This paper proposes a method for the small signal stability analysis and correction of power system based on Light Gradient Boosting Machine (LightGBM). Taking the load power, branch power, and ...generator power as inputs, the minimum damping ratio is output to build the mapping relationship between input and output. A small signal stability analysis model is established to assess the minimum damping ratio of the system, and the influence of noise on the accuracy of assessment results is also considered. The damping ratio sensitivity of generator is estimated based on LightGBM method, and the approximate sensitivity optimization model of the generator damping ratio is established when the system is weakly damped. The outputs of generators are adjusted according to the optimization model to correct the minimum damping ratio to enhance the system’s stability and finally estimate the modified minimum damping ratio by LightGBM algorithm. Test results on 3-machine 9-node and 10-machine 39-node systems indicate that the proposed method is hardly prone to over-fitting under noise interference with better robustness and could maintain better performance in assessing and correcting the small signal stability of the power system.
The influence of small-signal stability on the safety and stability of the power system is becoming more prominent. A mapping model based on steady-state operation information is established using ...the sample learning method, which provides a new technical path for the rapid assessment and correction of significant power grid oscillation characteristics. This paper establishes a small signal stability assessment and correction control model based on the Extreme Gradient Boosting (XGBoost) algorithm. Firstly, the XGBoost model is obtained by analyzing the mapping relationship between generator power, node power, branch power, and minimum damping ratio. Then, the sensitivity of the generator damping ratio is calculated, and the objective is to minimize the active power adjustment amount of the generator. The stability constraint and power balance are the constraint conditions to establish the optimization correction model, obtain the optimal adjustment amount, correct the minimum damping ratio, and improve the system’s stability. Finally, the minimum damping ratio after correction is obtained, and the modified damping ratio is estimated by XGBoost algorithm. The performance of the proposed model is verified in IEEE 3-machine 9-node and 10-machine 39-node systems.
The essence of traditional power system’s small signal stability analysis model using the eigenvalue analysis method is to analyze the time-invariant system obtained after the approximate ...linearization of the system, because it only considers the equilibrium state and therefore cannot consider the power system nonlinearity. In contrast, time-domain simulation can fully consider the system nonlinearity from the whole small signal dynamic period, because it considers not only the equilibrium state but also the state after the equilibrium point. On the basis of the time-domain simulation idea, this paper proposes an SSSC-OPF (small signal stability constrained-optimal power flow) based on optimizing the rotor angle trajectory. The objective function and the SSS constraint (small signal stability constraint) of the model are extracted from rotor angle curves of each generator, and the system stability is ensured by both in concert. Compared with the general SSSC-OPF model using the SSS constraint based on the eigenvalues, the proposed model can consider nonlinearity while avoiding the errors caused by the approximate linearization in the general SSSC-OPF model, and has a higher degree of generalizability. Finally, this paper performs the simulations in three test systems, the IEEE 9-bus test system, the IEEE 39-bus test system, and the IEEE 118-bus test system, and verifies the proposed model’s effectiveness by comparing the simulation results.
The Unit Commitment problem (UC) is a complex mixed-integer nonlinear programming problem, so the main challenge faced by many researchers is obtaining the optimal solution. Therefore, this ...dissertation proposes a new methodology combining the multi-dimensional firefly algorithm with local search called LS-MFA and utilizes it to solve the UC problem. In addition, adaptive adjustment, tolerance mechanism, and pit-jumping random strategy help to improve the optimal path and simplify the redundant solutions. The experimental work of unit commitment with the output of 10–100 machines in the 24-hour period is carried out in this paper. And it shows that compared with the previous UC artificial intelligence algorithms, the total cost obtained by LS-MFA is less and the results are excellent.
This paper presents a new metaheuristic optimization algorithm, the firefly algorithm (FA), and an enhanced version of it, called chaos mutation FA (CMFA), for solving power economic dispatch ...problems while considering various power constraints, such as valve-point effects, ramp rate limits, prohibited operating zones, and multiple generator fuel options. The algorithm is enhanced by adding a new mutation strategy using self-adaptation parameter selection while replacing the parameters with fixed values. The proposed algorithm is also enhanced by a self-adaptation mechanism that avoids challenges associated with tuning the algorithm parameters directed against characteristics of the optimization problem to be solved. The effectiveness of the CMFA method to solve economic dispatch problems with high nonlinearities is demonstrated using five classic test power systems. The solutions obtained are compared with the results of the original algorithm and several methods of optimization proposed in the previous literature. The high performance of the CMFA algorithm is demonstrated by its ability to achieve search solution quality and reliability, which reflected in minimum total cost, convergence speed, and consistency.
