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The increasing penetration of renewable energy sources (RESs) can challenge both power system planners and operators to maintain system reliability. Potential power system stability issues may arise when a large amount of RESs are connected to a weak power system. The short-circuit ratio (SCR) with some modifications has been used to analyze power system strength. However, the existing SCR-based methods for system strength assessment neglect real electrical network connections among multiple RESs, which may not reflect the effect of the interactions among multiple RESs at different sites on system strength. To account for the interactions among electrically interconnected RESs, the so-called site-dependent SCR (SDSCR) is proposed in this paper by analyzing the relationship between system strength and voltage stability. The efficacy of the proposed SDSCR is demonstrated through numerical simulation case studies on the IEEE 39-bus system. [ABSTRACT FROM AUTHOR]

The number and locations of transmission lines that are likely to get simultaneously congested are useful information for analysis of power market. In this paper, we present a study that demonstrates the number of simultaneously congested transmission lines is very limited, as well as an algorithm for identifying a small set of transmission lines that may become simultaneously congested based on the current states of the system and market. To this end, we first investigate the maximum number of simultaneously congested lines. Then, a novel algorithm is developed to identify a smaller set using two scientific criteria – one is concerned with the absolute impact of generation dispatch decisions, and the other, the relative sensitivities of line flows with respect to the changes of generation outputs. The effectiveness of the proposed algorithm is demonstrated through two simulation studies, one based on IEEE 39-bus for illustration of concepts, and the other based on a large-scale, real-world power system for showing the practical application and significance of results. [ABSTRACT FROM AUTHOR]

In this paper, we introduce an approach for a fast assessment of the dynamic characteristics of system frequency during the period of cold load pickup following a large-scale blackout. The approach is developed based on a load model and a model of generation control system: the load model considers the unique time-dependent characteristic of inrush power surges during the period of cold load pickup, while the model of generation control system mimics the characteristics of various governors that are crucial to the determination of the key variables including initial rate of frequency change, frequency nadir and settling frequency. With the proposed linearization and estimation methods, the model of generation control system can be quickly constructed to offer a great amount of flexibility and simplicity for the study of the impact of cold load on frequency response. The proposed approach allows system operators to quickly evaluate many different options for system restoration. The application of the proposed approach is demonstrated in a case study based on the IEEE 39-bus system. The differences between the results obtained using the proposed approach and those obtained from complete PSS/E simulation are very small, which suggests that the linearized model of generation control system is fast, and accurate enough to address the major concerns of cold load pickup in system restoration. [ABSTRACT FROM PUBLISHER]

Decentralized electrical energy systems will play an essential role in the future smart grid. In this paper, we introduce a new industrial scale electric thermal energy system using a high-voltage electrode boiler, of which the level of electricity consumption can be adjusted as desired. It is also shown that, with appropriate instrumentation and measurement algorithms, the energy consumption can be adjusted quickly and accurately. This feature makes such a thermal energy system an ideal candidate to deal with the variability of renewable energy, to respond to the prices in the electric power markets and support the frequency stability of the power grid. [ABSTRACT FROM PUBLISHER]

Many important issues of power system dynamics are often studied by looking at the dynamic responses of generators connected through the power grid, taking their interactions into consideration. In this paper, we present a specific study on the significant impact of grid structure on the power system dynamics with quantitative evidence. Specifically, it is found that the impact of grid structure heavily depends on two types of grid-structure-related variables: 1) electrical distances among the generator internal buses, and 2) electrical distances between the generator internal buses and the faulted bus. Furthermore, with the examples of coherency identification problem, the significance of grid structure is demonstrated by the strong agreement of identification results between using a set of criteria that only takes into account the grid-structure-related variables and dynamic simulations. [ABSTRACT FROM PUBLISHER]

Publicly available information today on wind and wind generation is incomplete for deep understanding of their characteristics. The owner or operator of a wind farm typically only releases minutes-level turbine wind speed data. Although seconds-level wind power data may be obtained from the SCADA system, they only reflect aggregated performance at the wind farm level and thus cannot be used to obtain the covariance/correlation of wind speeds experienced by individual turbines at the seconds-level, which is a key to in-depth understanding of the characteristics of wind for wind farm control studies. To address this issue, this paper presents an empirical framework that uses incomplete wind data to calibrate a wind farm wind speed model. First, two such models are constructed from an ARIMA state-space model. Next, Monte Carlo filters and likelihood function maximization are incorporated to calibrate the models, reconstruct the unobserved states, and estimate the parameters. Finally, we test the model using synthetic wind data and demonstrate its effectiveness in statistically recovering missing information in the data. [ABSTRACT FROM PUBLISHER]

Wind farm power control is key to reliable large-scale wind integration. The design of a sophisticated wind farm controller, however, is challenging partly because there is a lack of models that appropriately simplify the complex overall dynamics of a large number of wind turbine control systems (WTCSs). In this paper, using system identification approaches, we develop a simple approximate model that attempts to mimic the active and reactive power dynamics of two generic WTCS models under normal operating conditions: an analytical model described by nonlinear differential equations, and an empirical one by input-output measurement data. The approximate model contains two parts—one for active power and one for reactive—each of which is a third-order system that would have been linear if not for a static nonlinearity. For each generic model, we also provide an identification scheme that sequentially determines the approximate model parameters. Finally, we show via simulation that, despite its structural simplicity, the approximate model is accurate and versatile, capable of closely imitating several different analytical and empirical WTCS models from the literature and from real data. The results suggest that the approximate model may be used to facilitate research on wind farm power control. [ABSTRACT FROM PUBLISHER]

This paper presents a feedback/feedforward nonlinear controller for variable-speed wind turbines with doubly fed induction generators. By appropriately adjusting the rotor voltages and the blade pitch angle, the controller simultaneously enables: 1) control of the active power in both the maximum power tracking and power regulation modes; 2) seamless switching between the two modes; and 3) control of the reactive power so that a desirable power factor is maintained. Unlike many existing designs, the controller is developed based on original, nonlinear, electromechanically-coupled models of wind turbines, without attempting approximate linearization. Its development consists of three steps: 1) employ feedback linearization to exactly cancel some of the nonlinearities and perform arbitrary pole placement; 2) design a speed controller that makes the rotor angular velocity track a desired reference whenever possible; and 3) introduce a Lyapunov-like function and present a gradient-based approach for minimizing this function. The effectiveness of the controller is demonstrated through simulation of a wind turbine operating under several scenarios. [ABSTRACT FROM AUTHOR]