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This letter introduces a novel approach to prevent ice formation on transmission lines during ice storms. First, weather forecast is used to calculate minimum currents needed to raise the conductor temperature above the freezing point. Then, a preventive unit commitment model is developed to enforce those minimum limits. Simulation studies are conducted on the three-area RTS-96 system. The results

The robust optimization based dynamic economic dispatch (DED) model has been extensively studied to address uncertainties of net loads induced by renewable energy resource variabilities and demand fluctuations. However, the robust DED model is computationally expensive, when solved by the column-and-constraint generation (CCG) approach that iterates between a master problem and a max-min subproblem

This letter presents a robust generalized correlation approach for monitoring of power system oscillatory modes. Due to the non-Gaussian nature of measurement noise, and presence of impulsive outliers, the wide-sense stationarity assumption of power system measurement data is violated even under ambient conditions thus limiting the effectiveness of conventional autocorrelation based approaches in mode

Distributed generators performing black start to form isolated microgrids offer a flexible and resilient solution to service restoration in distribution systems. Employing the dynamic microgrid concept, distributed generators can form isolated microgrids by changing their physical boundaries through smart switches and conventional circuit breakers. However, the flexibility of distributed generators

The synchronization instability in the presence of a fault is a main issue for the dynamic behavior and control of grid-feeding converters. In the literature, the synchronization stability assessment is carried out considering the dynamics of Phase-Locked Loops (PLL) but the transients of converter currents are neglected. The letter shows that such a simplification leads to inaccuracies and, thus,

This paper introduces quantum computing as a necessary and viable tool in addressing the needs of a modernized power grid. The application of quantum computing in enhancing physical security of the grid – an increasingly difficult problem to solve– is investigated. A comparative study based on mathematically proven computing performance measures shows the merits of the proposed method and further unveils

In this discussion, an analysis that the authors of the above name paper used the probable precision index ρ and made it to be greater than or equal to ρmin upon exit of forming clusters. This leads to the formation of clusters which are nearby to each order. In other words, border of one cluster is near to the border of other cluster. Indeed, any minor change in cluster data will lead to the major

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High-level penetration of intermittent renewable energy sources has introduced significant uncertainties and variabilities into modern power systems. In order to rapidly and economically respond to the changes in power system operating state, this letter proposes a real-time optimal power flow (RT-OPF) approach using Lagrangian -based deep reinforcement learning (DRL) in continuous action domain. A

In this paper, detectability analysis is studied and extended to guide selection of measurements for the dynamic state estimation (DSE) of a synchronous machine. To make sure that the DSE converges, past studies suggested that enough measurements must be available to make the system observable. In this paper, the convergence condition is relaxed via detectability analysis to reduce the number of required

This letter presents an analytical closed-form expression that quantifies the contributions of nodal active- and reactive-power injections to total loss in a power system operating at sinusoidal steady state. We term this as the loss divider , since it is derived by leveraging the ubiquitous current divider law. The proposed loss divider innately embeds the dependence of system loss on both the network

Radiality constraints are involved in both distribution system restoration and reconfiguration problems. However, a set of widely used radiality constraints, i.e., the spanning tree (ST) constraints, has its limitations which have not been well recognized. In this letter, the limitation of the ST constraints is analyzed and an effective set of constraints, referred to as the single-commodity flow constraints

In energy-only electricity markets, the operational reserve demand curve is a scarcity pricing mechanism adopted to address the shortage of reserves and incentivize the generators. It is constructed based on the assumption of the normality of loss of load probability, which is estimated from reserve error data. In this Letter, the historical record of reserve error is collected and analyzed to test

In this letter, a new model to represent power system inertia distribution is derived first. Then, a specific online identification method is proposed to identify parameters of the model under normal operating conditions so that the system inertia distribution can be tracked in real-time. The effectiveness of the proposed model and identification method is validated in the IEEE 39-bus system.

