Presents the table of contents for this issue of the publication.

Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.

This paper proposes a Kriging assisted strategy to expedite evolutionary computation for solving Optimal Power Flow (OPF) problems. First, two algorithms were developed–a Kriging Assisted Genetic Algorithm (KAGA) and a Kriging Assisted Particle Swarm Optimization (KAPSO) - and tested using unconstrained benchmark functions; it was found that both algorithms provided reliable and robust solutions. Accordingly

To decarbonize the heating sector, residential consumers may install heat pumps. Coupled with heating loads with high thermal inertia, these thermostatically controlled loads may provide a significant source of demand side flexibility. Since the capacity of residential consumers is typically insufficient to take part in the day-ahead electricity market (DAM), aggregators act as mediators that monetize

This paper presents a hierarchical-hybrid architecture for Volt/Var control of distribution grids in the presence of high penetration of distributed generators (DGs). The architecture includes three layers with specific operational goals associated with each layer based on data resolution, communication network, and control device response time. The top layer carries out central optimization and seeks

Wide-area control helps damp the inter-area oscillations in modern power systems. However, compared to traditional local control, it is more vulnerable to cyber attacks due to its dependence on remote real-time-communicated measurements. In this paper, a formal mathematical framework for analyzing resilience of various wide-area controllers under adversarial scenarios is proposed. A novel resilience

Power systems with high penetration of wind resources must cope with significant uncertainties originated from wind power prediction error. This uncertainty might lead to wind power curtailment and load shedding events in the system as a big challenge. Efficient modeling and incorporation of wind power uncertainty in generation and reserve scheduling can prevent these events. This paper presents a

To address the challenge of the renewable energy uncertainty, the ISO New England (ISO-NE) has proposed to apply do-not-exceed (DNE) limits, which represent the maximum nodal injection of renewable energy the grid can accommodate. Unfortunately, it appears challenging to compute DNE limits that simultaneously maintain the system flexibility and incorporate a large portion of the available renewable

Prosumers, with ability to act both as a supplier and a consumer in a power market, have received considerable attention recently. Possessing with distributed energy resources, their capability to operate in an isolated mode, shielding from the main grid, has also been promoted as a vital option to enhance the power system's resilience. One emerging concern is the prosumer's ability to manipulate the

Stalling of residential air conditioners (RACs) following a transient fault can delay the voltage recovery ranging from 3 to 20 seconds. This phenomenon is referred to as fault-induced delayed voltage recovery (FIDVR). Several aggregated RAC models have been presented to replicate the actual FIDVR events. However, they usually have two main drawbacks as: i) considering independent stalling voltage

Synchronized phasor measurement unit (PMU) data contain rich information about power systems, hence the quality of estimates is of utmost concern. The existing methodologies for estimation rely on certain assumptions regarding the error in the measurement data. This paper revisits a key assumption specifically the Gaussian character of the error. A quantification of the PMU error yields its nature

This paper develops models for hurricane exposure, fragility curve-based damage to electrical transmission grid components and power generating stations using Monte-Carlo simulation, and restoration cost to predict resiliency factors including power generation capacity lost and the restoration cost for electrical transmission grid and power generation system damages. Synthetic grid data are used to

Dynamic simulation is vitally important in power system analysis, but traditional approaches based on numerical integration over small time steps are time-consuming. Also, the Newton-Raphson method suffers from difficulty in convergence when solving nonlinear algebraic equations. This paper proposes a novel dynamic simulation approach based on holomorphic embedding. By obtaining a high-order approximation

Frequency drop due to loss of massive generation is a threat to power system frequency stability. Under-frequency load shedding (UFLS) is the principal measure to prevent successive frequency declination and blackouts. Based on traditional stage-by-stage UFLS scheme, a new continuous UFLS scheme is proposed in this paper to shed loads proportional to frequency deviation. The characteristic of the proposed

This paper proposes a variable proportion coefficient based control scheme for the doubly-fed induction generator based wind turbines (DFIG-WTs) to implement frequency support by regulating rotor speed. To reduce the adverse impact caused by regulating DFIG-WT on the dynamic characteristic of the grid frequency, a two-stage switching control scheme is employed for the proposed method. In the first

With the deployment of online monitoring systems in distribution networks, massive amounts of data collected through them contain rich information on the operating states of the networks. By leveraging the data, an unsupervised approach based on bidirectional generative adversarial networks (BiGANs) is proposed for operational risk assessment in distribution networks in this paper. The approach includes

