Large-scale Interconnected Power Grid Research Articles

Development of a DSP based collaborative computing platform for power system

Abstract With the advancement of information technology, there has been tremendous progress in data production, processing, and storage technology, especially in data processing technology. With the rapid development of the power grid, its operation has become more intelligent and efficient. Traditional power system simulation and analysis tools have disadvantages, such as slow message transmission and the inability to share data, which cannot meet the requirements of modern power system simulation calculations. DSP was introduced and developed by the Southern Power Grid Research Institute and can perform various simulation calculations such as transient stability calculation, power flow calculation, and short circuit calculation. It is widely used in departments such as power planning and design. However, the data calculated by DSP is input through a data card, which is cumbersome and difficult to manage. In order to meet the new requirements of power system simulation analysis, a power system collaborative computing platform has been developed based on DSP, which makes DSP data maintenance and management more efficient and intuitive. It comprehensively improves the efficiency of power grid planning work. This article provides a detailed analysis of the architecture design and application problems of the power system collaborative computing platform, clarifies the requirements of large-scale interconnected power grids for simulation computing data management, and proposes solutions that can meet the needs of simulation computing data management in China’s power grid from two aspects: key data architecture issues and software architecture technology.

Dynamic Analysis and Suppression Strategy Research on a Novel Fractional-Order Ferroresonance System

Ferroresonance is characterized by overvoltage and irregular operation in power systems, which can greatly endanger system equipment. Mechanism analysis of the ferroresonance phenomenon depends mainly on model accuracy. Due to the fractional-order characteristics of capacitance and inductance, fractional-order models are more universal and accurate than integer-order models. A typical 110 kV ferroresonance model is first established. The influence of the excitation amplitude on the dynamic behavior is analyzed. The fractional-order ferroresonance model is then introduced, and the effects of the fractional order and flux-chain order on the system’s motion state are studied via bifurcation diagrams and phase portraits. In order to suppress the nonlinear dynamic behavior of fractional-order ferroresonance systems, a novel fractional-order fast terminal sliding mode control method based on finite-time theory and the frequency distributed model is proposed. A new fractional-order sliding mode surface and control law using a saturation function are developed. A robust fractional-order sliding mode controller could achieve finite-time stabilization and tracking despite model uncertainties and external disturbances. Compared with conventional sliding mode methods, the simulation results highlight the effectiveness and superiority. The research provides a theoretical basis for ferroresonant analysis and suppression in large-scale interconnected power grids.

Transient Stability Impact of Short Circuit Fault System Based on SVC And PSS Applications

Researchers are currently focusing on two solutions, namely Static VAR compensator (SVC) and power system stabilizer (PSS), to address different power system stability issues in large area interconnected power grids. To enhance transient stability, researchers have suggested a combined approach involving SVC and PSS. In this method, SVC and PSS coordinate and cooperate with each other to provide better stability assurance. To verify the feasibility of this method, simulation experiments were conducted using MATLAB. Simulated the situation of single-phase ground fault, two-phase ground fault, and three-phase ground fault in the power system, and tested the effectiveness of SVC and PSS respectively. The simulation results show that the combined use of SVC and PSS can significantly improve the transient stability of power systems and effectively reduce the impact of faults on the system. In summary, the combined use of SVC and PSS can effectively solve various power system stability issues that may arise in large-scale interconnected power grids. By conducting simulation experiments in MATLAB, researchers have verified the feasibility of this method under different fault conditions, providing strong support for practical applications.

A Distributed Dynamic Power Flow Algorithm for an Interconnected System Containing Two-Terminal LCC-HVDC Tie-Line

In China, a growing number of regional power grids are interconnected by the line-commutated converter based high voltage direct current (LCC-HVDC) tie-line, forming a large-scale interconnected power grid. As the operation and control of the interconnected power grid are undertaken by multiple control centers, there is a demand for a distributed alternating current (AC)/direct current (DC) power flow algorithm. In this paper, a distributed power flow algorithm considering the LCC-HVDC tie-line is implemented based on the existing work of the author. The paper proposed some technologies to implement the algorithm. In the fixed-point iteration scheme of this paper, the combined boundary bus states are used to calculate the power flow of the DC system, thus the coordination of discrete state variables of the DC system is avoided. Also, the idea that converting the DC tie-line to an AC line is proposed to calculate the extended WARD equivalent of the external network of subsystems. Moreover, the unbalanced power distribution method is improved to make it more in line with the practical situation. Tests were carried out on the IEEE 118-bus system and an interconnected power grid constructed by six IEEE 118-bus systems, the correctness and effectiveness of the algorithm were proved.

