José L. Rueda

Assessment and Enhancement of Small Signal Stability Considering Uncertainties

This paper proposes a probabilistic small signal stability assessment (PSSSA) methodology based on the application of Monte Carlo approach for iterative evaluation, via modal analysis of small signal stability (SSS). Operation states represented by random values of generation and demand are analyzed. A probabilistic instability risk index based on cumulative probability distribution function of damping ratios of oscillatory modes is calculated, as well as a power system stabilizer (PSS) devices location index based on eigenvectors and participation factors, which are considered random variables. Moreover, the impact of long-distance power flows on oscillatory modes (OM) and how the damping of OM depends on the orientation and magnitude of power flows is investigated. Further, an additional index concerns qualitatively the determination of transfer capability as affected by small signal stability. PSSSA is tested on a reduced order model of New England-New Yorks interconnected system considering uncertainties around three different system conditions separately: highly loaded, fairly loaded, and lowly loaded. The results highlight the main advantages of PSSSA over deterministic SSS studies such as instability risk assessment, small signal stability enhancement through adequate PSS location, and the proposal of possible restrictions for transfer capability in order to avoid poorly damped oscillations in the face of the diversity in power system operation.

Wavelet-Based Analysis of Power System Low-Frequency Electromechanical Oscillations

This paper addresses the use of the continuous wavelet transform (CWT) in the study of power system low-frequency electromechanical oscillations (LFEOs). Based on a modified complex Morlet mother-wavelet function, an approach is proposed to exploit the relationship between system low-frequency oscillation features and the Morlet CWT of a system ringdown signal for detection of modal parameter changes as well as for modal frequency and damping computation. Also, several guidelines for selecting the center frequency and bandwidth parameters, the scaling factor and the translation factor, are proposed in order to provide reliable modal identification estimates. The efficiency of the proposed approach is confirmed by applying it to synthetic, simulated and measured signals.

A novel optimization algorithm for optimal reactive power dispatch: A comparative study

Optimal reactive power dispatch (ORPD) is a key instrument to achieve secure and economic operation of power systems. Due to complex characteristics of ORPD, heuristic optimization has become an effective solver. A novel heuristic optimization algorithm namely the Mean-Variance Mapping Optimization (MVMO) is proposed to handle the ORPD problem. The concept, mechanism and implementation of MVMO are discussed in this paper. Based on the IEEE 57- and 118- bus systems, MVMO is compared with some basic and enhanced evolutionary algorithms. Simulation results show that MVMO is an excellent algorithm for ORPD and should deserve more attention. The superiority to the other algorithms is very pronounced in the IEEE 118-test case.

Impact of large offshore wind farms on power system transient stability

This paper deals with the impact of large scale wind power integration on the transient stability performance of power systems. Typical offshore wind farm topologies including the medium and high voltage submarine cables, the generator, the multi-stage transformers, the controllers were simulated using real-world values. Voltage and power at the point of common coupling and the swing curves of conventional synchronous generators following a major grid fault were computed and the critical fault clearing times were determined and compared with one another for different levels of wind integration. It was found out that using the currently established controller structure and parameter settings, the transient stability performance of the system deteriorates with increasing wind integration. The study has also revealed that there are a range of options to improve the performance of the system even to the extent of improving on the performance of the system beyond the baseline scenario where there is no wind power generation at all.

Evaluating the Mean-Variance Mapping Optimization on the IEEE-CEC 2014 test suite

This paper provides a survey on the performance of the hybrid variant of the Mean-Variance Mapping Optimization (MVMO-SH) when applied for solving the IEEE-CEC 2014 competition test suite on Single Objective RealParameter Numerical Optimization. MVMO-SH adopts a swarm intelligence scheme, where each particle is characterized by its own solution archive and mapping function. Besides, multi-parent crossover is incorporated into the offspring creation stage in order to force the particles with worst fitness to explore other sub-regions of the search space. In addition, MVMO-SH can be customized to perform with an embedded local search strategy. Experimental results demonstrate the search ability of MVMO-SH for effectively tackling a variety of problems with different dimensions and mathematical properties.