In this paper, we propose a novel Newton method-based distributed algorithm (NMDA), which is also effective in solving the general single-area EDP (SAEDP), to deal with the multi-area economic dispatch problem (MAEDP), of which the focus is to minimize the total generation cost in the presence of system and generator constraints. To develop the NMDA, we first introduce a virtual SAEDP formulation to

Using their fast power reduction capabilities, the induction motor variable speed drives can successfully participate in the power system primary frequency control. A new control strategy for fast frequency support from the diode front-end induction motor variable speed drive is presented in this paper. By this, practical restrictions are considered. In this context, an existing conventional scheme

We study a non-convex Transmission-Constrained Economic Dispatch (TCED) problem that uses the traditional linear DC model of the transmission system together with a non-linear representation of losses. This problem is typically approximated by the convex problem obtained by linearizing the constraints around some base-case state. Electricity prices and dispatch decisions are then chosen based on the

The rapid increase in the installation of renewable energy sources, particularly solar photovoltaic (PV) sources associated with unbalanced features of distribution systems (DS), disturbs the classic control strategy of voltage regulation devices and causes voltage violation problems. This paper proposes an effective control strategy for voltage regulators in the DS based on the voltage sensitivity

High-voltage direct current (HVDC) systems are increasingly incorporated into today's AC power grids, necessitating optimal power flow (OPF) tools for the analysis, planning, and operation of such hybrid systems. To this end, we introduce hynet , a Python-based open-source OPF framework for hybrid AC/DC grids with point-to-point and radial multi-terminal HVDC systems. hynet 's design promotes ease

As the number of smart meters increases, compression of metering data becomes essential for data transmission, storing and processing perspectives. Specifically, feature extraction can be used for the compression of metering data and further be utilized for smart grid applications such as customer clustering. So far, there are many studies for compression and clustering based on daily load profiles

High renewable energy penetration profoundly increases the diversity of operating statuses for the power system. Therefore, massive operating scenarios need to be considered in transmission expansion planning (TEP) to fully reflect the impact of renewable energy on power system operation. Usually, representative scenarios need to be selected to reduce the computational burden of TEP. However, the impact

The appearance of the flexible behavior of end-users based on demand response programs makes the power distribution grids more active. Thus, electricity market participants in the bottom layer of the power system, wish to be involved in the decision-making process related to local energy management problems, increasing the efficiency of the energy trade in distribution networks. This paper proposes

Successful trading in electricity markets relies on the market actor's ability to accurately forecast the electricity price. The fundamental electricity price models use market information, provided by various price drivers, including the residual that contains a risk premium. In the past, researchers investigating risk premium focused primarily on daily spot price levels, ignoring the intraday information

One major difficulty in transmission expansion planning is selecting the representative scenarios to use to evaluate candidate transmission networks. The variability in demand and renewable generation makes the inclusion of several scenarios critical when calculating reliability and cost, but including too many scenarios in an optimization is computationally intractable. To reduce the number of representative

In this work, we develop a polynomial-chaos-expa- nsion (PCE)-based approach for decentralized dynamic parameter estimation through Bayesian inference. Using this approach, the non-Gaussian distribution of the inverted parameters is obtained. More specifically, we first represent the decentralized generator model with the PCE-based surrogate. This surrogate allows us to efficiently evaluate the time-consuming

Modern grid codes demand the integration of voltage support capability with photo-voltaic (PV) generators to ensure a secure operation of power systems. On the other hand, short-term voltage instability (STVI) of distribution networks (DNs) is one of the key issues to be addressed. It can occur due to high proportion of induction motor loads. However, the existing literature lacks a thorough analysis

The paper focuses on the day-ahead operational planning of a grid-connected local energy community (LEC) consisting of an internal low-voltage network and several prosumers including generation units, battery storage systems, and local loads. In order to preserve, as much as possible, the confidentiality of the features of prosumers’ equipment and the production and load forecasts, the problem is addressed

This paper proposes a comprehensive load flow algorithm for balanced and unbalanced distribution systems considering the effect of a multi-grounded neutral conductor. The method is based on the implicit Z BUS method presenting fast convergence and robustness regardless of the R / X ratio of the lines. Its distinct feature is its ability to handle all network configurations, including highly meshed

This paper details a nonlinear Sliding Mode Control (SMC) based Sub-Synchronous Resonance (SSR) mitigation method for Doubly Fed Induction Generator (DFIG) based wind turbines interconnected to series compensated transmission systems. The proposed method is used to control the rotor side converter to mitigate SSR while ensuring decoupled torque and reactive power control ability of the DFIG is maintained