Extracting Spatial-Temporal Characteristics of Frequency Dynamic in Large-Scale Power Grids

In large-scale interconnected power grids, the frequency dynamic response exhibits temporal-spatial distribution characteristics, of which the internal mechanism is not clear. In this paper, we use a statistical-model-based method to analyze the propagation characteristic of frequency dynamic behavior. The frequency data collected from the wide area measurement system are decomposed into standing and traveling wave components with complex empirical orthogonal function, while the information reflecting the spatial-temporal features of frequency dynamics is also obtained in the process. An index is defined to gauge the travelling wave and standing wave components, and the distribution of propagation speed in the entire grid is estimated by the bicubic interpolation method. Finally, the proposed method is applied in a standard test system as well as a real power system to validate its effectiveness. This work explores the mechanism of frequency dynamic in large-scale power grids from a novel view point.

A Fast and Robust Linear State Estimator for Very Large Scale Interconnected Power Grids

This paper presents a computationally efficient and statistically robust linear state estimator for very large scale interconnected power grids that are made observable by synchronized phasor measurements. The developed estimator has some desirable properties such as robustness against gross errors in phasor measurements (bad data), computational performance that remains minimally affected by growing system size or bad data as long as the size of the largest control area remains bounded, and the fact that independent system operators associated with control areas do not have to share majority of their real-time data or measurements while the estimator solves for the entire system. The estimator is implemented and tested on a small (30-bus) and a large (2917-bus) utility test systems and results are provided.

Adaptive control method for chaotic power systems based on finite-time stability theory and passivity-based control approach

Chaotic oscillation in a power system is considered the main cause of power blackouts in large-scale interconnected power grids. The chaotic oscillation mechanisms and the control methods for chaos oscillation of power systems need to be analyzed. This paper thus proposed an adaptive control method for chaotic power systems using finite-time stability theory and passivity-based control approach. The adaptive feedback controller is first constructed using the finite-time stability theory and the passive theory to make the chaotic power system equivalent to a closed-loop passive system. We then proved that the passive power system can stabilize the equilibrium points. We also extensively studied fourth-order power system. Results show that the controller based on the finite-time theory and the passivity-based control approach can effectively stabilize the chaotic behavior within finite time. The control strategy was also found to be robust to the different power system states.

Artificial emotional reinforcement learning for automatic generation control of large‐scale interconnected power grids

This study proposes an artificial emotional reinforcement learning (ERL) controller for automatic generation control (AGC) of large-scale interconnected power grids. In the scheme of ERL, the agent consists of two parts, a mechanical logical part and a humanistic emotional part, which essentially develop the control strategies of the agent. These two parts in proposed controller are introduced by reinforcement learning (RL) and artificial emotion (AE), respectively. The ERL controller can generate different control strategies depending on the operating scenarios, by highly integrating AE functions, which are quadratic function, exponential function, and linear function, respectively, with the elements of RL, such as action, learning rate, and reward function. The effectiveness of ERL controller with nine control strategies has been demonstrated considering AGC on a two-area load frequency control power system and China Southern Power Grid (CSG) power system. Results of simulation show the superior performance of ERL over that of proportional-integral control and four RL techniques.

Probabilistic stability analysis of low frequency oscillation of large-scale interconnected power grid based on the theory of point estimation method and risk assessment

Probabilistic stability analysis of low frequency oscillation of large-scale interconnected power grid based on the theory of point estimation method and risk assessment

Research on forced oscillations disturbance source locating through an energy approach

Summary Low-frequency oscillations (LFOs) are inherent phenomena of modern interconnected electrical power systems, essentially caused by the continuous exchange of momentum among rotating masses. It is widely recognized that LFOs can be induced by both the occurrence of multiple disturbances and the existence of periodic disturbance sources. LFOs can be classified into negative damped oscillations and forced power oscillations. The former can be suppressed by standard controllers (e.g., power system stabilizers). The latter cannot be eliminated until the disturbance source is removed or isolated. Thus, locating the forced disturbance source promptly and accurately is crucial. In this paper, a traditional energy function, simplified and improved, with a new decomposition way to show the direction of energy flow is proposed. Energy associated with the LFO is decomposed into oscillating component and quasi-steady component at the aim of analyzing the inducing multiple disturbances. The branch energy is hence decomposed into periodic and aperiodic components. By identifying the direction along which the aperiodic component is propagated and dissipated, the periodic forced disturbance source could be located rapidly and accurately. The proposed energy decomposition method provides a novel idea to judge the direction along which the dissipated energy flows. The effectiveness and feasibility of the proposed method were verified by simulation results obtained on an actual large-scale interconnected power grid in China. Copyright © 2015 John Wiley & Sons, Ltd.

