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Practical application of deep learning based non-intrusive load monitoring (NILM) system requires the deep neural network model to generalize on new unseen data. Existing NILM solutions are not suitable for real-world application due to their poor disaggregation accuracy on new unseen data. In order to address this problem, this paper presents a NILM algorithm that uses data augmentation to generate

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Power utilities are adopting Automated Demand Response (ADR) to replace the costly fuel-fired generators and to preempt congestion during peak electricity demand. Similarly, third-party Demand Response (DR) aggregators are leveraging controllable small-scale electrical loads to provide on-demand grid support services to the utilities. Some aggregators and utilities have started employing Artificial

The information and communication technology (ICT) is increasingly involved in the measurement, operation, control and protection of the cyber-physical power system (CPPS). As one of the most promising communication infrastructure projects, Starlink is a satellite Internet constellation being constructed by SpaceX for providing global Internet access, which can benefit the network service supply for

The technology of virtual synchronous machine (VSM) is attracting interest of researchers as it controls converters mimicking the synchronous machine’s response so as to provide inertial support for power electronics dominated smart grids. For the VSM-based microgrid, its slow dynamics are dominated by synchronous generators (SGs) and the VSM control loops, which makes it possible to model this microgrid

Generators are critical components of electrical grids and have to operate synchronously. Unfortunately, faults in power grids can cause significant electro-mechanical oscillations. A number of methods to estimate these electro-mechanical oscillation modes have been proposed in the literature. With the advent of synchrophasors which enable real-time measurements over a wide-area, and in keeping with

Plug-in electric vehicle (PEV) charging station service capability is physically limited by the charger availability and local transformer capacity. However, the station operation performance has become an increasingly important factor for enhancing charging service accessibility. In this work, we propose an innovative station-level optimization framework to operate charging station with optimal pricing

To avoid potential privacy threats and associated cyber-security issues in microgrids, this letter presents a distributed active power sharing and frequency regulation method with preserved privacy of local information. In the proposed approach, the transmitted data including the active power outputs and capacities are protected by adding noise to the original ones. Theoretical analysis and verification

This paper presents a distributed solution for energy trading in smart grid with voltage and congestion management. In the proposed approach, the energy trading is formulated with a distributed consensus algorithm to optimize both generation- and demand-side cost functions based on incremental cost. The proposed approach is designed for directed communication networks.

With the rapid development of microgrid and large-scale grid-connected operation, the detection and location of short-circuit faults in microgrid has become a bottleneck. In this paper, a simulation model of short-circuit fault in low-voltage AC microgrid is built on PSCAD/EMTDC. The characteristics of current wavelet energy spectrum under various short-circuit fault states are studied and the early

Integrated electricity and heat systems facilitate efficient interactions between individual energy sectors for higher renewable energy accommodation. However, the feasibility of operational strategies is difficult to guarantee due to the presence of substantial uncertainties pertinent to renewable energy and multi-energy loads. This paper proposes a novel efficient robust scheduling model of integrated

Simulations have shown that while semi-definite relaxations of AC optimal power flow (AC-OPF) on three-phase radial networks with only wye connections tend to be exact, the presence of delta connections seem to render them inexact. This article shows that such inexactness originates from the non-uniqueness of relaxation solutions and numerical errors amplified by the non-uniqueness. This finding motivates

In this paper, a novel mask-based load disaggregation scheme is presented to extract flexible load profiles in buildings. Flexible loads are those that can be adjusted as needed and examples of such loads are heating, ventilation, and air-conditioning (HVAC), and lighting loads. Knowledge about the flexible sub-load in buildings is crucial for demand-side management programs. However, the load decomposition

Load identification is a core concept in non-intrusive load monitoring (NILM). Through NILM systems, users can check their home appliance usage habits and then adjust their behavior to save electricity. In this way, a NILM system offers an effective method to detect the event status of household appliances as well as individual loads’ energy consumption. However, prior NILM methods have encountered

Wide-area protection scheme (WAPS) provides system-wide protection by detecting and mitigating small and large-scale disturbances that are difficult to resolve using local protection schemes. As this protection scheme is evolving from a substation-based distributed remedial action scheme (DRAS) to the control center-based centralized RAS (CRAS), it presents severe challenges to their cybersecurity

With the rapid advancement and integration of communication and sensor technologies, power system operation is becoming more vulnerable to cyberattacks, particularly attacks in which malicious data could induce catastrophic consequences on market operations. Financial risks, as well as the potential physical damages, raise growing concerns about the reliable operation of the electricity market. Existing

Nowadays, smart meters are deployed in millions of residential households to gain significant insights from fine-grained electricity consumption data. The information extracted from smart meter data enables utilities to identify the socio-demographic characteristics of electricity consumers and then offer them diversified services. Traditionally, this task is implemented in a centralized manner with

