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Synthetic power systems that imitate functional and statistical characteristics of the actual grid have been developed to promote researchers’ access to public system models. Developing time series to represent different operating conditions of these synthetic systems will expand the potential of synthetic power systems applications. This paper proposes a methodology to create synthetic time series of bus-level load using publicly available data. Comprehensive validation metrics are provided to assure that the quality of synthetic time series data is sufficiently realistic. This paper also includes an example application in which the methodology is used to construct load scenarios for a 10,000-bus synthetic case. [ABSTRACT FROM AUTHOR]

This paper develops a systematic framework for analyzing how low frequency forced oscillations propagate in electric power systems. Using this framework, the paper shows how to mathematically justify the so-called Dissipating Energy Flow (DEF) forced oscillation source location technique. The DEF's specific deficiencies are pinpointed, and its underlying energy function is analyzed via incremental passivity theory. This analysis is then used to prove that there exists no passivity transformation (i.e. quadratic energy function) which can simultaneously render all components of a lossy classical power system passive. The paper goes on to develop a simulation-free algorithm for predicting the performance of the DEF method in a generalized power system, and it analyzes the passivity of three non-classical load and generation components. The proposed propagation framework and performance algorithm are both tested and illustrated on the IEEE 39-bus New England system and the WECC 179-bus system. [ABSTRACT FROM AUTHOR]

The renewable energy-based hydrogen production can lead to the integrated electric power and hydrogen system (IPHS) and offer a pathway to a sustainable energy utilization. Hydrogen is mainly transported via hydrogen tube trailers (HTs), making the hydrogen energy system (HES) operation quite different from those of other energy technologies. This paper proposes an optimal IPHS operation strategy which utilizes HT for transportation. The proposed strategy coordinates hydrogen generation, transportation, and storage stages considering constrained operations of electric power system (EPS), transportation system, and variable renewable energy. The proposed solution method is based on the alternating direction method of multipliers (ADMM) in which HES and EPS constraints are managed individually and the respective solutions are coordinated accordingly. The case studies using the modified IEEE-RTS79 have verified the validity of the proposed IPHS model and its solution method and confirmed the necessity of considering HES in enhancing the EPS operation. The synergies between EPS and HES are studied via numerical examples and the impact of the flexibilities in hydrogen generation, transportation and demand are highlighted. [ABSTRACT FROM AUTHOR]

In this paper, a methodology to solve the optimal reactive power dispatch (ORPD) in electric power systems (EPS), considering discrete controllers, is proposed. Discrete controllers, such as the tap position of on-load tap changing (OLTC) transformers and switchable reactive shunt compensation, are optimized by the proposed method. A semidefinite relaxation (SDR) of the ORPD problem and a branch-and-bound (B&B) algorithm have been fully deployed. A new formulation is presented for the OLTC transformers to obtain a connected structure of the semidefinite programming (SDP) matrices. The customized B&B algorithm deals with the discrete nature of the binary control variables. Moreover, in order to enhance the convexification, valid inequalities called lifted nonlinear cuts (NLC) are implemented in the SDR. Additionally, a chordal decomposition technique is used to improve the computational performance. Finally, the B&B algorithm is used to solve the mixed-integer semidefinite programming problem. Several benchmarks have been used to show the accuracy and scalability of the proposed method, and convergence analysis shows that near-global optimal solutions are generated with small relaxation gaps. [ABSTRACT FROM AUTHOR]

This paper intends to address the dynamic repair scheduling of electric power transmission systems based on look-ahead strategy approximation. The objective is to minimize system functionality loss during the restoration stage after disruptive events. A series of decisions regarding which damaged component to be repaired has to be made successively considering currently available information of repair time and its uncertainty in the future. To achieve this goal, the dynamic repair scheduling problem is represented as a stochastic Markovian decision process (MDP). To overcome the computational complexity of MDP derived from exponentially growing state space, the cost-to-go function is approximated by a look-ahead strategy based on repair importance ordering. Stage-dependent coefficients are used to balance the approximated functionality loss at different decision stages. The tradeoff between the efficiency and optimality can be achieved by adjusting the look-ahead depth and the updating policy of look-ahead strategy. The IEEE-14 and 118-bus systems were used for performance evaluation of the proposed method and comparison with various approaches. The results show that it can produce decisions close to the best-known solutions within small amount of time. [ABSTRACT FROM AUTHOR]

Power system stability is widely assessed based on tools that rely on the representation of voltages and currents through quasi-static phasor calculus, implying that the network itself and the synchronous machine stators are modeled by algebraic equations. Accordingly, the associated fast transients are neglected, assuming those decay rapidly. However, with the increasing penetration of converter interfaced generation in power systems, the reliance on quasi-static phasor calculus is to be questioned. In this paper, the validity of quasi-static phasor calculus models is verified, and dynamic phasor calculus is considered as the alternative. A methodology to systematically compare quasi-static and dynamic phasor calculus is developed. It includes frequency response, modal, and sensitivity analyses. The methodology is applied to an IEEE test network considering penetrations of converter interfaced generation of up to 100%. The models are implemented in MATLAB. The H-infinity norm is proposed as an indicator to identify differences in the applicability of the models. The results show that the quasi-static phasor calculus is suitable for stability analysis only if low bandwidths of converter controls are given. Dynamic phasor calculus instead is suitable and applicable to generic stability studies of integrated power electric and electronic systems with high penetration of renewables. [ABSTRACT FROM AUTHOR]