Recently, subsynchronous resonance (SSR) in HVDC transmission is considered to be related to electronic converter equipment and complex control systems. Aiming at the subsynchronous resonance problem ...caused by frequent topology changes of AC–DC systems, this paper firstly proposes an impedance-frequency characteristic analysis method based on Thevenin Equivalent and Fast Fourier Transform (FFT) algorithm. This method is used to analyze the impedance frequency characteristics of AC–DC systems after the bypass damping filter (BDF) is configured. Firstly, based on the IEEE first benchmark model, the mechanism of BDF in suppressing subsynchronous resonance is explained by quantitative analysis, and the BDF parameter setting method is proposed. Then, the time domain simulation model of a single-machine HVDC system with BDF is established in PSCAD/EMTDC. Finally, according to Thevenin’s theorem, the equivalent structure of each subsystem is simplified, and the FFT algorithm is used to solve the harmonic equivalent impedance of each subsystem. After BDF is configured, the mechanical resonance frequency ”transfers” from 16Hz to 10Hz, and the minimum electrical damping changes from -0.9637 to -0.4581. The results show that the BDF configuration can change the impedance-frequency characteristics of the system, thereby improving the electrical damping in the torsional vibration mode in a targeted manner, and has a certain effect on suppressing the subsynchronous resonance of AC–DC systems.
Power system stabilizer (PSS) is widely used to improve power system stability. The current parameter coordination optimization method is easy to fall into the local optimization, to solve the ...problem and find the optimal parameter combination of PSS, the sample screening method based on the similarity index of power system state (SIPSS) and BP neural network is proposed for global optimization parameters of PSS. The SIPSS screening method uses a similar metric index of the grid state variable as the criterion to screen out the required samples. The BP neural network fits the predicted and expected values of the minimum damping ratio of the system after random fluctuations of PSS parameters under various operating modes to minimize the mean square deviation by fitting the streamlined training samples. Firstly, the SIPSS-BP neural network model is obtained by analyzing the mapping relationship between generator power, node power, branch power, and minimum damping ratio. Then, the sensitivity of the PSS parameters damping ratio is calculated, and the PSS parameter optimization model is established. The optimal adjustment of the PSS parameter is obtained, and the minimum damping ratio is modified to improve the system’s stability. Finally, the minimum damping ratio after correction is obtained. The test results of the SIPSS-BP network with the IEEE 3-machines and 9-nodes show that the method can achieve good prediction accuracy, the parameter optimization effect of PSS can be remarkable, and the stability of the power system has been greatly improved.
To deal with the high dimensionality and computational density of the Optimal Power Flow model with Transient Stability Constraints (OTS), a credible criterion to determine transient stability is ...proposed based on swing curves of generator rotor and the characteristics of transient stability. With this method, the swing curves of all generator rotors will be independent one another. Therefore, when a parallel computing approach based on the MATLAB parallel toolbox is used to handle multi-contingency cases, the calculation speed is improved significantly. Finally, numerical simulations on three test systems including the NE-39 system, the IEEE 300-bus system, and 703-bus systems, show the effectiveness of the proposed method in reducing the computing time of OTS calculation.
This paper presents a method to analyze the Sub Synchronous Oscillation (SSO) problem based on broad learning system (BLS), which can quickly analyze the risk of SSO in a system and take measures. ...The simulation system is constructed by the eigenvalue analysis method to obtain training data, that solves the problem which is difficult to obtain actual data in SSO problem and makes the model more accurate and the conclusion more convincing. Subsequently, BLS is applied for feature extraction and the prediction model is constructed, the model can show the deep relationship between the oscillation source and topology of the system as well as various operating data, which is difficult to be expressed by formula. The system was tested and validated in the 41-bus system. The feature importance analysis method which comes from eXtreme Gradient Boosting (XGboost) algorithm is proposed and combined with the BLS prediction model, which can analyze the influence of each variable on the prediction results in different series compensation levels, and is validated in the 41-bus system, that makes the results of prediction more interpretable. Finally, the results of simulation show that the model can predict data with high accuracy and give adjustment plans for effective control of the system to avoid the risk of SSO.
With the rapid increase of penetration level of new energy power generation, the construction of auxiliary service market is facing new challenges. The stricter requirements of the power plant unit ...AGC are proposed by the power system. How to coordinate and control the output of hydropower and thermal power units to increase the use of hydropower while meeting the requirements of AGC regulation is a problem to be solved. Under the condition of interconnection of units in the whole network, an optimal control strategy for joint commissioning of hydropower and thermal power plants that meets the performance conditions of ‘two rules’ is proposed in this paper. The strategy establishes the connection between hydropower and thermal power units. Combined with the output characteristics and economic characteristics of hydropower units and thermal power units, a coordinated optimization control strategy model of hydropower and thermal power AGC units suitable for the ’two rules’ assessment rules is proposed for each objective and constraint condition in the joint scheduling of hydropower and thermal power. The optimal mathematical model with multiple objectives is constructed to realize the distribution of AGC among different types of power plants and units, which can give full play to the regulation ability of hydropower and thermal power. The proposed strategy achieves the efficient use of clean energy and reduces the grid’s overall operating costs to achieve energy conservation and emission reduction. Simulation results verify the superiority of the proposed strategy.
PDF
