Algorithm for identifying wind power ramp events via novel improved dynamic swinging door

An algorithm for forecasting day-ahead wind power via novel long short-term memory and wind power ramp events

With the increasing penetration of renewable energy in recent years, wind power ramp events (WPREs) have started affecting the economic and reliable operation of power grids. In this paper, we develop an optimized swinging door algorithm (OpSDA) to improve the state of the art in WPREs detection. The swinging door algorithm (SDA) is utilized to segregate wind power data through a piecewise linear approximation. A dynamic programming algorithm is performed to optimize the segments by: 1)merging adjacent segments with the same ramp changing direction; 2)handling wind power bumps; and 3)postprocessing insignificant-ramps intervals. Measured wind power data from two case studies are utilized to evaluate the performance of the proposed OpSDA. Results show that the OpSDA provides 1)significantly better performance than the SDA and 2)equal-to-better performance compared to the L1-Ramp Detect with Sliding Window (L1-SW) method with significantly less computational time.

Simulation and detection of wind power ramps and identification of their causative atmospheric circulation patterns

One of the key aspects in the development of power engineering all over the world is the use of distributed small-scale generation. This is both based on fuel carbon resources with a synchronized connection between sources when they are connected to the electric power grids and renewable energy sources operated in the electrical grid via frequency converters (electronic generation). The latter brings an inevitable broad use of inverters in available AC power systems. The objectives of this paper are numerous. First is the desire to study the effect of electronic generation on modes and stability of current electrical grids and electrical power systems. Another objective is to establish requirements for electronic generation control that lets us minimize actions on relay protection coordination and automation upon the integration of electronic generation in power grids. A final objective is to increase the reliability of general electrical modes. This article shows the outcomes of the study on the statical aperiodic stability of the electrical power system upon the integration of electronic generation, requirements for its statical characteristics, and the control when operated within the electrical power system.

One of the technical solutions for improving the stability of power system is incorporation of Static Synchronous Compensators (STATCOM) and Static Synchronous Series Compensator (SSSC) controllers. However, the impact of hybridized STATCOM and SSSC on the generator damping stability of the power system to improve the post disturbance recovery voltages of the generator is necessary. Thus, in this study, hybridized model of STATCOM and SSSC controllers were incorporated on the Nigerian 31-bus power system to improve the system generator damping stability during disturbance. Transient stability of electrical power system with contingency was performed using swing equations technique. Line-Voltage Stability Index (L-VSI) technique was employed to determine the critical load bus for the placement of the controllers. Hybridized model of the STATCOM and SSSC was developed and incorporate into the selected load buses and its impact on stability of the generator oscillation damping was examined. Simulation was done in MATLAB R2023a. The generator damping ratio, total active power losses and total cost of controllers were determined. Results verified the effectiveness of hybridized model of STATCOM and SSSC controllers in improving the stability of power generator oscillation damping. Keywords : STATCOM, SSSC, Line-Voltage Stability Index, Contingency, Generator Oscillation Damping, Power Loss. DOI: 10.7176/NCS/15-04 Publication date: February 28 th 2025

Wind power ramp events increasingly affect the integration of wind power and cause more and more problems to the safety of power grid operation in recent years. Several forecasting techniques for wind power ramp events have been reported. In this paper, the statistical scenarios forecasting method is proposed for wind power ramp event probabilistic forecasting based on the probability generating model. Multi-objective fitness functions are established considering cumulative density functions and higher order moment autocorrelation functions with respect to the consistency of distribution and timing characteristics, respectively. Parameters of probability generating model are calculated by the iterative optimization using the modified genetic algorithm with multi-objective fitness functions. A number of statistical scenarios captured bands are generated accordingly. Eventually, ramp event probability characteristics are detected from scenarios captured bands to evaluate the ramp event forecasting method. A wind plant of Bonneville Power Administration with actual wind power data is selected for calculation and statistical analysis. It is shown that statistical results with multi-objective functions are more accurate than the results with single objective functions. Moreover, the statistical scenarios forecasting method can accurately estimate the characteristics of wind power ramp events. The results verify that the proposed method can guide the generation method of statistical scenarios and forecasting models for ramp events.

Due to the rapid change of wind power, limit prediction cycle and severe uncertainty, wind power ramp events raise new challenges to the power system with high penetration of wind power. In order to reduce the risk and scheduling cost, an IGDT-based intraday scheduling strategy method is proposed in this paper. The wind farm cost caused by prediction errors is analyzed and taken into account as part of the scheduling cost, which is the optimization objective. By analyzing the characteristic of wind power ramp events, a new constraint related to the minimum start-up time of conventional units is suggested into the wind power ramp scheduling model. To deal with the uncertainty of wind power ramp prediction, the scheduling model is solved using IGDT method, which can provide robust strategy. The Monte Carlo method is used to compare the IGDT-based method and traditional deterministic method. Simulation results verify that the proposed wind power ramp scheduling strategy method proposed in this paper is more robust and economical.