This paper summarizes the technical activities of the Task Force on Power System Dynamic State and Parameter Estimation. This Task Force was established by the IEEE Working Group on State Estimation Algorithms to investigate the added benefits of dynamic state and parameter estimation for the enhancement of the reliability, security, and resilience of electric power systems. The motivations and engineering values of dynamic state estimation (DSE) are discussed in detail. Then, a set of potential applications that will rely on DSE is presented and discussed. Furthermore, a unified framework is proposed to clarify the important concepts related to DSE, forecasting-aided state estimation, tracking state estimation, and static state estimation. An overview of the current progress in DSE and dynamic parameter estimation is provided. The paper also provides future research needs and directions for the power engineering community. [ABSTRACT FROM AUTHOR]

Composite power system reliability evaluation is computationally time-consuming because the optimal power flow (OPF) with the least load curtailment is calculated for a large number of samples. Most current studies of probabilistic simulation methods focus on sampling techniques to improve the sampling efficiency and decrease the calculations of the OPF. This paper proposes a fast reliability evaluation method that accelerates the calculation of the OPF using multi-parametric linear programming (MPLP). In this paper, the sampled transmission line statuses are considered by the transmission line status dictionary (TLSD). We match the line status of each sample with the scenarios in the TLSD. For matching samples, the generation status and the sampled load are treated as MPLP parameters of the DC-OPF evaluation model. A dynamic learning algorithm is applied to solve the MPLP problem. Case studies are conducted on both IEEE Reliability Test Systems and a provincial power system in China. The results show that the proposed method improves the evaluation efficiency by 23–30 times compared with the normal DC-OPF-based model. [ABSTRACT FROM AUTHOR]

Electromechanical modes are inherent to any interconnected power systems which provide a measure of the small-signal stability margin of the system. A number of algorithms have been developed for the estimation of these modes using synchrophasor measurements. However, most of these algorithms are not designed to operate in the presence of forced oscillations (FO). These FOs are results of periodic rogue input driving the system. When FOs are present, estimates of system modes can be biased depending on the frequency and the amplitude of the FOs. To tackle this problem, a new algorithm is proposed in this paper to estimate system modes in the presence of FOs. In the proposed method, the over-determined modified Yule–Walker method which is used to estimate autoregressive coefficients of an autoregressive moving average (ARMA) signal model is extended to an ARMA with exogenous input (ARMAX) model that incorporates the presence of FOs. Two versions of the proposed method are included in this paper based on the requirement of the information of the duration of FOs in the signal. Results obtained by implementing the proposed algorithm on simulated data and real-world data validate the effectiveness of both versions of the proposed method. [ABSTRACT FROM AUTHOR]

This paper presents a new approach for reliability evaluation of composite power systems by combining Monte Carlo simulation and multi label k-nearest neighbor (MLKNN) algorithm. MLKNN is a classification technique in which target vector of each instance is assigned into multiple classes. In this paper, MLKNN is used to classify states (failure or success at system or bus level) of a complete power system without requiring optimal power flow (OPF) analysis, except in the training phase. As a result, the computational burden to perform OPF is reduced dramatically. For illustration, the proposed method is applied to the IEEE 30 BUS Test System and IEEE Reliability Test System. The obtained results from various case studies demonstrate that MLKNN based reliability evaluation provides promising results in both classification accuracy and computation time in evaluating the composite power system reliability. [ABSTRACT FROM AUTHOR]

The use of phasor measurement units (PMU) has enabled monitoring the power system dynamics online. There are many PMUs installed, which will give a comprehensive view in real or near real time of the entire system. In general, there are many operating conditions of power systems, which requires different tools to analyze the synchrophasor data provided by PMUs. Changes in power system monitoring must be detected as quickly as possible, so that the system operators can choose a different tool for data analysis. Therefore, in this paper, changes in the working conditions of the power system are detected using a subspace state-space based change-point detection method. The detection algorithm proposed in this paper is sequential detection, which aims at both detection accuracy and detection speed. We have tested our proposed algorithm to detect many various kinds of changes in power system operations and verified that the algorithm is able to detect changes successfully, including very small ones in the system such as the low-amplitude forced oscillations buried in the system's ambient conditions in a real-time manner. The algorithm is tested in a set of real-world data to show its practical usage in large systems with imperfect data. [ABSTRACT FROM AUTHOR]

Under the deregulated environment, electric utility companies have been encouraged to ensure maximum system reliability through the employment of cost-effective long-term asset management strategies. Previously, the age based Weibull distribution has been used vastly for modeling and forecasting aging failures. However, this model is only based on asset age and does not consider additional information such as asset infant mortality period and equipment energization delay. Some works on modifying Weibull distribution functions to model bathtub-shaped failure rate function can be practically difficult due to model complexity and inexplicit parameters. To improve the existing methods, this paper proposes four modified Weibull distribution models with straightforward physical meanings specific to power system applications. Furthermore, this paper proposes a novel method to effectively evaluate different Weibull distribution models and select the suitable model(s). More importantly, if more than one suitable model exists, these models can be mathematically combined as a joint forecast model, which could provide better accuracy to forecast future asset reliability. Finally, the proposed approach was applied to a Canadian utility company for the reliability forecast of electromechanical relays and distribution poles to demonstrate its practicality and usefulness. [ABSTRACT FROM AUTHOR]

This paper is devoted to the description of a new approach for large-scale electric power systems (EPS) simulation, so-called hybrid simulation approach. The design and research of EPS require solving a large number of non-trivial tasks. Due to the well-known EPS specificity, mathematical modeling is the only way to proceed. According to the hybrid approach, several simulation techniques (analogue, digital, and physical) are used to achieve the best results. An analogue part provides the elimination of methodological integration error, which appears in a case of numerical methods usage. A digital part allows the realization of control and parameter changing algorithms on software level. In a physical part, the connection and switching of modeled elements are provided in a way as in real EPS. In addition, the paper presents hardware features of the simulator—hybrid real-time power system simulator (HRTSim), which is an alternative to the digital simulators currently used. The important part of this paper is the result of comparative analysis of transient processes oscillograms obtained by HRTSim and real disturbance recorders in Tomsk region power system, as well as HRTSim and real-time digital simulator. [ABSTRACT FROM AUTHOR]