This paper develops a model-free approach to recover the missing points in streaming synchrophasor measurements obtained in nonlinear dynamical systems. It can accurately recover simultaneous and consecutive data losses across all channels for some time consecutively without modeling the nonlinear dynamics at all. The idea is to lift the nonlinear system to an infinite-dimensional linear dynamical

The rapid expansion of wind power has triggered significant wind curtailment because the power system lacks flexibility to deal with the uncertainty and variability of wind power. The operational flexibility of coal-fired power plants is limited by the minimum stable firing rate in the boiler. Steam extraction and thermal energy storage could enable power output adjustment without changing the firing

The paper introduces a robust method to detect random errors and cyber-attacks targeting alternating current (AC) dynamic state estimation through false data injection. The dynamic state estimator uses measurements that are delivered at a high reporting rate from synchrophasors or phasor measurement units (PMUs). A statistical outlier detection algorithm using the S-estimator is implemented on successive

A torque limit-based (TLB) method was proposed in literature in order to emulate inertial response of variable speed wind turbines (VSWTs). In this paper, this conventional TLB scheme is firstly modified by considering a finite ramp rate for inertial power of the VSWT. It is exposed that the maximum values of the VSWT's inertial power and kinetic energy released by its rotor have a non-linear relationship

In this paper, novel models for electronically coupled distributed energy resources (ECDERs) for online fault calculations of large-scale systems are proposed. ECDERs have different fault responses than traditional synchronous and induction (AC) machines, and generally accepted models for these emerging DERs do not exist. The deployment of ECDERs is constantly increasing worldwide and there is an urgent

The single imbalance pricing is an emerging mechanism in European electricity markets where all positive and negative imbalances are settled at a unique price. This real-time scheme thereby stimulates market participants to deviate from their schedule to restore the power system balance. However, exploiting this market opportunity is very risky due to the extreme volatility of the real-time power system

With ever increasing penetration of inverter-interfaced generators and consequent reduction in available inertial reserve, traditional allowable delay in the provision of the primary frequency reserve will threaten the security of the future grids. However, droop control with fast-enough inertia-less generators can limit the post-contingency frequency excursion. To conform with the fast-enough reserve

Over the last years, extreme weather events have caused extensive damages in power systems, leaving millions of customers without electricity and therefore highlighting the necessity to enhance power system resilience. This paper proposes a resilience constrained day-ahead unit commitment framework for increasing resiliency of a power system exposed to an extreme weather event. The weather-dependent

Non-technical losses (NTL) in electricity utilities are responsible for major revenue losses. In this paper, we propose a novel end-to-end solution to self-learn the features for detecting anomalies and frauds in smart meters using a hybrid deep neural network. The network is fed with simple raw data, removing the need of handcrafted feature engineering. The proposed architecture consists of a long

This paper introduces an alternative description of autonomous dynamical systems as a sum of individual vector fields. This structure of a dynamical system gives us the opportunity to construct individual Lyapunov-like functions to certify stability of an equilibrium point. A theorem on individual functions is developed in a quadratic form to maintain computational efficiency. As a corollary to the

The enhancement of economic sustainability and the reduction of GHG emissions in most of the small isolated regions strongly depends on reducing their use of imported fossil fuels. To evaluate the effectiveness of interconnecting small islands in promoting renewable penetration levels increase and cost reductions, this work proposes a multiyear expansion-planning optimization model for the Azores archipelago

Electrical power generation, transmission and distribution systems are often simulated through the single-phase equivalent model by assuming the presence of only the positive sequence in the real system. The well known power flow ( pf ) analysis is typically used to determine the steady state solution of these single-phase models. After the pf solution was determined, other elements, such as for example

In this paper, a compartmentalization strategy is proposed for the economic operation of a hybrid AC/DC microgrid. The hybrid AC/DC microgrid will be compartmentalized into several independently controlled and coordinated AC and DC nanogrids. Accordingly, the optimal economic operation of the microgrid consists of two segments, including the optimal power sharing among local DERs in individual nanogrids

This paper investigates the impact of synchrophasor estimation algorithms in Under-Frequency Load-Shedding (UFLS) and Load-Restoration (LR) schemes, relying on frequency and Rate-of-Change-of-Frequency (ROCOF) measurements produced by Phasor Measurement Units (PMUs). We compare two consolidated window-based synchrophasor estimation algorithms, as representative approaches based on static and dynamic