This letter proposes an optimization-free technique to estimate the parameters of voltage dependent loads through the measurements of only the load active and reactive power consumption and frequency deviations at the load bus. The technique is shown to be a relevant consequence of the dependency of power flow equations on the bus voltage phase angles. The WSCC 9-bus and the IEEE 14-bus systems serve

In the literature, Bode plots and Nyquist diagrams are used extensively in stability analysis for admittance-based models. In this letter, we demonstrate that eigenvalues obtained from the total admittance lead to accurate prediction of stability while Bode plots and Nyquist diagrams show limitations. A voltage source converter with weak grid interconnection is used as an illustrative example to demonstrate

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This paper proposes a multi-agent deep reinforcement learning-based approach for distribution system voltage regulation with high penetration of photovoltaics (PVs). The designed agents can learn the coordinated control strategies from historical data through the counter-training of local policy networks and centric critic networks. The learned strategies allow us to perform online coordinated control

The implicit $\text{Z}_\text{bus}$ Gauss algorithm is revisited to empower the power flow analysis for microgrids with hierarchical control and frequency- and voltage- dependent loads. The contributions of the revisited Gauss (GRev) algorithm include: 1) a droop-based implicit $\text{Z}_\text{bus}$ Gauss microgrid algorithm which automatically incorporates the distributed energy resources (DERs)/load

This letter addresses the initialization problem of power systems modeled as (SDAEs) and proposes a novel efficient initialization method. The method involves finding the co-variance matrix for the system state variables and initializing the stochastic state variables of the system randomly based on their probability distribution. Deterministic states and algebraic variables are then initialized based

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Power distribution grids are structurally operated radially, such that energized lines form a collection of trees with a substation at the root of each tree. The operational topology may change from time to time; however, tracking these changes, even though important for the distribution grid operation and control, is hindered by limited real-time monitoring. This paper develops a learning framework

Implementing state estimation in low and mediumvoltage power distribution is still challenging given the scale of many networks and the reliance of traditional methods on a large number of measurements. This paper proposes a method to improve voltage predictions in real-time by leveraging a limited set of real-time measurements. The method relies on Bayesian estimation formulated as a linear least

Near-optimal unit commitment (UC) scheduling is a practical reality in wholesale electricity markets. This paper revisits previous work that has found that minor differences in cost among near-optimal schedules can result in a large redistribution of market payments (i.e., changes in generator profits and consumer surplus). It has been believed that this instability is unavoidable, but previous studies

This paper develops a systematic approach to derive the optimal bidding strategy for prosumers in a distribution-level energy market. In particular, the optimal bidding curve describes the cost-minimizing buying/selling strategy of prosumers and is composed of a limited number of linear segments. As such, only a small number of end points of the linear segments are sufficient to exactly describe the

This paper presents a new method of instability detection and subsequent stabilization of the power system network using a proposed multi-shot remedial action scheme (RAS) that can extemporaneously detect critical generators based on the dynamic states of generator computed from the terminal phasor measurement units. The instability detector is a moving window classifier that predicts impending instability

An integrated energy system (IES) represents coordinated operations of constrained natural gas (NG), electric power, and thermal systems in three distinctly different time scales. Microturbines (MTs) are increasingly utilized in IES as suppliers of combined cooling, heating and power (CCHP) units, which optimize the delivery and the usage of interdependent NG, electric power, and thermal energy sectors

This paper focuses on transactive energy management in local energy communities and proposes a coalitional game model which considers the presence and utilization of flexible loads and the power output uncertainties from renewable energy sources. The superadditivity and balancedness of the proposed game model are proved rigorously by demonstrating that a nucleolus-based solution leads to a stable and

Earlier works have reported the emerging fault current limiter (FCL) segmentation technique to mitigate concurrent commutation failure (CF) under ac faults in multi-infeed LCC-HVDC systems. However, the FCL's parameter is determined by the electromagnetic transient (EMT) simulation based method, which will lead to enormous workload and long computation time. Moreover, the subsequent CF after ac faults

A line loss approximation via parametrization is developed to improve performance of the simplified Baran and Wu DistFlow method, while maintaining a linear set of equations. The approach is evaluated on thousands of training feeders that are created to determine a numerically optimal setting for the parameterization. Feeders are generated using recent advances in synthetic network test case generation

Parameter identification facilitates the improvement of the accuracy of power system simulation. However, for complex models of electrical equipment, it is impossible to simultaneously identify all the parameters. Inaccurate values of the nontarget parameters (NTPs) will affect the identification accuracy of the target parameters (TPs). However, no suitable methods are available in the parameter identification

Fully electrified ships, which is known as the “all-electric ships (AESs)”, have the potentials to bring great economic /environmental benefits. To further improve the energy efficiency of AESs, PV generations are gradually integrated, which introduces uncertainties to the AES operation. However, current researches mostly focus on sizing problem whereas rarely concern the operation. In this perspective