The co-optimization of security-constrained unit commitment and dispatchable transmission network is a large-scale and computationally complex optimization problem that brings big challenges for the traditional centralized and/or master–slave based decomposition approaches. This paper proposes a fully parallel approach to achieve an efficient and fast solution while considering post-contingency corrective actions. In this paper, the original co-optimization problem is decomposed into six major solution modules for unit commitment, optimal power flow, and transmission switching in base case and contingencies, respectively. Moreover, each major solution module is further decomposed by unit, period, dispatchable line, and/or contingency to make the proposed approach favorable in a fully parallel computing environment. The effectiveness and efficiency of the proposed fully parallel approach are justified using numerical cases on a high-performance computing (HPC) platform. [ABSTRACT FROM AUTHOR]

A continuous Online Monitoring System (OMS) for power system stability based on Phasor Measurements (PMU measurements) at all the generator buses is proposed in this paper. Unlike the state-of-the-art methods, the proposed OMS does not require information about fault clearance. This paper proposes a convolutional neural network, whose input is the heatmap representation of the measurements, for instability prediction. Through extensive simulations on standard IEEE 118-bus and IEEE 145-bus systems, the effectiveness of the proposed OMS is demonstrated under varying loading conditions, fault scenarios, topology changes, and generator parameter variations. Two different methods are also proposed to identify the set of critical generators that are most impacted in the unstable cases. [ABSTRACT FROM AUTHOR]

Load characteristics have substantial influence on the voltage stability of power systems. The self-restorative characteristic and stalling of induction motor loads can deteriorate the voltage stability, so it is necessary to develop accurate and efficient dynamic analysis methods for voltage stability analysis of systems with induction motor loads. In this paper, a set of methods based on holomorphic embedding is proposed, which is able to solve steady states and dynamics of a power system with induction motors. The paper is the first work that applies holomorphic embedding to dynamic problems of power systems. The test cases on the IEEE 14-bus system, the NPCC 140-bus system, and the Polish 2383-bus system verify both accuracy and efficiency of the proposed methods. [ABSTRACT FROM AUTHOR]

This paper deals with the impact of linear approximations for the unknown nonconvex confidence region of chance-constrained ac optimal power flow problems. Such approximations are required for the formulation of tractable chance constraints. In this context, we introduce the first formulation of a chance-constrained second-order cone (SOC) OPF. The proposed formulation provides convergence guarantees due to its convexity, while it demonstrates high computational efficiency. Combined with an ac feasibility recovery, it is able to identify better solutions than chance-constrained nonconvex ac-OPF formulations. To the best of our knowledge, this paper is the first to perform a rigorous analysis of the ac feasibility recovery procedures for robust SOC-OPF problems. We identify the issues that arise from the linear approximations, and by using a reformulation of the quadratic chance constraints, we introduce new parameters able to reshape the approximation of the confidence region. We demonstrate our method on the IEEE 118-bus system. [ABSTRACT FROM AUTHOR]

High intermittency in today's renewable-rich distribution systems, and the prohibitive cost of upgrading the system infrastructure, has rendered voltage instability a real concern for heavily loaded systems. The voltage instability of distribution systems can spread to the corresponding transmission grid, as proven by real-life incidents. Recent advances in energy storage systems (ESSs), however, have offered a viable means of enhancing the reliability and robustness of power systems. In this paper, the optimal placement, sizing, and operation of ESS devices in wind-intensive distribution power systems are studied. The objectives of this paper are to minimize the ESS size (power and energy), required to ensure a desired voltage stability margin (VSM), and to minimize the reactive power loss and reactive power import from the upstream network. Wind uncertainty has been accounted for through a risk-based stochastic optimization framework. Besides, active network management (ANM) tools, such as the tap position of on-load tap changers, modelled by using a new method, and reactive power capabilities of both ESS devices and wind farms, are used as additional means to reduce the required ESS size. The results show that the required ESS significantly increases with increase in the desired VSM. Nevertheless, the increase can be considerably curtailed by using risk-based VS constraints and ANM tools. [ABSTRACT FROM AUTHOR]

In this paper, a new systematic method is proposed to analyze the system frequency in power systems under uncertain variability (UV). UV gradually increases in power systems, which originates from the renewable energy generation, random loads, frequency measurement, and communication channels, exerting noteworthy impacts on dynamic system frequency. The UV is modeled as a stochastic process in this paper. Then, the stochastic differential equations are used to describe the dynamic system frequency response (SFR) of a power system under UV, which is based on the SFR model. To assess system frequency dynamics under UV, an index of intra-range probability is put forward. Based on stochastic analysis theory, an analytic method is proposed to analyze the system frequency under UV, by which the intra-range probability can be analytically solved. Compared with Monte Carlo simulation in a typical SFR case and the Iceland electricity transmission network, the proposed method shows almost the same results using much less computation resource. Finally, insights for improving the SFR under UV are provided. The proposed method can be used to quickly verify whether the system frequency could withstand the UV and stay in the security range. [ABSTRACT FROM AUTHOR]

Time-domain simulation is the basis of dynamic security assessment for power systems. Traditionally, numerical integration methods are adopted by simulation software to solve nonlinear power system dynamics for any given contingency under a specific operating condition. An alternative simulation approach promising for online applications is to offline derive a semi-analytical solution (SAS) for power system differential equations and then online evaluate the SAS over consecutive time windows regarding the operating condition and contingency until the simulation result over a desired period is obtained. This paper proposes a general semi-analytical approach that derives and evaluates an SAS in the form of a power series in time to approximate the true solution. This paper provides an error-rate upper bound of the SAS for reliable use of adaptive time windows in evaluation of the SAS. To extend the semi-analytical approach for solving general power system differential-algebraic equations, this paper also proposes a dynamic bus method to efficiently link the SAS for dynamic components with the numerical solution of the network algebraic equations. Case studies on the New England 39-bus system and the Polish 2383-bus system test the performance of the proposed approach, compare it with other methods, and show the potentials of the proposed semi-analytical approach for online simulation. [ABSTRACT FROM AUTHOR]