To narrow the width of prediction interval while guaranteeing coverage for probabilistic short term load forecasting, we propose a deep-learning forecasting model based on neural basis expansion analysis (N-BEATS). It takes load data as input, and feed the load sequence into three stacks. Each stack projects the load sequence on a set of basis vectors. Both the basis vectors and the corresponding coefficients

Most of the distributed control strategies for grid-connected power converters are droop-based approaches composed of converters driven in voltage-control mode, based on local and shared data with adjacent units. They are usually combined with consensus protocols to deal with the trade-off between power sharing accuracy and voltage/frequency regulation. To achieve the desired results these control

Demand-side management (DSM) is a process by which the user demand patterns are modified to meet certain desired objectives. Traditionally, DSM was utility-driven, but with an increase in the integration of renewable sources and privacy-conscious consumers, it also becomes a “consumer-driven” process. Promising theoretical studies have shown that privacy can be achieved by shaping the user demand using

The steady-state security region of the integrated energy system (IES) is a useful tool for rapid security assessment and security evaluation of the integrated energy system. A complete characterization of the IES steady-state security region is derived. The derivation is under the nonlinear and non-convex AC power flow model, the gas flow model, and the uncertainty of renewable energy without any

This paper presents flexible operating modes of marine DC microgrids and main advantages of employing energy storage systems into such DC microgrids. Scaled-down marine systems with two DC buses and integrated energy storages are considered in this paper. To verify superior features of the DC microgrids with solid-state technologies and energy storage systems, a wide range of system operating modes

Recently, several numerical algorithms have been proposed to solve the power flow (PF) problems of islanded microgrids (MGs). However, these algorithms approximate the steady-state model of the distributed generation units (DGs) as linear equations. In some cases, this linear approximation leads to inaccurate PF solutions due to dead-zone and generation limits of the given DGs. To fill this gap, we

With the spatial flexibility exchange across the network, mobile energy storage systems (MESSs) offer promising opportunities to elevate power distribution system resilience against emergencies. Despite the remarkable growth in integration of renewable energy sources (RESs) in power distribution systems (PDSs), most recovery and restoration strategies do not unlock the full potential in such resources

This paper presents an operating model of a station that charges a single-depot and homogeneous fleet of electric vehicles (EV) performing deliveries. Both the charging station and the fleet of EVs are owned by a single delivery company. The operating model, whose goal is to find the optimal EV battery charging schedule, is based on a clustering technique that keeps track of the number of EVs with

Electric microgrids require accurate dynamic models for operation, control, stability, and protection studies, then adequate load modeling plays an important role. This paper presents a two-stage adaptive approach to improve the generalization capability of load models obtained with the measurement-based modeling. The load model and their respective parameters are obtained through machine learning

In recent years, the rapid growth of active consumers in the distribution networks transforms the modern power markets’ structure more independent, flexible, and distributed. Specifically, in the recent trend of peer-to-peer (P2P) transactive energy systems, the traditional consumers became prosumers (producer+consumer) who can maximize their energy utilization by sharing it with neighbors without

Economic dispatch is a critical problem in operation of power grids. A consensus-based algorithm was recently proposed to solve the economic dispatch problem in a distributed manner. In this paper, we propose a novel secure scheme for the consensus-based economic dispatch algorithm using the Paillier cryptosystem. This secure scheme ensures that not only the network transmitted information is protected

In this paper, a distributed planning method for EV dynamic wireless charging system (DWCS) is proposed, which determines the locations and the scales of DWCS to maximize the economic effects of wireless charging while meeting EV charging demands. The Nesterov’s model with multiple traffic patterns is adopted in the traffic network (TN) to solve the traffic assignment problem and the traffic wave theory

The IEEE T ransactions on S mart G rid Editor-in-Chief and Editorial Board would like to thank and recognize the following top Associate Editors and Reviewers for their outstanding commitment and contributions to the journal in 2020, and for their indefatigable efforts, which together with those of all Associate Editors and Reviewers have helped to maintain, if not improve, the quality and relevance

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In [1] , an additional affiliation for Omar Hafez was not included. The affiliation information in the first footnote should read as follows:

In [1] , an additional affiliation for Omar Hafez was not included. The affiliation information in the first footnote should read as follows:

This paper is dedicated to solving the economic dispatch problem in smart grids, which aims at minimizing the total generation cost while satisfying the power supply-demand balance and generation capacity constraints. A distributed algorithm is proposed to solve the economic dispatch problem over directed communication topologies that are time-varying unbalanced. Its features are that the proposed

Distribution-level phasor measurement units, a.k.a, micro-PMUs, report a large volume of high resolution phasor measurements which constitute a variety of event signatures of different phenomena that occur all across power distribution feeders. In order to implement an event-based analysis that has useful applications for the utility operator, one needs to extract these events from a large volume of

This paper proposes hybrid islanding detection for inverter-based distributed generation (DG) units. Conventionally, passive islanding detection methods may fail when power mismatches are nearly zero. Also, the difficulty of setting threshold is another common problem. To overcome this drawback, a new procedure for islanding detection is proposed based on the combination of the rate of change of voltage