The objective of the paper is to present a method which can be used to evaluate rapidly the transient stability of an electric power system. The stability evaluation is performed by using a fuzzy pattern recognition approach, incorporating fuzzy membership values for the system operating states. These values classify the operating states into the defined fuzzy sets representing the class of either the stable or the unstable states. The memberhsip evaluation is performed by considering the lack of a known mathematical expression for the membership values and by using the fuzzy ISODATA clustering algorithm. The developed computational method is applied to evaluate the transient stability of a sample electric power system.

With increasing heating demand and installed capacity of wind farms, combined heat and power (CHP) systems with inflexible generation are confronted with a major challenge for the efficient utilization of the wind power. Distributed heat sources (DHSs), such as electric boilers and heat storage, offer an effective way to enhance wind power penetration in a combined heat and power system by reducing the electric-heat coupling of the CHP unit. In this paper, an assessment approach for the wind power penetration of a CHP system with DHSs is proposed, and a two-stage multiple types of DHSs optimal configuration strategy to realize the minimum construction cost at a certain permissible wind power curtailment rate is established. After that, the proposed strategy is applied to a case study of a practical CHP system with in-depth analysis and detailed discussion, which reveals the effectiveness of the proposed strategy and indicates its promising applications for DHS configuration.

In this days, the necessity of using wind generators to produce energy and environmental issues, show that increasing the importance of study between researchers in this field. Since the penetration of wind power in electric power system is increasing greatly, it is urgent to study the impact of wind power on the dynamic stability of electric power system. In this paper, the dynamic behavior of the small Wind Turbine in domestic load is studied. Wind turbine induction generator connected to local load and by short transmission line that connected to an infinite bus. To achieve this goal, the simple model of small Wind turbine has been connected to an infinite bus through a short transmission line and domestic load. Using a dynamic systems model is sensitivity Analysis to changes in transmission line ratio and reactive power compensator has been studied. Finally, to investigate the eigenvalues and the locus of the system is studied. The system's modelling has been done analytically using the differential equations dominant on its behavior. The aforementioned equations have been solved using Rang-Kutta order-four method. At the end, the results of the simulation have been analyzed, and the variation of different parameters has been studied.

Characteristic multipliers (CM) of the Mathieu equation are the equivalent of eigenvalues of a linearized nonlinear differential equation. Oscillations will be stable when the real part of CMs is less than unity. The characteristic of an oscillation will change if the real part of CMs have magnitude greater than unity. In this letter, the investigation is directed to the effect of changes in CM on the stability of power systems. The significant role of nonlinearity is demonstrated by finding CM for the nontrivial single-machine system. The nonautonomous form of the Mathieu equation obtained models the effect of time dependent perturbations at the quasi-infinite bus.

Introduction. The article is devoted to the analysis of the stability of the electric power system (EPS) in mountainous areas using the Hurwitz criterion. In mountainous regions, the EPS faces a number of specific problems, such as complex terrain, remoteness of consumers and an increased probability of power transmission line failures. An important task is to develop a mathematical model that takes these features into account and to conduct an analysis of the stability of the system using the Hurwitz criterion. The purpose of the research: stability analysis of the system “high-pressure hydroelectric power plant – electric power system” using the Hurwitz criterion; identification of critical parameters of the system that affect its stability, and application of various optimization methods to improve the reliability and safety of the EPS in mountainous regions. Objects and methods. The object of the study is the high-pressure hydroelectric power plant (HPP) of PJSC RusHydro – Zaramagskaya HPP. The following methods were used for stability analysis: numerical modeling (integration of differential equations); state variable method; Laplace method; frequency response method; analytical methods for finding an exact solution to differential equations. Results and discussions. The results of the study demonstrate that the Gurwitz criterion is an effective tool for analyzing the stability of complex electric power systems, especially in mountainous areas. In the work, this method was successfully applied to analyze the static stability of the system taking into account automatic excitation control. Conclusion. A mathematical model has been developed that takes into account the specific conditions of mountainous areas. An analysis of the static stability of the system has been conducted taking into account the automatic excitation control (AEC). Critical parameters that affect the stability of the system, such as the load angle and the AEC gain factors, have been identified. It has been shown that increasing the accuracy of voltage maintenance can lead to a violation of stability in high-load modes. A method has been proposed for determining the minimum permissible gain factor, which allows avoiding aperiodic instability. Prospects for further research. In the future, possible alternative methods of stability analysis should be considered, such as frequency methods or methods based on Lyapunov theory, which could complement the results obtained using the Hurwitz criterion. A more detailed dynamic stability analysis should also be presented, which could provide a more complete understanding of the system’s behavior in transient conditions.