This paper studies the optimal transmission switching (OTS) problem for power systems, where certain lines are fixed (uncontrollable) and the remaining ones are controllable via on/off switches. The goal is to identify a topology of the power grid that minimizes the cost of the system operation while satisfying the physical and operational constraints. Most of the existing methods for the problem are based on first converting the OTS into a mixed-integer linear program (MILP) or mixed-integer quadratic program (MIQP), and then iteratively solving a series of its convex relaxations. The performance of these methods depends heavily on the strength of the MILP or MIQP formulations. In this paper, it is shown that finding the strongest variable upper and lower bounds to be used in an MILP or MIQP formulation of the OTS based on the big- $M$ or McCormick inequalities is NP-hard. Furthermore, it is proven that unless $P=NP$ , there is no constant-factor approximation algorithm for constructing these variable bounds. Despite the inherent difficulty of obtaining the strongest bounds in general, a simple bound strengthening method is presented to strengthen the convex relaxation of the problem when there exists a connected spanning subnetwork of the system with fixed lines. With the proposed bound strengthening method, remarkable improvements in the runtime of the mixed-integer solvers and the optimality gaps of the solutions are achieved for medium- and large-scale real-world systems. [ABSTRACT FROM AUTHOR]

The integration of variable renewable energy (VRE) generation, i.e., wind power and solar photovoltaic, brings significant uncertainty for the power system operation. Different with VRE techniques, concentrating solar power (CSP) is an appealing renewable generation technology due to its dispatch ability through the use of thermal energy storage and is thus expected to play a significant role in high renewable energy penetrated power systems. In this paper, we propose a look-ahead stochastic unit commitment model to operate power systems with CSP under high renewable energy penetration. It has a three-stage structure. The first stage optimizes the operational decisions in a day-ahead framework based on forecasts; the second stage minimizes the expected generation cost for possible realizations in the real time; and the third stage accounts for look-ahead operation in future operating days. This paper has a dual purpose: first, exploring how CSP plants operate in high renewable penetrated power systems; and second, analyzing the benefits of CSP in accommodating VRE generation. A case study on a modified IEEE RTS-79 system with actual solar and wind power data is provided to validate the proposed method. [ABSTRACT FROM AUTHOR]

Most techniques for power system analysis model the grid by exact electrical circuits. For instance, in power flow study, state estimation, and voltage stability assessment, the use of admittance parameters (i.e., the nodal admittance matrix) and hybrid parameters is common. Moreover, network reduction techniques (e.g., Kron reduction) are often applied to decrease the size of large grid models (i.e., with hundreds or thousands of state variables), thereby alleviating the computational burden. However, researchers normally disregard the fact that the applicability of these methods is not generally guaranteed. In reality, the nodal admittance must satisfy certain properties in order for hybrid parameters to exist and Kron reduction to be feasible. Recently, this problem was solved for particular cases of monophase and balanced triphase grids. This paper investigates the general case of unbalanced polyphase grids. First, conditions determining the rank of the so-called compound nodal admittance matrix and its diagonal subblocks are deduced from the characteristics of the electrical components and the network graph. Second, the implications of these findings concerning the feasibility of Kron reduction and the existence of hybrid parameters are discussed. In this regard, this paper provides a rigorous theoretical foundation for various applications in power system analysis. [ABSTRACT FROM AUTHOR]

As the level of uncertain renewable capacity increases on power systems worldwide, industrial and academic researchers alike are seeking a scalable, transparent, and effective approach to unit commitment under uncertainty. This paper presents a statistical ranking methodology that allows adaptive robust stochastic unit commitment using a modular structure, with much-needed flexibility. Specifically, this paper describes a bus ranking methodology that identifies the most critical buses based on a worst-case metric. An important innovation is the ability to identify alternative metrics on which to rank the uncertainty set—for example, to minimize economic dispatch cost or ramping needs, to provide a customized robust unit commitment solution. Compared to traditional robust unit commitment models, the proposed model combines statistical tools with analytical framework of power system networks. The resulting formulation is easily implementable and customizable to the needs of the system operator. The method and its applications are validated against other established approaches, showing equivalent solution to the state-of-the-art approach. Case studies were conducted on the IEEE-30, IEEE-118, and the pegase-1354 networks. In addition, the flexibility of bus ranking formulation is illustrated through implementation of alternative definitions of worst-case metrics. Results show that the bus ranking method performs as well as the best of these methods, with the provision of additional flexibility and potential for parallelization. [ABSTRACT FROM AUTHOR]

Battery energy storage system (BESS) services will be of great help when operating power systems at high renewable energy penetrations. This paper demonstrates the requirements for effective frequency and inertia services. Some system operators currently apply scalars to financially reward improved performance. This paper demonstrates a method of validating and improving these scalars by considering the delay time and ramp time of the BESS. The importance of the method used to measure the rate of change of frequency is discussed in the paper. While the rate of change of frequency services improves with reduced delivery times, limits are identified where further reductions produce a negligible impact. This demonstrates the tangible benefits of a rapid response, and that current technology could meet the criteria. A variety of BESS capacities are trialed, which demonstrate consistency in performance and the occurrence of diminishing returns [ABSTRACT FROM AUTHOR]