Hybrid Mean-Variance Mapping Optimization for solving the IEEE-CEC 2013 competition problems

Mean-Variance Mapping Optimization (MVMO) is a recent addition to the emerging field of heuristic optimization algorithms, which has been quite successful in solving a variety of power system optimization problems. This paper introduces a hybrid variant of MVMO (MVMO-SH) for solving the IEEECEC 2013 competition test suite. MVMO-SH is based on a swarm scheme of MVMO with embedded local search and multi-parent crossover strategies to increase search diversity and solution quality. Numerical results attest to the promising prospect of MVMO-SH to become a general purpose optimization algorithm.

Identification of dynamic equivalents based on heuristic optimization for smart grid applications

Vulnerability assessment is one of the main tasks in a Self-Healing Grid structure, since it has the function of detecting the necessity of performing global control actions in real time. Due to the short-time requirements of real time applications, the eligible vulnerability assessment methods have to consider the improvement of calculation time. Although there are several methods capable of performing quick assessment, these techniques are not fast enough to analyze real large power systems in real time. Based on the fact that vulnerability begins to develop in specific regions of the system exhibiting coherent dynamics, large interconnected power systems can be reduced through dynamic equivalence in order to reduce the calculation time. A dynamic equivalent should provide simplicity and accuracy sufficient for system dynamic simulation studies. Since the parameters of the dynamic equivalent cannot be easily derived from the mathematical models of generators and their control systems, numerical identification methods are needed. Such an identification task can be tackled as an optimization problem. This paper introduces a novel heuristic optimization algorithm, namely, the Mean-Variance Mapping Optimization (MVMO), which provides excellent performance in terms of convergence behavior and accuracy of the identified parameters. The identification procedure and the level of accuracy that can be reached are demonstrated using the Ecuadorian-Colombian interconnected system in order to obtain a dynamic equivalent representing the Colombian grid.

Impacts of large scale integration of wind power on power system small-signal stability

In this paper, based on a small-size power system, a deterministic assessment on the impact of wind power on power system small-signal stability is first thoroughly discussed. Next, a realistic weak wind-hydro-thermal (WHT) power system is used to ascertain if the indicative findings of the preliminary work can be confirmed by a large scale case study. Subsequently, Monte Carlo based probabilistic eigenanalysis is implemented on the weak WHT system in order to further corroborate the findings drawn from the deterministic studies. It was found out that large wind power integration can have positive or negative impacts on system damping depending on the location of the wind power plant, the amount of the conventional generation replaced by wind power and the stress level of the power system.

PowerFactory Applications for Power System Analysis

This book presents a comprehensive set of guidelines and applications of DIgSILENT PowerFactory, an advanced power system simulation software package, for different types of power systems studies. Written by specialists in the field, it combines expertise and years of experience in the use of DIgSILENT PowerFactory with a deep understanding of power systems analysis. These complementary approaches therefore provide a fresh perspective on how to model, simulate and analyse power systems. It presents methodological approaches for modelling of system components, including both classical and non-conventional devices used in generation, transmission and distribution systems, discussing relevant assumptions and implications on performance assessment. This background is complemented with several guidelines for advanced use of DSL and DPL languages as well as for interfacing with other software packages, which is of great value for creating and performing different types of steady-state and dynamic performance simulation analysis. All employed test case studies are provided as supporting material to the reader to ease recreation of all examples presented in the book as well as to facilitate their use in other cases related to planning and operation studies. Providing an invaluable resource for the formal instruction of power system undergraduate/postgraduate students, this book is also a useful reference for engineers working in power system operation and planning.

Online Optimal Control of Reactive Sources in Wind Power Plants

This paper suggests a novel approach to the problem of online optimal control of reactive sources in wind power plants (WPPs). Based on measurements tracking the actual conditions of each wind generator and the settings of transformers and compensation equipment within the WPP facility, the key idea is to incorporate reactive power optimization into a global WPPs control loop so that it can be used online to determine the optimal distribution of reactive power, which is needed to meet grid code requirements, among the available Var sources. The optimization problem is handled using an enhanced version of the mean-variance mapping optimization algorithm. A test case, based on a representative offshore WPP, is presented to demonstrate the effectiveness of the proposed control strategy.