physical space only one zone exists at whatever level of mesh that is appropriate for that physical location. The dynamic creation of a locally refi ned computational mesh is made practical by a judicious selection of mesh rules. With these rules the mesh is evolved via a mesh potential designed to concentrate the nest mesh in regions where the physics is modally dense, and coarsen zones in regions where the physics is modally sparse.

97 MATHEMATICS AND COMPUTING↗

Guest Editorial: Planning and operation of resilient distribution system for integrated multi-energy

Resilience is the ability of power systems to prepare for and adapt to low-probability, high-impact incidents and withstand and recover rapidly from disruptions. With the ageing of electricity distribution infrastructure and increasing threats of weather-related incidents and natural disasters, the need to effectively enhance the resilience of the electricity distribution system has become urgent and has attracted worldwide attention. Although there are an increasing number of publications related to enhancing resilience strategies, resilience is an emerging concept in power systems. Existing practices are mostly focused on deploying distributed energy resources (DERs) and microgrids, hardening the existing infrastructures and building redundant capacities. However, from a broader perspective, resilience enhancement of power distribution system is a systematic engineering, involving long-term system planning and upgrading (e.g., deployment of smart grid technologies and intelligent switches), short-term proactive scheduling, real-time robust and resilient control of DERs, and post-event restoration and recovery strategies. Based on this point, this Special Issue in IET Energy System Integration focuses on soliciting the most recent and original technologies, scheduling and control strategies for improving the resilience of power distribution system. Eight papers are presented in this Special Issue, covering various aspects related to resilience enhancement of power distribution system, including fault-tolerant frequency measurement, robust scheduling of integrated electricity and district heating systems, robust control of DERs, efficient methods for safety verification as well as novel graph theory-based approach to restore the distribution systems after multiple simultaneous faults. A brief introduction of these 8 papers is provided below.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Cross-Layered Distributed Data-Driven Framework for Enhanced Smart Grid Cyber-Physical Security

Smart Grid (SG) research and development has drawn much attention from academia, industry and government due to the great impact it will have on society, economics and the environment. Securing the SG is a considerably significant challenge due the increased dependency on communication networks to assist in physical process control, exposing them to various cyber-threats. In addition to attacks that change measurement values using False Data Injection (FDI) techniques, attacks on the communication network may disrupt the power system's real-time operation by intercepting messages, or by flooding the communication channels with unnecessary data. Addressing these attacks requires a cross-layer approach. In this paper a cross-layered strategy is presented, called Cross-Layer Ensemble CorrDet with Adaptive Statistics(CECD-AS), which integrates the detection of faulty SG measurement data as well as inconsistent network inter-arrival times and transmission delays for more reliable and accurate anomaly detection and attack interpretation. Numerical results show that CECD-AS can detect multiple False Data Injections, Denial of Service (DoS) and Man In The Middle (MITM) attacks with a high F1-score compared to current approaches that only use SG measurement data for detection such as the traditional physics-based State Estimation, Ensemble CorrDet with Adaptive Statistics strategy and other machine learning classification-based detection schemes.

cyber-physical security↗