This paper examines the small-signal stability of an integrated multiterminal dc (MTDC)/ac power system. The examination is based on a closed-loop multi-input multi-output interconnected model of the MTDC/ac power system, which comprises an MTDC subsystem and an ac subsystem. The focus of the examination is the condition of open-loop modal coupling when an open-loop oscillation mode of the MTDC subsystem is close to an open-loop oscillation mode of the ac subsystem on the complex plane. Analysis in the paper indicates that when the open-loop modal coupling happens, the multivariable ac–dc dynamic interactions between the MTDC and ac subsystems degrade the small-signal stability of the MTDC/ac power system. Estimation on the degree of stability degradation is derived. Hence, the paper reveals the mechanism about why the integration of the MTDC network may bring about the small-signal instability risk. In addition, a method of open-loop modal analysis to detect the risk is proposed. Example multimachine power systems with an MTDC network are presented to validate the analysis and conclusions made in the paper. Application of the proposed open-loop modal coupling analysis for parameter tuning of converter control systems of the MTDC network is demonstrated. [ABSTRACT FROM AUTHOR]

The control of reactive power exchange between grids of different voltage levels has always been a concern for system operators. With production moving from the transmission to the distribution level, its importance increases. This paper proposes a novel approach to estimate reactive power capability of the grid as a whole. A linearized analytical model for an estimation of available reactive power exchange at the interface between two grids has been developed. The maximum estimation error for the scenarios we tested was only 2%. The model gives the relation between important grid parameters and the supported reactive power. The conclusions drawn from the model are confirmed on typical Swedish distribution network with scattered wind power and small industry consumers. Common scenarios in development of distribution grids are applied to show relevant parameters influence. One studied scenario is replacement of overhead lines with cables. It is shown that this particular change enhances the reactive power capability of the grid which is directly seen from the analytical analysis without running any optimal power flow. The analytical model proposed in this paper gives fundamental understanding of the reactive power capability of radial distribution grids. [ABSTRACT FROM AUTHOR]

DC electric power systems, including HVDC, HVDC light, dc distribution systems, and dc microgrids, have a significant position in present and, especially, future electric power systems, namely, smart grids. One of the most significant issues of electric power systems, including dc electric power systems, is the calculation of accurate and fair energy costs of the consumers. In this paper, novel, simple, practical, and precise relations between economic and electrical variables in dc electric power systems are extracted. The novel relations prove that there are interesting relations between voltages of nodes, as electrical variables, and prices of nodes, as economic variables, in dc electric power systems. Applying the extracted novel relations in this paper, a new, fair, precise, practical nodal price, i.e., the fair nodal price, is determined to calculate the energy costs of consumers in dc electric power systems, including dc distribution systems and microgrids. Moreover, as an application of the extracted novel relations, a practical method to determine the fair nodal prices of all nodes and, as a result, the real energy cost of each consumer at each node of dc electric power systems is presented. The analyses results demonstrate the mentioned significant characteristics. [ABSTRACT FROM AUTHOR]

Day-ahead scheduling has played a significant role in the operation of distribution systems, aiming at minimizing the total operation cost. With the excessive integration of information and communication technologies and intelligent electronic devices, distribution system operators may seek to optimally control the active management elements to increase the economic and technical performance of future smart distribution systems. This paper focuses on an integrated day-ahead scheduling scheme that is formulated as a mixed integer second-order cone programming problem to obtain the optimal solution by means of the relaxed power flow model (RPFM). The detailed technical constraints for all the elements are accommodated based on the RPFM-based optimization method. Meanwhile, active management cost and punishment cost of wind power curtailed and customer energy not supplied are also considered in the design objectives of this paper. In order to address the uncertainties, a stochastic robust optimization method is first introduced to decide the active management elements (including capacitor bank, electrical storage system, controllable load, and switch) as the robust decision scheme. Afterwards, the column-and-constraint generation algorithm is applied to solve the proposed stochastic robust two-stage optimization model. Numerical results based on the IEEE 33-bus, PG&E 69-bus, and practical 152-bus systems are obtained to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Independent system operators (ISOs) are responsible for the secure and economic operation of the power systems. Accordingly, ISOs should solve an optimal power flow to minimize the operating cost of a system while meeting the system's security constraints. However, transmission congestion could drastically limit more economical generating units from being dispatched in the power system operation. In this paper, a decentralized transmission switching is introduced in the operation of multi-area power systems to manage the congestion both on regional transmission lines and tie lines while considering credible contingencies. Our proposed methodology relies on a decentralized optimization methodology. Thus, regional control centers in areas would be able to locally manage the congestion within their regional networks as well as tie lines connecting them to their neighboring areas. Several testing systems are studied in this paper to test the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper presents a method for harmoniously coordinating roles between generators and faster-acting energy storage systems (ESSs), e.g., batteries, to improve their frequency response and regulation services to the grid, particularly at the high wind penetration. This paper theoretically demonstrates that the proposed droop with the state of charge (SOC) feedback (DaSOF) provides a unified frequency control framework for distributed and energy-constrained ESS, seamlessly fitting the conventional primary and secondary frequency control practice. The ESS autonomously takes charge of high-frequency components of a frequency deviation and thus complements the frequency controls of the incumbent generators. By securing the SOC of the ESS at the desired level, the method provides the capability to provide other ancillary services from the energy-constrained ESS. These coordinated roles are represented and validated through time- and frequency-domain analyses. Rigorous case studies using DIgSILENT/PowerFactory demonstrate the efficacy of the proposed method to support the high level of variable renewable energy, which should help in improving the value of operating the ESS and scale up renewable energy. [ABSTRACT FROM AUTHOR]

