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With the continuous expansion of the power system scale and extensive application of phasor measurement units (PMUs), the secure operation of power systems has been increasingly concerned. In this paper, an integrated scheme for online dynamic security assessment (DSA) based on feature selection and regression prediction is proposed. First, partial mutual information (PMI) and the Pearson correlation

The price-based demand response has been considered one of the most effective ways to reduce the peak demand of power grids. However, it is possible to form a new rebound critical peak to threaten the grid stability and economic operation when large-scale loads respond to the price signal simultaneously. Based on the Internet of Things (IoT), this paper proposes a cloud-edge coordination (CEC) automatic

Wireless communications can facilitate transfer of synchrophasor data between spatially separated phasor measurement units (PMUs) and phasor data concentrators (PDCs). However, such communication systems may impose random access delay and failure on PMU channels that lead to missing synchrophasor data frames at the output of the PDC. This paper presents a new approach for online reliability assessment

This paper presents a temporal decomposition strategy to decompose security-constrained economic dispatch (SCED) over the scheduling horizon with the goal of reducing its computational burden and enhancing its scalability. A set of subproblems, each with respect to demand response, normal constraints, and $N-1$ contingency corrective actions at a subhorizon, is formulated. The proposed decomposition

This study presents a market operation model integrated with energy management programs of independent smart grids using bilevel optimization. In this framework, autonomous smart grid entities, in the lower levels, operate their own networks and send decisions to the upper level market operator that clears the day ahead market based on unit commitment and second order conic AC power flow models. A

With rapid growth of distributed renewable generation, the establishment of electricity distribution markets has attracted widespread concerns. Different from existing transmission grid-scale electricity markets, an electricity distribution market is featured by numerous small-scale prosumers, and zero marginal cost and intermittency of renewable generation units. Against this background, this paper

This paper proposes a data-driven approach to assess the wind generation accommodation capability of the integrated electric-heat system. The overall assessment model is constructed based on the two-stage robust decision-making framework, where the uncertainty of wind generation is described by a convex hull formed by historical data. To take a balance between modeling accuracy and computation tractability

Hosting an increasing share of distributed generation and flexible consumers, distribution systems are being more often considered as providers of ancillary services among which are reactive power support and voltage control. For the purpose of reliable and efficient planning and operation of a transmission system, information about reactive power capabilities of connected distribution systems would

In this paper, a resilient distributed $H_{\infty }$ consensus-based control scheme is proposed to be used in the secondary layer of the hierarchical control structure of AC heterogeneous autonomous microgrids (MGs). In the presented study, the external disturbance, the uncertainty on the communication links, and fixed time-delays (FTDs) are all considered as the destabilizing components of the time-varying

Most of the launched power electronics-enabled distributed generators (DGs) adopt phase-locked-loop (PLL) synchronization control. In this paper, we delve into two different autonomous operation control (AOC) strategies to ensure the frequency/voltage profile and accurate power sharing for such DGs in islanded systems. The commonly used AOC is based on the concept of active power-frequency ( $P-f$

Continuity of supply plays a significant role in modern distribution system planning and operational studies. Accordingly, various techniques have been developed for reliability assessment of distribution networks. However, owing to the complexities and restrictions of these methods, many researchers have resorted to several heuristic optimization algorithms for solving reliability-constrained optimization

Air conditioners (ACs) are an important resource for demand-response (DR) services in electricity networks and have motivated much research activity in recent years. Existing approaches to model and control aggregate AC demand largely focus on ensembles of fixed-speed (on/off) compressor technology. However, AC markets are dominated by variable-speed compressor technology, which is rapidly becoming

With the increasing penetration of renewable energy sources and electric vehicles (EVs), coordinated operation of EV aggregator (EVA) and distribution system operation (DSO) becomes a complex multistage and multidimensional stochastic problem. The motivation behind this paper is to develop a decentralized mechanism to offer a computationally efficient and almost optimal on-line policy for such problem

Severe disruptions caused by natural disasters have highlighted the significance of enhancing the distribution system resilience in recent years. However, due to severe uncertain characteristics of natural disasters, there exists an insufficient level of information to evaluate their behavior and consequences. Lack of information such as proper distribution functions for probabilistic methods or known

