The proceedings contain 93 papers. The topics discussed include: network-aware mitigation of undetectable PMU time synchronization attacks;communication and computation resource allocation and offloading for edge inte...
ISBN:
(纸本)9781728161273
The proceedings contain 93 papers. The topics discussed include: network-aware mitigation of undetectable PMU time synchronization attacks;communication and computation resource allocation and offloading for edge intelligence enabled fault detection system in smart grid;side channel security of smart meter data compression techniques;power system state estimation using gauss-newton unrolled neural networks with trainable priors;generative adversarial networks and transfer learning for non-intrusive load monitoring in smartgrids;mitigating cascading failures via local responses;demand-side scheduling based on multi-agent deep actor-critic learning for smartgrids;edge layer design and optimization for smartgrids;and achieving sensor identification and data flow integrity in critical cyber-physical infrastructures.
The proceedings contain 93 papers. The topics discussed include: zero-day attack detection in digital substations using in-context learning;fast grid emissions sensitivities using parallel decentralized implicit diffe...
ISBN:
(纸本)9798350318555
The proceedings contain 93 papers. The topics discussed include: zero-day attack detection in digital substations using in-context learning;fast grid emissions sensitivities using parallel decentralized implicit differentiation;electricity substation supply area based data collation and visualization techniques for local area energy planning: perspectives from UK distribution network datasets;graphical learning based fault detection and classification in distribution systems;MANTRA: a multi-appliance transformer for non-intrusive load monitoring;REC to ReCert: introducing re-certification to empower prosumer-driven certificate aggregators;machine learning-based feature selection for intrusion detection systems in IEC 61850-based digital substations;and on the relation between the phase and amplitude response of indoor PLC channels.
The proceedings contain 94 papers. The topics discussed include: digital twin for evaluating detective countermeasures in smart grid cybersecurity;a data integrity attack targeting VSC-HVDC-connected offshore wind far...
ISBN:
(纸本)9781665455541
The proceedings contain 94 papers. The topics discussed include: digital twin for evaluating detective countermeasures in smart grid cybersecurity;a data integrity attack targeting VSC-HVDC-connected offshore wind farms;hardware-in-the-loop evaluation of grid-edge DER chip integration into next-generation smart meters;industrial network protocol security enhancement using programmable switches;distribution network digital twin: a basic machine learning based voltage estimator;enhancing short-term load forecasting with technical indicators and tree-structured Parzen estimator;optimizing pricing and charging strategy for electric taxis considering credit mechanism;hierarchical multi-layered sparse identification for prediction of non-linear dynamics of reconfigurable microgrids;and negative price forecasting in Australian energy markets using gradient-boosted machines: predictive and probabilistic analysis.
The proceedings contain 71 papers. The topics discussed include: mitigation of cyberattacks through battery storage for stable microgrid operation;automatic differentiation of variable and fixed speed heat pumps with ...
ISBN:
(纸本)9781665432542
The proceedings contain 71 papers. The topics discussed include: mitigation of cyberattacks through battery storage for stable microgrid operation;automatic differentiation of variable and fixed speed heat pumps with smart meter data;cooperative carbon emission trading: a coalitional game approach;edge computing supported fault indication in smart grid;time-of-use-aware priority-based multi-mode online charging scheme for EV charging stations;a hybrid submodular optimization approach to controlled islanding with heterogeneous loads;a reconfigurable and secure firmware updating framework for advanced metering infrastructure;probabilistic capacity planning framework for electric vehicle charging stations with overstay;fast graphical learning method for parameter estimation in large-scale distribution networks;microgrid fault detection utilizing state observer and multi-agent system;and scheduling electric vehicle fleets as a virtual battery under uncertainty using quantile forecasts.
The proceedings contain 71 papers. The topics discussed include: talking after lights out: an ad hoc network for electric grid recovery;data-driven frequency regulation reserve prediction based on deep learning approa...
ISBN:
(纸本)9781665415026
The proceedings contain 71 papers. The topics discussed include: talking after lights out: an ad hoc network for electric grid recovery;data-driven frequency regulation reserve prediction based on deep learning approach;analysis of moving target defense in unbalanced and multiphase distribution systems considering voltage stability;scalable integration of high sampling rate measurements in deterministic process-level networks;minimizing age of information for distributed control in smartgrids;cyber-physical disaster response of power supply using a centralised-to-distributed framework;detecting attacks on synchrophasor protocol using machine learning algorithms;and achieving runtime state verification assurance in critical cyber-physical infrastructures.