The paper proposes a new adaptive approach to power system model reduction for fast and accurate time-domain simulation. This new approach is a compromise between linear model reduction for faster simulation and nonlinear model reduction for better accuracy. During the simulation period, the approach adaptively switches among detailed and linearly or nonlinearly reduced models based on variations of the system state: it employs unreduced models for the fault-on period, uses weighted column norms of the admittance matrix to decide which functions to be linearized in power system differential-algebraic equations for large changes of the state, and adopts a linearly reduced model for small changes of the state. Two versions of the adaptive model reduction approach are introduced. The first version uses traditional power system partitioning where the model reduction is applied to a defined large external area in a power system and the other area defined as the study area keeps full detailed models. The second version applies the adaptive model reduction to the whole system. The paper also conducts comprehensive case studies comparing simulation results using the proposed adaptively reduced models with the linearly reduced model and coherency-based reduced model on the Northeast Power Coordinating Council 140-bus 48-machine system. [ABSTRACT FROM AUTHOR]

This paper presents parameter values and ranges of static load models used in a power system analysis for the representation of both individual electrical devices and aggregate system loads. The paper discusses and correlates load models and their parameters following statistical processing of the responses of around 100 transmission system operators and utilities around the world, who participated in a survey initiated by CIGRE Working Group C4.605, with the corresponding information on load models and their parameter values from the existing literature. According to the survey, the most frequently used static load models are voltage dependent, and voltage and frequency dependent exponential load models. The identified typical parameter values and ranges of these static load models, both for low voltage devices and for aggregate loads at higher voltage levels, are results of the analysis of a large number of data. Based on these results, the paper provides recommendations for their further use in power system studies and also introduces a novel method for obtaining the mean values and ranges of parameters of the aggregate system load models. [ABSTRACT FROM AUTHOR]

This paper focuses on economic dispatch (ED) in power systems with intermittent wind power, which is a very critical issue in future power systems. A stochastic ED problem is formed based on the recently proposed versatile probability distribution of wind power. The problem is then analyzed and proved to be strictly convex. Although such convex optimization is tractable in many cases, it may take a long time to solve due to its large scale. This paper proposes a dual decomposition method to decompose the large problem. Then, two methods are employed to solve the decomposed problem, namely, the subgradient method and a faster method, limited-memory BFGS with box constraints (L-BFGS-B, a quasi-Newton method). Case studies were conducted to verify the efficiency of the dual decomposition and L-BFGS-B method for solving the stochastic ED problem. [ABSTRACT FROM AUTHOR]

The introduction of an equivalent model for a regional power area in a large-scale power system with complex loads is essential for reducing the computation burden in real-time dynamic analyses. In this paper, we propose a generalized discrete-time equivalent model (GDEM) with specific relations among model parameters for simulating the physical characteristics of a regional power area. The GDEM facilitates the interconnection of equivalent models representing regional power areas and improving the simulation accuracy and speed in large-scale dynamic power systems. This paper first investigates the inherent relations among GDEM parameters in the discrete-time models of synchronous generators and composite loads so as to guide the GDEM parameter estimation in regional power areas. This paper then develops relations among GDEM parameters for a regional power area. Numerical experiments are conducted by simulating ground faults in the China Electric Power Research Institute system and the accuracy of the proposed GDEM is verified by analyzing the dynamic simulation results. In addition, this paper has applied the GDEM to study the regional power area of Central China, which validates the use of GDEM in practical power system analyses. [ABSTRACT FROM AUTHOR]

A fast reliability calculation method based on the fault incidence matrix (FIM) for the complex distribution system is proposed in this paper. First, the M-segment-N-tie-switch (MSNT) reliability calculation unit for the complex distribution network is established and the power supply path matrix is obtained by inversing the node branch incidence matrix of the MSNT unit. Then, three types of FIMs are constructed considering the influence type of each fault event on the load points. Finally, the system reliability indexes are calculated through the algebraic operation between the FIMs and the fault event parameter vectors. The accuracy and the efficiency of this method are verified using the IEEE RBTS bus-6 system. The reliability evaluation method proposed in this paper avoids complicated fault event enumeration and repetitive fault influence range searching, thus, saves the computation time greatly. And more importantly, the analytical expression of the reliability indexes in the matrix form can clearly show the influence of each fault event on each load interruption. So, it is convenient for the reliability sensitivity analysis and helpful for the operator with the reliability improvement planning. [ABSTRACT FROM AUTHOR]

Optimal placement and sizing of distributed energy resources (DERs) can be performed from various points of view. In this paper, a multiobjective function is employed to determine optimal place and size of DERs including combination of photovoltaic resources and a small-scale synchronous generator (SSSG) with an internal combustion engine as its prime mover. As the objective function, not only minimization of investment costs, operation costs, and system losses are used, but also the voltage of microgrid (μG) busses and current of lines are considered as constraints. In addition, this paper shows mechanical stresses can be imposed on the SSSG caused by generator swings after short circuit fault clearing. Furthermore, it may lead to mechanical fatigue in its associated shaft and prime mover. Meanwhile, it is revealed that the mechanical stresses depend on the DERs placement and size. Thus, a novel index representing the stresses on the SSSG shaft is applied in the multiobjective goal function. This decreases SSSG loss of life in a μG with overhead lines which has high rate of short circuit faults. Optimization studies are performed in a six-bus and four-DER μG using time-based simulations. [ABSTRACT FROM AUTHOR]

This paper presents an online event location estimating process in a wide-area power system using the phasor measurement unit (PMU). For real-world applications of PMU-based event location estimation (ELE), it is necessary to consider the insufficiency of PMU data caused by a lack of PMUs, communication failure, PMU malfunction, etc., because insufficient PMU data cannot guarantee event observability over the entire network. To ensure possible event locations in a real-world system, an estimation method is developed by combining offline zonal analysis and an online ELE algorithm. The K-mean clustering method is utilized for electrical-bus clustering, which enables us to recognize separate electrical zones (EZs). Then, we propose a two-stage ELE algorithm by estimating the event EZ and localizing the specified event section within the estimated EZ. Proposed ELE algorithm is applied to a real-world PMU data collected from southwestern part of the United States. Finally, successful results from a real-world PMU data application are presented at the end of this paper. [ABSTRACT FROM AUTHOR]