With the increasing application of Information and Communication Technologies (ICTs), cyberattacks have become more prevalent against Cyber-Physical Systems (CPSs) such as the modern power grids. Various methods have been proposed to model the cybersecurity threats, but so far limited studies have been focused on the defensive strategies subject to the limited security budget. In this paper, the power

In order to improve the efficiency and sustainability of electricity systems, most countries worldwide are deploying advanced metering infrastructures, and in particular household smart meters, in the residential sector. This technology is able to record electricity load time series at a very high frequency rates, information that can be exploited to develop new clustering models to group individual

This paper develops a fully distributed attack-resilient secondary control framework for DC microgrids, in the presence of unknown unbounded attacks on control input channels. The secondary control of each converter consists of an average consensus-based voltage regulator and a consensus-based current regulator that use relative information from neighboring converters. This distributed control manner

Including complementarity constraints in energy storage system (ESS) models in optimization problems ensure an optimal solution will not produce a physically unrealizable control strategy where there is simultaneous charging and discharging. However, the current approaches to impose complementarity constraints require the use of non-convex optimization methods. In this paper, we propose a convex relaxation

Considering the increasing coupling between transmission and distribution networks, an affine arithmetic-based interval power flow algorithm of integrated transmission and distribution (I-T&D) networks is proposed. First, a novel two-step approximation method for sine and cosine functions is proposed to reduce the number of noise variables in the affine form of the injected power, as the basis of the

The problem of optimal planning of plug-in electric vehicle (PEV) charging stations is studied. Different from many other works, we assume the station investor to be a new private entrant into the market who intends to maximize its own profit in a competitive environment. A modified Huff gravity-based model is adopted to describe the probabilistic patronizing behaviors of PEV drivers. Accordingly,

The growing trend in the use of blockchain-based cryptocurrencies in modern communities provides several advantages, but also imposes several challenges to energy markets and power systems, in general. This paper aims at providing recommendations for efficient use of digital cryptocurrencies in today’s and future smart power systems, in order to face the challenging aspects of this new technology.

In this paper a novel concept of event triggering control (ETC) for effective resource utilization is proposed for dc microgrid. Matched uncertainty elimination is possible through sliding mode control (SMC) itself as addressed in the literatures. This paper proposes a new approach for suppression of both matched and unmatched uncertainties in grid connected and islanded mode through an integral disturbance

The microgrid is widely recognized as a promising concept for integrating distributed energy resources (DERs). Considering the enormous number of DERs, the future smart grid will likely be a grid containing a number of interconnected microgrids. Thus, the optimal power flow (OPF) problem should be studied by properly taking account of the coupling between the microgrids. In this paper, the models of

The interdependency of transportation and electric power networks is becoming tighter due to the proliferation of electric vehicles (EVs), which introduces additional difficulties in the planning of the two networks. This paper presents the enhanced solution for the coordinated planning of multiple facilities in the two networks, including electric power lines, transportation roads, energy storage

Fast-acting reactive power support from distributed generations (DGs) is a promising approach for tackling rapid voltage fluctuations in distribution networks. However, the voltage regulation range via reactive power of DGs alone is narrow especially in distribution networks with high resistance-reactance ratio. In this paper, a randomized algorithm is proposed to improve the voltage profile in distribution

Recovering the distribution grid topology is essential to perform several distribution system operator functions. Many algorithms that address the topology recovery problem have already been proposed in the literature. Most are based on a priori information regarding which buses are fed by which substation; however, this information might not be available because frequent grid reconfigurations change

Electric power utilities employ “smart” re-closing devices capable of capturing electrical disturbance (ED) waveforms in real-time. These waveforms are digitally sampled, transmitted back to the utility, and stored in text files that comply with the IEEE COMmon format for TRAnsient Data Exchange (COMTRADE) standard. An average of 2,100 ED events are recorded, by 850 devices, on a monthly basis within

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In this paper, the issue of interarea oscillations in wide-area power systems with false data injection (FDI) attacks is studied. A wide-area robust sliding mode controller (WARSMC) is proposed to defense the hacker attacks and damp out the interarea oscillations. First, an extended observer is designed to estimate the states and defense actuator attacks simultaneously. Then, a WARSMC based on the