Forewarned Is Forearmed: An Automated System for Remedial Action Schemes

The integrity of large-scale interconnected power grids may break down under system disturbances. The postdisturbance system may even turn out to cause a major blackout. To mitigate the undesired impacts of system disturbances, special protection systems (SPSs), also known as remedial action schemes (RASs), are widely used in modern power grids to safeguard their integrity.

Chaotic control of the interconnected power system based on the relay characteristic function

Chaotic oscillation in a power system is very harmful for the large-scale interconnected power grid. Here, the basic dynamic properties of the interconnected power system are investigated under the disturbance of electromagnetic power through the Lyapunov exponent spectrum, bifurcation diagram, phase plane, and power spectrum. The sensitivity to the disturbance of electromagnetic power is also studied. Meanwhile, from the sliding mode variable structure control and relay characteristic function, a new method to control the chaotic oscillation is presented, which can quickly and smoothly make the system reach the expected target. Simulation results show that the method can not only shorten the control time, but also reduce the possibility of the impulse response from the system, due to the large parameters. It can inhibit the high-frequency buffeting effectively and has strong robustness.

Fuzzy fast terminal sliding mode controller using an equivalent control for chaotic oscillation in power system

Chaotic oscillation in a power system is taken to be the main cause for power blackouts in large-scale interconnected power grid. This paper studies a 2-D power system with chaotic oscillation dynamic behaviors through parameter phase portraits, Lyapunov exponents, time-domain waveform graph and proposes fuzzy fast terminal sliding mode controller based on equivalent control to stabilize the power system to synchronization status. Simulation results show that our control scheme can not only speed up convergence rate, but also have smooth control action, reduce control energy and suppress chattering phenomenon effectively.

The decomposition and computation method for distributed optimal power flow based on message passing interface (MPI)

This paper investigates the decomposition and computation method for the distributed optimal power flow (DOPF) based on message passing interface (MPI) framework in large-scale interconnected power grids. Firstly, a DC-DOPF model and an AC-DOPF model are introduced respectively. Next, a new equivalent decomposition model to be used to solve DC-DOPF and AC-DOPF is proposed. It decomposes the OPF computation of large power grid into the sub-problems of interconnected multiple regions. Then, two different decomposition methods, i.e., partial duality and auxiliary problem principle (APP), are used to solve interconnected DC-DOPF and AC-DOPF, respectively. DC-DOPF and AC-DOPF are modeled as multiple base-cases OPF to get the runtime status in real time. Finally, several experiments are implemented based on multiple interconnected IEEE RTS-96 regions and IEEE 118 test regions. The computational results illustrate that the proposed decomposition and computation methods for DOPF based on MPI are applicable and effective, and it can be as a useful computation method for interconnected power system.

Supplementary Damping Controller Design using Direct Heuristic Dynamic Programming in Complex Power Systems

In modern, large scale interconnected power grids, low-frequency oscillation is a key roadblock to improved power transmission capacity. Supplementary generator control, flexible AC transmission system (FACTS), and high voltage direct currents (HVDC) are engineered devices designed to damp such low frequency swings. In this paper a neural network-based approximate dynamic programming method, namely direct heuristic dynamic programming (direct HDP), is applied to power system stability enhancement. Direct HDP is a learning and approximation based approach to addressing nonlinear system control problems under uncertainty, and it is also a model-free design strategy. The action and critic networks of the direct HDP are implemented using multi-layer perceptrons; learning is carried out based on the interactions between the controller and the power system. For this design approach, real time system responses are provided through wide-area measurement system (WAMS). The controller learning objective is formulated as a reward function that reflects global characteristics of the power system under low frequency oscillation, as well as tight coupling effects among system components. Direct HDP control design is illustrated by case studies, which are also used to demonstrate the learning control performance. The proposed direct HDP learning control is also developed as a new solution to a large scale system coordination problem by using the China Southern Power Grid as a major test bed.