With the advent of the advanced metering infrastructure, electricity usage data is being continuously generated at large volumes by smart meters vastly deployed across the modern power grid. Electric power utility companies and third party entities such as smart home management solution providers gain significant insights into these datasets via machine learning (ML) models. These are then utilized

This paper studies the vulnerability of deep reinforcement learning (DRL) models for power systems topology optimization under data perturbations and cyber-attack. DRL has recently solved many complex power system optimization problems. However, it has been practically proven that small perturbations of input data can lead to drastically different control decisions and induce danger. To evaluate and

Interconnection of microgrids (MGs) provides the opportunity of increasing loadability and enhancing reliability by allowing power exchange among individual MGs. Control of networked MGs requires coordination of distributed energy resources (DERs) within each MG such that the sum of the MG’s load and exported power is shared proportionally among DERs while maintaining power quality. This paper proposes

Several drawbacks of the conventional and inverse droop control based decentralized techniques for islanded microgrids are being addressed actively, over the years by various researchers. One of the prominent issues is the inaccurate power sharing (reactive power in the conventional droop and real power in the inverse droop) among the distributed generators (DGs) due to the feeder/line impedances.

Communication systems introduce uncertainties that directly impact power system management. Quantitative analysis of such impact is essential for power system reliability and resilience. This paper establishes rigorous relationships between communication packet delivery ratio and errors on optimal load tracking and allocation (OLTA) in DC microgrids (MGs). By modeling channel uncertainties using packet

The most commonly used method for including photovoltaic system in the control of system frequency is to operate a PV power plant at reduced power while maintaining a specific amount of available power reserve. Such operating regime, often referred to as de-loaded, can cause additional costs and, consequently, determining a required power reduction becomes vitally important. This paper introduces a

Energy storage (ES) plays a significant role in modern smart grids and energy systems. To facilitate and improve the utilization of ES, appropriate system design and operational strategies should be adopted. The traditional approach of utilizing ES is the individual distributed framework in which an individual ES is installed for each user separately. Due to the cost inefficiency of the individual

This paper proposes a novel adversarial scheme for learning from data under harsh learning conditions of partially labelled samples and skewed class distributions. This novel scheme integrates the generative ability of the state-of-the-art conditional generative adversarial network with the semi-supervised deep ladder network and semi-supervised deep auto-encoder. The proposed generative-adversarial

We present a method for joint phase identification and topology recovery in unbalanced three phase radial networks using only voltage measurements. By recovering phases and topology jointly, we utilize all three phase voltage measurements and can handle networks where some buses have a subset of three phases. Our method is theoretically justified by a novel linearized formulation of unbalanced three

Distribution-level electricity market provides a platform for trading energy and grid services from large-amount of small-scale distributed energy resources (DERs) located on distribution grids. The behavior of the DERs in the distribution electricity market may ultimately impact the market-clearing and locational marginal prices (LMPs) in the wholesale market. This paper proposes a bi-level optimization

In this paper, we consider the distributed reactive power sharing control problem for an autonomous inverter-based microgrid with resilience for communication faults, which may be caused by partial communication link failures or some channel manipulation attacks. Under the standard decoupling approximation for bus angle differences, the reactive power flow of each inverter can be controlled by manipulating

Electrical energy storage (EES) with a virtual synchronous generator (VSG) method is used widely for power fluctuation compensation in renewable energy microgrid systems. In the traditional VSG method, the inertia moment and damping coefficients usually remain constant. When dealing with large load variations, this method may cause obvious system frequency deviations and exceed the standard limit (e

Electric buses (EBs) possess large-capacity batteries and are dispatched by a central operator, exhibiting great potential to enhance the resilience of distribution systems (DSs) against meteorological disasters. This paper proposes an optimization model for joint post-disaster DS restoration, considering coordinated dispatching with EBs. By assuming that the DS can rent some EBs from the bus company

Wide-area measurement, protection and control systems link the cyber power system with the physical power system to realize a cyber-physical power system (CPPS). This paper proposes a reliability modeling and assessment method for the wide-area protection system (WAPS). The proposed WAPS model takes into account the decision accuracy of protection algorithms with limited available data at the control

The increasing penetration of dc distributed energy resources (DERs) and dc loads has motivated the utilization of dc microgrids (MGs). In this paper, a new two-level control scheme is proposed for accurate power sharing and appropriate voltage regulation in dc MGs during islanded operation mode. In the primary control level, a $P-\dot {V}$ droop method is proposed to eliminate the dependency of power

The distributed Volt/Var control (VVC) methods have been widely studied for active distribution networks(ADNs), which is based on perfect model and real-time P2P communication. However, the model is always incomplete with significant parameter errors and such P2P communication system is hard to maintain. In this article, we propose an online multi-agent reinforcement learning and decentralized control