With the significant increase in integration of renewable energy generation into the electric grid, market-based transactive exchanges between energy producers and prosumers will become more common. Transactive energy systems (TESs) employ economic and control mechanisms to dynamically balance the demand and supply across the electrical grid. Emerging transactive control mechanism depends on a large

This paper presents a two-layer distributed cooperative control method for networked microgrid (NMG) systems, taking into account the proprietary nature of microgrid (MG) owners. The proposed control architecture consists of an MG-control layer and an NMG-control layer. In the MG layer, the primary and distributed secondary controls realize accurate power sharing among distributed generators (DGs)

This paper presents a framework for malicious corruption resilience in phasor measurement unit (PMU) data and a methodology for applying this in wide-area damping control. The problem of detecting corruptions in raw PMU measurements is formulated as a compressed sensing problem and the compromised signals are recovered using an lp-norm (0 <; p <; 1)-based online robust principal component analysis

The increasing penetration of distributed photovoltaics (PVs) has brought great challenges to the security and stability of distribution networks (DNs), especially voltage violation. Current voltage optimization methods rarely consider the mutual voltage support between high voltage (HV) and medium voltage (MV) DNs, which may cause PV generation losses in extreme scenarios. Limited by the convergence

Existing models featuring numerous electric vehicles (EVs) for centralized frequency regulation achieved high accuracy at the expense of heavy computational workloads and a high real-time communication requirement. This paper develops a state space model (SSM) that provides a probability to realize the real-time power control of aggregated EVs with high accuracy and computational efficiency but a low

The online monitoring data in distribution networks contain rich information on the running states of the networks. By leveraging the data, this paper proposes a spatio-temporal correlation analysis approach for anomaly detection and location in distribution networks. First, spatio-temporal matrix for each feeder line in a distribution network is formulated and the spectrum of its covariance matrix

This paper presents a two-stage microgrid scheduling strategy in which the frequency control reserve (FCR) is incorporated to ensure economic, reliable, and stable microgrid operation in a joint energy and ancillary service market environment. In addition, to using such reserve to limit frequency excursions caused by uncertainties of active loads and renewable generation, this paper is focused on determining

The cascaded control method with an outer voltage loop and an inner current loop has been traditionally employed for the voltage and power control of photovoltaic (PV) inverters. This method, however, has very limited power regulation capability. With the fast increasing penetration of PV power generation systems in the distribution network, the voltage rise/drop has become a serious problem impacting

Mobile energy storage systems (MESSs) provide promising solutions to enhance distribution system resilience in terms of mobility and flexibility. This paper proposes a rolling integrated service restoration strategy to minimize the total system cost by coordinating the scheduling of MESS fleets, resource dispatching of microgrids, and network reconfiguration of distribution systems. The integrated

Hurricanes can damage transmission network structure components, e.g., towers and conductors, and threat the system reliability. To quantify the consequence severity of hurricanes on transmission networks, a spatial-temporal reliability and damage assessment method is proposed to evaluate the effect of a specific hurricane. The hurricane can be a simulated, historical, or forecasting one for different

Trustworthy and secure operation of the cyber-power system calls for resilience against malicious and accidental failures. The objective of a resilient system is to withstand and recover operation of the system to supply critical loads despite multiple contingencies in the system. To take timely actions, we need to continuously measure the cyberphysical security of the system. We propose a cyber-physical

In this paper, an intelligent multi-microgrid (MMG) energy management method is proposed based on deep neural network (DNN) and model-free reinforcement learning (RL) techniques. In the studied problem, multiple microgrids are connected to a main distribution system and they purchase power from the distribution system to maintain local consumption. From the perspective of the distribution system operator

In this paper, we propose a data-driven algorithm for probabilistic optimal power flow (POPF). In particular, we develop a nonparametric Bayesian framework based on the Dirichlet process mixture model (DPMM) and variational Bayesian inference (VBI) to establish a probabilistic model for capturing the uncertainties involved with wind generation and load power in power systems. In the proposed setup

Machine learning and artificial intelligence (AI) techniques can play a key role in resource allocation and scheduler design in wireless networks that target applications with stringent QoS requirements, such as near real-time control of community resilience microgrids (CRMs). Specifically, for integrated control and communication of multiple CRMs, a large number of microgrid devices need to coexist