The proceedings contain 103 papers. The topics discussed include: European case studies for impact of market-driven flexibility management in distribution systems;latency minimization for energy Internet communication...
ISBN:
(纸本)9781538680995
The proceedings contain 103 papers. The topics discussed include: European case studies for impact of market-driven flexibility management in distribution systems;latency minimization for energy Internet communications with SDN virtualization infrastructure;on the feasibility, cost, and carbon emissions of grid defection;spectrum and power allocation for vehicular networks with diverse latency requirements;online demand response of voltage-dependent loads for corrective grid de-congestion;research on high-precision time distribution mechanism of multi-source power grid based on MEC;and a market oriented, reinforcement learning based approach for electric vehicles integration in smart micro grids.
The proceedings contain 99 papers. The topics discussed include: Battery scheduling in a residential multi-carrier energy system using reinforcement learning;application of a deep learning generative model to load dis...
ISBN:
(纸本)9781538679548
The proceedings contain 99 papers. The topics discussed include: Battery scheduling in a residential multi-carrier energy system using reinforcement learning;application of a deep learning generative model to load disaggregation for industrial machinery power consumption monitoring;parallel statistical model checking for safety verification in smartgrids;a plug-and-play home energy management algorithm using optimization and machine learning techniques;OpenStack-based evaluation framework for smart grid cyber security;low complexity closed-loop energy manager for a grid-tied PV system with battery;power system equipment cyber-physical risk assessment based on architecture and critical clearing time;and EDSGuard: Enforcing network security requirements for energy delivery systems.
Band-Stop filter is one of the key components in smartgrids, wireless communications systems, radar, and signal processing. Due to the ability of suppressing signals at specific frequencies, these filters enable the ...
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ISBN:
(数字)9798350318555
ISBN:
(纸本)9798350318562;9798350318555
Band-Stop filter is one of the key components in smartgrids, wireless communications systems, radar, and signal processing. Due to the ability of suppressing signals at specific frequencies, these filters enable the rejection of unwanted signals in a particular frequency band in a crowded microwave spectra. Specifically, such filters can be utilized to mitigate the effect of harmonics in smartgrids. The traditional band-stop filters suffer from lack of high suppression, reconfigurable bandwidth and frequency agility. This paper presents a novel approach to realize reconfigurable and flexible band-stop filters using the computing-in-memory (CIM) technique. The proposed scheme consists of a low-pass filter and a high-pass filter, with their corresponding coefficients programmed into an array of memristive devices. As a result, reconfigurable and low-complexity band-stop filters can be implemented, which support the realization of arbitrary filter impulse responses and high-order filters.
The electrical state of the power distribution grid can be estimated based on noisy measurements of a subset of voltages and currents in the grid. The accuracy and cost of such state estimation depends strongly on the...
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ISBN:
(纸本)9798350318562;9798350318555
The electrical state of the power distribution grid can be estimated based on noisy measurements of a subset of voltages and currents in the grid. The accuracy and cost of such state estimation depends strongly on the selection of measurands. This paper addresses the selection of measurands, i.e. choice of which voltage and current phasors to measure, for the purpose of grid state estimation. The investigation is based on calculation of so-called leverages known from mathematical statistics. Based on the leverages a greedy measurand selection algorithm is prosed. The performance of the algorithm is studied by simulation in a small and a larger example grid.
Security in power line communications (PLC) is a crucial topic, given their deployment in smartgrids. In this paper, we consider the presence of an attacker who aims to damage the communication between two PLC nodes ...
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ISBN:
(纸本)9798350318562;9798350318555
Security in power line communications (PLC) is a crucial topic, given their deployment in smartgrids. In this paper, we consider the presence of an attacker who aims to damage the communication between two PLC nodes by inserting label noise during the channel estimation phase. We present a new approach that uses an f-divergence-based neural receiver to mitigate the effect of label flipping. Although the presented receiver works for any scenario, we study the performance of different f-divergences on a real dataset collected from a PLC system employing joint voltage and impedance modulation. The numerical results demonstrate that the shifted log (SL) divergence achieves a better performance with respect to the famous cross-entropy minimization approach, both in the absence and presence of label noise.
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