With large wind energy integration into power systems, wind farms begin to influence power systems in a much more significant manner. As wind energy systems utilize different generator technologies from the one utilized in the conventional power plants, the steady-state, transient and small-signal dynamics, as well as, power system stability will thus be significantly affected. The impact of wind energy systems on the power system dynamics and stability is thus of practical importance. As there is a significant increase in installation of wind turbines equipped with doubly-fed induction generator (DFIG) in recent years, a dynamic model of the DFIG wind turbine is firstly developed in this thesis. The model is validated against field measurement data, and the validation gives confidence about the accuracy and applicability of the developed model. DFIG wind farms consist of tens to hundreds of identical DFIG wind turbines increasing the complexity of the wind farm model and simulation time. A novel aggregation technique is developed in this thesis that incorporates a multiplication factor, namely mechanical torque compensation factor (MTCF), to the mechanical torque of the full aggregated wind farm model. The MTCF is initially constructed to approximate a Gaussian function by using fuzzy logic method. By optimizing the MTCF on a trial and error basis, less than 10 percent discrepancy is then achieved between the proposed aggregated model and the complete model. The proposed aggregation technique is then applied to a 120 MVA offshore wind farm comprising of 72 DFIG wind turbines and shows higher accuracy in approximating the wind farm dynamics as it appears at the point of common coupling (PCC) as compared to the full aggregated model. The proposed aggregated model computes faster than the complete wind farm model by 90.3 percent during normal operations and 87 percent during grid disturbances. To overcome the adverse effects due to the fluctuating nature of wind, two wind power smoothing methods are proposed using a fuzzy logic pitch angle controller for a smooth performance with a minimum drop in output power. One method performs partial smoothing with only 4.74 percent drop in the output power while the other method offers complete smoothing with a 8.28 percent drop in output power. The impact of wind energy integration on power system transient stability (PSTS) is studied quantitatively with the transient energy margin (TEM), which is calculated through the evaluation of the transient energy function (TEF). This study is carried out in two ways in the thesis. One is to analyse the impact of transient fault on the DFIG wind turbine as compared to SGs for different factors, like the fault clearing time, the grid coupling, the inertia constant and the voltage sag. The study reveals that transient stability of the DFIG wind turbine is hardly affected by the grid coupling, the inertia constant and the generator terminal voltage sag variations indicating its consistent transient performance within a wide range of these factors. The fault clearing time should be almost 11 percent faster for the system with the DFIG than the synchronous generator (SG). The other is to investigate the impact of the DFIG wind farm on the PSTS with the variation of different factors, which are the voltage sag, the fault clearing time, the load and the wind power penetration level. The study reveals that power systems integrated with DFIG wind farms are sensitive to transient events with high voltage sag, high fault clearing time, low load operation and high wind power penetration level. Machines at different locations individually possess distinct fault response and suffer from a large-scale power imbalance. As a result, reliable operation of DFIG wind farm integrated power systems demands upgraded equipment, such as advanced switchgear, fast breakers/isolators, efficient power reserve systems and advanced reactive power compensating device, etc.

The paper sum up an effort that has been done within an initial phase of the project sponsored by the Technology Agency of the Czech Republic (TACR) Application of methods of reliability and risk oriented decision making for operation of complex electric power systems (TA04020956). In the paper, authors present the problem of stability of the electrical power system in the Czech Republic from the point of view of external hazards. The complexity of the electrical power grid and the diversity of its components represent the reason for decomposition of the problem. Possible methodology to deal with external hazards influencing the stability of electrical power system is presented and a few of selected external hazards are discussed more in detail, e.g. wind, sand storm, icing, electromagnetic storms and solar storms.

Accurate damping of inter-area and intra area oscillations are very much critical in the stability of electric power system. Power system stabilizer (PSS) is mainly used as auxiliary controllers to damp out the low frequency oscillations in the area of electric power system. The tuning of Conventional Power System Stabilizer (CPSS) for a nonlinear power system should be robust such that overall system stability can be improved under several operating points. Today's scenario, various populations based heuristic algorithms are available to minimize the effect of stability problem by properly tuning the parameters of CPSS. In this paper presents a new heuristic population based optimization technique named as Group Search Optimization (GSO) algorithm to tune the PSS parameters for a multi-machine system for different operating conditions. The importance of the GSO algorithm is evaluated and compared for damping the system oscillations during small and large disturbances, and their robustness is illustrated using the transient signal analysis.