The ever-growing requirement for reliability and quality of power supply suggests to enable self-healing features of smart distribution network using intelligent communication and control. In this article, a concept of fully decentralized multi-agent system (FDMAS) automation is proposed to build a unified restoration service framework for distribution network with distribution generators (DGs), where

Energy storage can play an important role in energy management of end users. To promote an efficient utilization of energy storage, we develop a novel business model to enable virtual storage sharing among a group of users. Specifically, a storage aggregator invests and operates the central physical storage unit, by virtualizing it into separable virtual capacities and selling to users. Each user purchases

The future electric grid will consist of significant penetration of renewable and distributed generation that is likely to create a homogenous transmission and distribution (T&D) system, requiring tools that can model and robustly simulate the combined T&D networks. Existing tools use disparate models and formulations for simulation of transmission versus distribution grids and solving for the steady-state

Optimally scheduling power consumption of appliances is the essential feature of smart grid, which enables Demand Response Management (DRM) and helps to shape the power usage profile. This problem is often required to be solved in face of a large number of appliances and many time slots; thus the computational efficiency of solving a large scale optimal power scheduling problem with limited computational

This paper proposes a day-ahead market framework for congestion management in smart distribution networks. The presented scheme provides a platform for collaboration between distribution-level market operator (DMO) and data traffic operator (DTO) to alleviate congested feeders such that data transmission traffic between market participants is effectively managed in a smart grid. In addition, a decentralized

This study is motivated by the recent advancements in developing non-contact line sensor technologies that come at a low cost, but have limited measurement capabilities. While they are intended to measure current, they cannot measure voltage and power. This poses a challenge to certain distribution system applications, such as topology identification (TI), because they commonly use voltage and power

Power system emergency control is generally regarded as the last safety net for grid security and resiliency. Existing emergency control schemes are usually designed offline based on either the conceived “worst” case scenario or a few typical operation scenarios. These schemes are facing significant adaptiveness and robustness issues as increasing uncertainties and variations occur in modern electrical

Electric load forecasting, especially short-term load forecasting (STLF), is becoming more and more important for power system operation. We propose to use multiple kernel learning (MKL) for residential electric load forecasting which provides more flexibility than traditional kernel methods. Computation time is an important issue for short-term forecasting, especially for energy scheduling. However

This paper presents an approximate Reinforcement Learning (RL) methodology for bi-level power management of networked Microgrids (MG) in electric distribution systems. In practice, the cooperative agent can have limited or no knowledge of the MG asset behavior and detailed models behind the Point of Common Coupling (PCC). This makes the distribution systems unobservable and impedes conventional optimization

In the future power system, an increasing number of distributed energy resources will be integrated including intermittent generation like photovoltaic (PV) and flexible demand like electric vehicles (EVs). It has been long thought to utilize the flexible demand to absorb the PV output locally with the technical solution proposed while an effective commercial arrangement is yet to be developed due

The uncertainties of distribution energy resources (DERs) have significant impacts on active distribution networks (ADNs), and it is necessary to control the DER outputs to hedge the negative impacts of their uncertainties on ADNs. However, DER uncertainties are complicated, containing spatial and temporal correlation, which makes it challenging to design proper control schemes, especially when there

Targeting the right customers for energy efficiency (EE) programs is crucial for the power distribution or retail companies to enhance the efficiency of marketing budget allocation and the yield of energy savings. This work presents a scalable methodology for targeting residential customers for EE programs that focus on reducing unnecessary domestic energy consumption and replacing low efficient r

The presence of single-phase distributed generators unevenly injecting active power in three-phase microgrids may create undesired upstream current unbalance. Consequently, voltage asymmetry and even active power curtailment may occur in such networks with negative economic impact. Thus, this paper proposes an optimal multiobjective approach to regulate the active and reactive power delivered by distributed

In a wide-area control system (WACS) of power systems, delays will affect the control performance. Dealing with randomly distributed delays besides achieving desired control performance via the WACS control strategy will make the control strategy design more challenging. Moreover, delays from the centralized controller to actuators in WACS are unknown for the controller when calculating the control

Traditionally, energy consumers pay non-commodity charges (e.g., transmission, environmental and network costs) as a major component of their energy bills. With the distributed energy generation, enabling energy consumption close to producers can minimize such costs. The physically constrained energy prosumers in power networks can be logically grouped into virtual microgrids (VMGs) using telecommunication