This paper analyzes different models for evaluating investments in energy storage systems (ESS) in power systems with high penetration of renewable energy sources. First of all, two methodologies proposed in the literature are extended to consider ESS investment: a unit commitment model that uses the “system states” (SS) method of representing time; and another one that uses a “representative periods” (RP) method. Besides, this paper proposes two new models that improve the previous ones without a significant increase of computation time. The enhanced models are the “system states reduced frequency matrix” model which addresses short-term energy storage more approximately than the SS method to reduce the number of constraints in the problem, and the “representative periods with transition matrix and cluster indices” (RP-TM&CI) model which guarantees some continuity between representative periods, e.g., days, and introduces long-term storage into a model originally designed only for the short term. All these models are compared using an hourly unit commitment model as benchmark. While both system state models provide an excellent representation of long-term storage, their representation of short-term storage is frequently unrealistic. The RP-TM&CI model, on the other hand, succeeds in approximating both short- and long-term storage, which leads to almost 10 times lower error in storage investment results in comparison to the other models analyzed. [ABSTRACT FROM AUTHOR]

To encourage and support innovation, synthetic electric grids are fictional, designed systems that mimic the complexity of actual electric grids but contain no confidential information. Synthetic grid design is driven by the requirement to match wide variety of metrics derived from statistics of actual grids. In order to scale these systems to 10,000 buses or more, robust reactive power planning is needed, accounting for power flow convergence issues. This paper addresses reactive power planning and power flow convergence in the context of large synthetic power grids. The iterative algorithm presented by this paper supplements a synthetic transmission network that has been validated by a dc power flow with a realistic set of voltage control devices to meet a specified voltage profile, even with the constraints of difficult power flow convergence for large systems. The algorithm is illustrated with an example new synthetic 10,000 bus system, geographically situated in the western United States, which is publicly available and useful for a variety of research studies. An analysis is shown validating the synthetic system with actual grid characteristics. [ABSTRACT FROM AUTHOR]

The unit commitment is still a widely studied problem, especially when more renewable energy of stochastic character is being added to power systems. This paper proposes a model for weekly planning of systems involving hydro, wind, and thermal energy under a stochastic perspective. The proposed model follows the endogenous reserve determination criterion to achieve a simultaneous optimization of energy and reserves considering wind uncertainty, forced outages of equipment, a dc Flow model of the network, and cascaded head sensitive hydro systems, among others. The paper also develops a practical solution methodology based on outer approximation and benders decomposition. Testing has been conducted over four systems, and computational results demonstrate that the proposed model and solution are useful and effective. [ABSTRACT FROM AUTHOR]

Time delay is prejudicial to power system stability and generally worsens the performance of a control system. In this paper, the approaches for stability analysis and stabilization of a power system consisting of time-varying delay are established. The paper starts with the modeling of the power system according to time-delay differential algebraic equations. An integral quadratic constraints (IQC) method is constructed to guarantee the stability of the proposed feedback controller. The frequency-domain IQC and time-domain dissipation inequality are effectively combined to perform stability analysis and stabilization of the power system considering time delays, without complex numerical computation. A two-area four-machine system, an IEEE 10-machine 39-bus system, and a WECC 179-bus system are employed to support the stability criteria and the IQC method. The simulation results indicate that the combined methods effectively damp the oscillation and improve the performance. [ABSTRACT FROM AUTHOR]

This paper extends the dynamic coherency determination (DCD) method by including Type-3 wind power plants (WPPs) models in the coherency evaluation process and quantifies impacts of the high depth of wind power penetration on the coherency phenomena of interconnected power systems. The method is based on frequency-deviation signals, measured at nongenerator buses and terminal buses of WPPs and synchronous generators. Salient features of the presented method are its ability to account for the hybrid nature of enhanced generic models of Type-3 WPPs and expanding notion of the power system coherency beyond the classical definition by including models of Type-3 WPPs. This paper also investigates impacts of the high depth of wind power penetration; i.e., up to 30%, on the coherency structure of the 16-machine/68-bus NPCC equivalent system. The studies are based on time-domain simulations in PSS/E software. The investigations reveal that Type-3 WPPs can introduce new coherent areas, significantly change areas’ boundaries and number of areas, and alter frequencies/dampings of interarea modes. [ABSTRACT FROM AUTHOR]

Centralized electricity markets currently do not optimize reactive power and voltage in the market clearing software. Voltage and local reliability (VLR) commitment requirements are mostly identified through out of market operational procedures. Failure to maintain VLR may incur voltage collapse, generation, transformer loss, or even blackout. Midcontinent Independent System Operator (MISO) employs binary constraints, minimum/maximum generation constraints, interface constraints, and manual commitments to address VLR requirement in the market clearing process and ensure adequate commitment for reliability. This paper integrates binary VLR constraints in day-ahead security constrained unit commitment to improve market efficiency. However, VLR constraints may cause uplift cost, and sometimes the associated uplift cost can be significant. An uplift cost allocation method with the consideration of resources commitment reasons is developed in this paper. The proposed approach is considered for implementation in MISO market clearing process and a MISO test case is used to validate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Day-Ahead Unit Commitment (UC) is an important problem faced by Independent System Operators (ISOs). Midcontinent ISO as the largest ISO in US, solves a complicated UC problem involving over 45,000 buses and 1,400 generation resources. With the increasing number of combined cycle units (CCs) represented by configuration-based modeling, solving the problem becomes more challenging. The state-of-the-practice branch-and-cut method suffers from poor performance when there are a large number of CCs. The goal of this paper is to solve such large UC problems with near-optimal solutions within time limits. In this paper, our recently developed Surrogate Lagrangian Relaxation, which overcomes major difficulties of Lagrangian Relaxation by not requiring dual optimal costs, is significantly enhanced through adding quadratic penalties on constraint violations to accelerate convergence. Quadratic penalty terms are linearized through a novel use of absolute value functions. Therefore, resource-level subproblems can be formulated and solved by branch-and-cut. Complicated constraints within a CC unit are thus handled within a subproblem. Subproblem solutions are then effectively coordinated. Computational improvements on key aspects are also incorporated to fine tune the algorithm. As demonstrated by MISO cases, the method provides near-optimal solutions within a time limit, and significantly outperforms branch-and-cut. [ABSTRACT FROM AUTHOR]