Distributed algorithms have been proposed as options to scale control propositions to the massive number of intelligent energy devices, sub-systems, and distributed energy resources being integrated into the electricity grid. Distributed algorithms rely on the communication network for exchanging information. Failures in the communication network can jeopardize distributed decision-making and in the

Recent changes in the fuel mix for electricity generation and, in particular, the increase in Gas-Fueled Power Plants (GFPP), have created significant interdependencies between the electrical power and natural gas transmission systems. However, despite their physical and economic couplings, these networks are still operated independently, with asynchronous market mechanisms. This mode of operation

Modern power grids incorporate renewable energy at an increased pace, placing greater stress on the power grid equipment and shifting their operational conditions towards their limits. As a result, failures of any network component, such as a transmission line or power generator, can be critical to the overall grid operation. The security constrained optimal power flow (SCOPF) aims for the long term

Short-term load forecasting has been playing an increasingly important role in electric power systems. Effective forecasting of the future electricity demand, however, is difficult in view of the complicated effects on load by a variety of factors. A hybrid method based support vector regression (SVR) with meteorological factors and electricity price is proposed to address such problem. First, the

This paper focuses on the interchange and generation scheduling problem of multi-area power systems, where decentralized decision procedure is preferred and the uncertainties of nodal injections should be considered. The problem is formulated as a multi-area robust security constrained unit commitment model, with a novel uncertainty set specified by the variance of system net load. We prove that such

Two spectral discretization methods based on linear multistep and implicit Runge-Kutta discretization of infinitesimal generator (IGD-LMS/IRK) are presented in this paper for eigen-analysis of large delayed cyber-physical power system (DCPPS) with large time delays. First, the whole delay interval is partitioned into several sub-intervals by time delays in the system. The piecewise partitioning allows

Truck-mounted mobile emergency resources (MERs) play a significant role in microgrid formation and regulation for power system resilience enhancement. This paper proposes a distributed fixed-time secondary control (DFSC) scheme to regulate the frequency and active power sharing in islanded microgrids with MERs. The proposed DFSC scheme is designed based on a general directed communication graph which

An adaptive decentralized control scheme is proposed for real-time control of oscillatory dynamics and overall stability improvement of an interconnected power system. A standard framework of continuous-time (CT) infinite-horizon optimal control paradigm is defined and an extended online actor-critic (AC) algorithm based on policy iteration is used for its solution. The AC structure uses neural networks

Although extreme natural disasters have occurred all over the world throughout history, power systems planners do not usually recognize them within network investment methodologies. Moreover, planners had historically focused on reliability approaches based on average (rather than risk) performance indicators, undermining the effects of high impact and low probability events on investment decisions

This paper proposes a homotopy-based method for efficiently computing and precisely determining controlling unstable equilibrium points (CUEPs) in transient stability analysis and screening using direct methods. The proposed method is intended to overcome potential numerical convergence problems associated with computing CUEPs. These convergence problems are mostly due to irregularities in the region

Increasingly frequent severe weather events in recent years threaten the security of power systems and result in major power outages throughout the world. The development of reasonable power system restoration (PSR) solutions is therefore urgently needed to speed up the recovery of the power supply while at the same time steering clear of vulnerable and risky equipment. This paper aims to develop a

For decades, power system stabilizers paired with high initial response automatic voltage regulators have served as an effective means of meeting sometimes conflicting system stability requirements. Driven primarily by increases in power electronically-coupled generation and load, the dynamics of large-scale power systems are rapidly changing. Electric grids are losing inertia and traditional sources

Analytical methods for evaluating the reliability of simple and radial distribution networks have been well established. Since these analytical methods cannot consider post-fault load transfer between feeders, the reliability indices are significantly underestimated for mesh-constructed distribution networks. To accommodate various application scenarios, Monte-Carlo simulations are widely used for

Power system state estimation is subject to false data injection (FDI) attacks, because of the integration of advanced computation and communication techniques in power systems. By coordinately tampering the readings of meters, FDI attacks can bypass bad data detectors and stealthily mislead the results of state estimation. In this paper, we propose a joint admittance perturbation and meter protection

Identifying network dynamic topology changes with limited measurement data is a primary challenge for power distribution system analysis. Existing methods require the measurement of the nodal voltage (both amplitudes and phase angles) of a majority of nodes, which means that large-scale installation of advanced monitors is necessary. In this paper, a distribution network dynamic topology awareness