Frequency Stability Control In Low -Inertia Power System Using Virtual Synchronous Generator

The stability of the electric power system is divided into transient stability, steady state stability and dynamic stability. Things that affect the performance of the generator include the addition of generators, changes in the load that vary in the system which have an impact on system stability and the distance between the generator and the load. The addition of a Virtual Synchronous Generator (VSG) is needed to improve the power system that is integrated with Renewable Energy Systems Source in maintaining system stability. When the integration between conventional generators and Renewable Energy Systems Source without Virtual Synchronous Generator (VSG) has a frequency response of 58.2 Hz when the generating capacity is -40% of the initial state, while integration between conventional generators and Renewable Energy Systems Source with Virtual Synchronous Generator (VSG) has a steady state response of 60 Hz even though the generating condition is 40% of the initial capacity of the generator. This means that the Virtual Synchronous Generator (VSG) can stabilize the return frequency in its nominal value on the system. Keywords : Inertia, Conventional Generating, Renewable Energy Systems Source, Virtual Synchronous Generator (VSG). &nbsp

Neural Network Predictive Controller for Grid-Connected Virtual Synchronous Generator

In this paper, a neural network predictive controller is proposed to regulate the active and the reactive power delivered to the grid generated by a three-phase virtual inertia-based inverter. The concept of the conventional virtual synchronous generator (VSG) is discussed, and it is shown that when the inverter is connected to non-inductive grids, the conventional PI-based VSGs are unable to perform acceptable tracking. The concept of the neural network predictive controller is also discussed to replace the traditional VSGs. This replacement enables inverters to perform in both inductive and non-inductive grids. The simulation results confirm that a well-trained neural network predictive controller illustrates can adapt to any grid impedance angle, compared to the traditional PI-based virtual inertia controllers.Comment: NAPS 2019 Conferenc

Improvement of Frequency Regulation in VSG-Based AC Microgrid via Adaptive Virtual Inertia

A virtual synchronous generator (VSG) control based on adaptive virtual inertia is proposed to improve dynamic frequency regulation of microgrid. When the system frequency deviates from the nominal steady-state value, the adaptive inertia control can exhibit a large inertia to slow the dynamic process and, thus, improve frequency nadir. And when the system frequency starts to return, a small inertia is shaped to accelerate system dynamics with a quick transient process. As a result, this flexible inertia property combines the merits of large inertia and small inertia, which contributes to the improvement of dynamic frequency response. The stability of the proposed algorithm is proved by Lyapunov stability theory, and the guidelines on the key control parameters are provided. Finally, both hardware-in-the-loop and experimental results demonstrate the effectiveness of the proposed control algorithm

Coordinated Damping Control Design for Power System With Multiple Virtual Synchronous Generators Based on Prony Method

With more renewables integrated into power grids, the systems are being transformed into low inertia power electronic dominated systems. In this situation, the virtual synchronous generator (VSG) control strategy was proposed to deal with insufficient inertia challenge caused by the reduction of synchronous generation. However, as the VSG control method emulates the dynamic behavior of traditional synchronous machines, the interaction between multiple VSG controllers and synchronous generators (SGs) may cause low-frequency oscillation similar to that caused by the interaction between multiple SGs. This paper reveals that the system low-frequency oscillatory modes are affected by multiple VSGs. Then Prony analysis is utilized to extract the system mode information which will be subsequently used for VSG controller design, and a decentralized sequential coordinated method is proposed to design the supplementary damping controller (SDC) for multiple VSGs. The system low-frequency oscillation is first analyzed based on a modified two-area system with a linearized state-space model, and a further case study based on a revised New England 10-machine 39-bus system is used to demonstrate the effectiveness of the proposed coordinated method for multiple VSGs

Virtual Inertia: Current Trends and Future Directions

The modern power system is progressing from a synchronous machine-based system towards an inverter-dominated system, with large-scale penetration of renewable energy sources (RESs) like wind and photovoltaics. RES units today represent a major share of the generation, and the traditional approach of integrating them as grid following units can lead to frequency instability. Many researchers have pointed towards using inverters with virtual inertia control algorithms so that they appear as synchronous generators to the grid, maintaining and enhancing system stability. This paper presents a literature review of the current state-of-the-art of virtual inertia implementation techniques, and explores potential research directions and challenges. The major virtual inertia topologies are compared and classified. Through literature review and simulations of some selected topologies it has been shown that similar inertial response can be achieved by relating the parameters of these topologies through time constants and inertia constants, although the exact frequency dynamics may vary slightly. The suitability of a topology depends on system control architecture and desired level of detail in replication of the dynamics of synchronous generators. A discussion on the challenges and research directions points out several research needs, especially for systems level integration of virtual inertia systems

Dual Heuristic Dynamic Programing Control of Grid-Connected Synchronverters

A new approach to control a grid-connected synchronverter by using a dual heuristic dynamic programing (DHP) design is presented. The disadvantages of conventional synchronverter controller such as the challenges to cope with nonlinearity, uncertainties, and non-inductive grids are discussed. To deal with the aforementioned challenges a neural network–based adaptive critic design is introduced to optimize the associated cost function. The characteristic of the neural networks facilitates the performance under uncertainties and unknown parameters (e.g. different power angles). The proposed DHP design includes three neural networks: system NN, action NN, and critic NN. The simulation results compare the performance of the proposed DHP with a traditional PI-based design and with a neural network predictive controller. It is shown a well-trained DHP design performs in a trajectory, which is more optimal compared to the other two controllers

Consensus Based Control Strategy for Virtual Synchronous Generators in Microgrids

Renewable energy sources such as photo-voltaic and wind energy are integrating very rapidly in power systems. These energy-based systems typically adopt power-electronic interfaced inverters to connect to the grid. However, unlike traditional generators, these sources have low inertia, resulting in system stability issues, especially in microgrids where they are the primary sources. To mitigate the low-inertia effect, the inverters are modeled as virtual synchronous generators (VSG), and their control is designed. The VSG emulates the inertia effect of the synchronous generator and maintains the stability of the system. Even though the droop control provides the primary control, it is insufficient due to the high variability of the power electronics in inverter systems. Hence, optimal and efficient power-sharing among distributed generators (DGs) is needed through secondary control. The consensus-based algorithm is proposed in this thesis to overcome the control challenges of inverters in a microgrid to obtain control under fast-changing system conditions and unbalanced scenarios. The developed controller is tested on microgrid systems through simulations in MATLAB/Simulink, and the performance is compared with other controllers and with just the primary controller