Combined heat, and power dispatch promotes interactions, and synergies between electric power systems, and district heating systems. However, nonlinear, and nonconvex heating flow imposes significant challenges on finding qualified solutions efficiently. Most existing methods rely on constant flow assumptions to derive a linear heating flow model, sacrificing optimality for computational simplicity. This paper proposes a novel convex combined heat, and power dispatch model based on model simplification, and constraint relaxations, which improves solution quality, and avoids assumptions on operating regimes of district heating systems. To alleviate mathematical complexity introduced by the commonly used node method, a simplified thermal dynamic model is proposed to capture temperature changes in networked pipelines. Quadratic, and polyhedral relaxations are then applied to convexify the original problem with quadratic equality, and bilinear constraints. Furthermore, an adaptive solution algorithm is developed to successively reduce the relaxation area based on sequential bound tightening, which improves solution optimality with desirable computational efficiency. The proposed method is verified on a distribution-level, and a transmission-level integrated electricity, and heat systems, compared to constant-flow-based solutions, and iterative algorithms. [ABSTRACT FROM AUTHOR]

Event-triggered control (ETC) is becoming increasingly popular in load frequency control (LFC) operation in power systems. So far, the existing literature has primarily focused on load disturbance rejection in face of communication delay without considering much on networked-induced measurement disturbances and messages sent. In this paper, we study the LFC operation as a problem of networked control system and propose, for the first time, an ETC based switching approach for frequency regulation. We derive delay-dependent conditions to obtain the lower bound on inter-event time during event-trigger mechanism which assures the robust stability under networked induced time-varying delays and measurement disturbance and reduction in the amount of sent measurements. The effectiveness of the proposed approach is verified via numerical examples based on single-, two-area power systems and single-area with electric vehicle (EV) participation. [ABSTRACT FROM AUTHOR]

Demand response (DR) programs aim to engage distributed demand-side resources in providing ancillary services for electric power systems. Previously, aggregated thermostatically controlled loads (TCLs) have been demonstrated as a technically viable and economically valuable provider of such services that can effectively compete with conventional generation resources in reducing load peaks and smoothing demand fluctuations. Yet, to provide these services at scale, a large number of TCLs must be accurately aggregated and operated in sync. This paper describes a Markov Decision Process (MDP) that aggregates and models an ensemble of TCLs. Using the MDP framework, we propose to internalize the exogenous uncertain dynamics of TCLs by means of stochastic and distributionally robust optimization. First, under mild assumptions on the underlying uncertainty, we derive analytical stochastic and distributionally robust control policies for dispatching a given TCL ensemble. Second, we further relax these mild assumptions to allow for a more delicate treatment of uncertainty, which leads to distributionally robust MDP formulations with moment- and Wasserstein-based ambiguity sets that can be efficiently solved numerically. The case study compares the analytical and numerical control policies using a simulated ensemble of 1,000 air conditioners. [ABSTRACT FROM AUTHOR]

This paper investigates the modal repulsion happened in the sub-synchronous resonance between a synchronous generator and series-compensated transmission line. The investigation is based on the closed-loop model of the series-compensated power system consisted of the torsional and electrical open-loop subsystems. Analytical explanation is presented to show how the SSO modal repulsion is formed as the result of moving close and apart between two open-loop SSO modes. Analysis is carried out to indicate that the peak of the SSO modal repulsion occurs when the two open-loop SSO modes from the torsional and electrical subsystem are closest to each other on the complex plane, which is referred to as the open-loop modal coupling. Estimation on the peak, i.e., the maximum damping degradation of the SSO modes, is derived in the paper. Subsequently, a method of open-loop modal analysis is proposed. Applications of the proposed method of open-loop modal analysis to study the SSOs caused by the DFIGs under the condition of the modal repulsion in the power system are demonstrated and evaluated by example power systems. The concept of modal repulsion explains why the grid connection of the DFIGs may bring about the SSO instability risk in the power system. [ABSTRACT FROM AUTHOR]

This paper presents a decentralized solution algorithm for network-constrained unit commitment (NCUC) in multiregional power systems. The proposed algorithm is based on our previous work in which a local NCUC was formulated for each control entity (i.e., region) and an analytical target cascading (ATC) based distributed but partially parallelized algorithm requiring a central coordinator was presented. The primary objective of this paper is to present a decentralized approach that relaxes the need for any form of central coordinator in ATC and allows fully parallelized solutions of the local NCUCs. To achieve this objective, we formulate a bilevel optimization problem for each control entity. While the upper level solves the NCUC problem of the control entity, the lower level seeks to coordinate the control entity with its neighboring regions. The lower level is a convex optimization, which can be further replaced in the upper level problem by the Karush–Kuhn–Tucker conditions. The control entities communicate directly with each other and synchronously solve their local NCUCs. Having no need for any form of central coordinator, the proposed algorithm is potentially less vulnerable to cyber-attacks and communication failures than the distributed methods utilizing a coordinator. [ABSTRACT FROM AUTHOR]