This paper presents a parameter estimation technique for a variable-speed wind turbine with permanent magnet synchronous generator and back-to-back voltage source converter. The proposed technique applies the cubature Kalman filter for the joint estimation of the system dynamic state and a modified set of parameters from which the original model parameters can be algebraically recovered. To the authors

Wide-area data and algorithms in large power systems are creating new opportunities for implementation of measurement-based dynamic load modeling techniques. These techniques improve the accuracy of dynamic load models, which are an integral part of transient stability analysis. Measurement-based load modeling techniques commonly assume response error is correlated to system or model accuracy. Response

This paper presents a novel distributed voltage control method for multi-terminal direct current (MTDC) systems based on the average consensus algorithm. The proposed method combines the idea of secondary integral voltage control and regulator synchronization problem. It realizes adjustable tradeoff between two conflicting control objectives, that is, voltage regulation and power sharing. The proposed

This paper proposes a methodology for advanced demand side management (DSM) in the distribution network (DN), catering at the same time for the requirements of the network operator, transmission or distribution, the available flexibility of the demand side, and the preservation of network performance. The basic premise of the study is that the distribution network operator is providing flexibility

This paper proposes a temporal decomposition strategy to reduce the computation time of security-constrained unit commitment (SCUC). The novelty of this paper is twofold. The scheduling horizon is decomposed into multiple subhorizons. The concept of coupling intervals is introduced, and a set of auxiliary counting variables and logical expressions along with their equivalent linear models are formulated

Invisible units mainly refer to small-scale units that are not monitored by, and thus are not visible to utilities. Integration of these invisible units into power systems does significantly affect the way in which a distribution grid is planned and operated. This paper, based on random matrix theory (RMT), proposes a statistical, data-driven framework to handle the massive grid data, in contrast to

In the analysis of cascading outages and blackouts in power systems, risky cascading fault chains should be accurately identified in order to do further block or alleviate blackouts. However, the huge computational burden makes online analysis difficult. In this paper, an online search method for representative risky fault chains based on reinforcement learning and knowledge transfer is proposed. This

This paper presents a new methodology to exploit consumers’ flexibility for the provision of ancillary services (AS) in the smart grid era. The proposed framework offers a control-based approach that adopts price signalsas the economic driver to modulate consumers’ response. In this framework, various system operators broadcast price signals independently to fulfil their AS requirements. Appropriate

Accurate and reliable low-voltage load forecasting is critical to optimal operation and control of distribution network and smart grid. However, compared to traditional regional load forecasting at high-voltage level, it faces tough challenges due to the inherent high uncertainty of the low-capacity load and distributed renewable energy integrated in the demand side. This paper proposes a novel hybrid

Renewable energy will become a normal energy source and will be required to participate in the market. The renewable portfolio standards (RPS) together with tradable green certificates (TGC) are considered as an appropriate market mechanism to help recover renewable energy investments. The strategic offering behaviors of renewable energy should be carefully studied, especially with the introduction

Poorly damped inter-area modes of oscillations represent a major concern to power system operation since they detain the power transfer capability of transmission networks. This situation becomes more stringent as the tie-lines are heavily stressed and/or large amounts of renewable energy resources are installed. To overcome this issue, a detailed mathematical model is proposed in this paper to reduce

A robust observer for performing power system dynamic state estimation (DSE) of a synchronous generator is proposed. The observer is developed using the concept of $\mathcal {L}_{\infty }$ stability for uncertain, nonlinear dynamic generator models. We use this concept to (i) design a simple, scalable, and robust dynamic state estimator and (ii) obtain a performance guarantee on the state estimation

The work reported in this paper aims at developing an algorithm for system operators to solve a robust security-constrained AC optimal power flow (R-SC-ACOPF) problem, which also optimizes the settings of discrete controllers including load tap changers (LTCs) and shunt capacitor banks (SCBs). An iterative algorithm involving a master problem and a number of sub-problems is proposed. The master problem

In this paper, a new theory-based dynamic method for computing unstable equilibrium points is proposed. This dynamic method is a combination of a dynamic transformation method and a trajectory-unified method for the computation of unstable equilibrium points (UEPs) of power system models. The transformation method converts a UEP into a stable equilibrium point (SEP) to expand its convergence region

We study market equilibria that are achieved by strategic firms that participate in electricity and natural gas markets. Strategic firms submit their offers and bids to both markets with the aim of maximizing profit or utility and we consider firms that can include a combination of electricity and natural gas supply and demand. The strategic actions of these firms are represented by upper-level problems