scholarly journals A Novel Model Predictive Control for Stability Improvement of Small Scaled Zero-inertia Multiple DGs Micro-grid

2022 ◽  
Author(s):  
Abdulrahman J. Babqi
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Strategy ◽  
Frequency Regulation ◽  
Small Scale ◽  
Power Sources ◽  
Control Approach ◽  
Islanded Mode ◽  
Micro Grid ◽  
Virtual Inertia

A zero-inertia micro-grid is a power system consisting of multiple renewable energy power sources and energy storage systems without the presence of conventional synchronous generators. In such a system, a large variation of the load or source sides during the islanded mode of operation extremely degrades the micro-grid's voltage and frequency stability. This study presents a virtual inertia-based predictive control strategy for a small-scale zero-inertia multiple distributed generators (DGs) micro-grid. In islanded mode, Voltage Model Predictive Control (VMPC) was implemented to control and maintain the voltage and frequency of the micro-grid. However, instabilities in frequency and voltage may rise at the Point of Common Coupling (PCC) due to large variations at both source and load sides. Therefore, the proposed virtual inertia loop calculates the amount of active power to be delivered or absorbed by each DG, and its effect is reflected in the estimated d current component of the VMPC, thus providing better frequency regulation. In grid-connected mode, Direct Power Model Predictive Control (DPMPC) was implemented to manage the power flow between each DG and the utility grid. The control approach also enables the DG plug and play characteristics. The performance of the control strategy was investigated and verified using the PSCAD/EMTDC software platform.

scholarly journals A Model Predictive Control Strategy for Distribution Grids: Voltage and Frequency Regulation for Islanded Mode Operation

Energies ◽  
2020 ◽  
Vol 13 (10) ◽  
pp. 2637 ◽  
Author(s):  
Giulio Ferro ◽  
Michela Robba ◽  
Roberto Sacile
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Distribution Systems ◽  
Large Scale ◽  
Reactive Power ◽  
Wind Farms ◽  
Local System ◽  
Frequency Regulation ◽  
Renewable Sources ◽  
Islanded Mode

In the last few years, one of the most important challenges of power technologies has been the integration of traditional energy production systems and distributed energy resources. Large-scale photovoltaic systems and wind farms may decrease the quality of the electrical grid service, mainly due to voltage and frequency peaks and fluctuations. Besides, new functionalities, such as the operation in islanded mode of some portions of the medium-voltage grid, are more and more required. In this respect, a model predictive control for voltage and frequency regulation in interconnected local distribution systems is presented. In the proposed model, each local system represents a collection of intelligent buildings and microgrids with a large capacity in active and reactive power regulation. The related model formalization includes a linear approximation of the power flow equations, based on stochastic variables related to the electrical load and to the production from renewable sources. A model predictive control problem is formalized, and a closed-loop linear control law has been obtained. In the results section, the proposed approach has been tested on the Institute of Electrical and Electronics Engineers(IEEE) 5 bus system, considering multiple loads and renewable sources variations on each local system.

Model predictive control approach for frequency and voltage control of standalone micro-grid

2018 ◽  
Vol 12 (14) ◽  
pp. 3405-3413 ◽  
Author(s):  
Vidyasagar Puvvula Sri Rama Venkata Ranga Sai Sesha ◽  
Shanti Swarup Kesanakurthy
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Voltage Control ◽  
Control Approach ◽  
Micro Grid

Model predictive control-based control strategy to reduce driving-mode switching times for parallel hybrid electric vehicle

2020 ◽  
pp. 014233122094971
Author(s):  
Jiangtao Fu ◽  
Zhumu Fu ◽  
Shuzhong Song
Keyword(s):  
Markov Chain ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Control Strategy ◽  
Driving Cycle ◽  
Mode Switching ◽  
Power Sources ◽  
The Real ◽  
Driving Mode ◽  
Switching Times

Multi-power sources are included in hybrid electrical vehicles, which leads to multi-driving modes co-existing when driving the vehicle. However, the frequent driving mode switching (DMS) will probably need the engine to be started frequently, which can result in extra fuel consumption. So, avoiding unnecessary DMS should be fully considered when designing the control strategy. For solving this problem, a model predictive control (MPC) strategy integrating Markov chain driving intention identification is put forward. First, the component models of the powertrain system are established. Second, according to the real driving cycle data, a driving intention model based on the Markov chain is designed according to the real driving cycle data. Then the MPC-based control strategy aiming at reducing DMS times is proposed by integrating the cost of DMS. Finally, the proposed control strategy is contrasted with three other control strategies to verify its validity in reducing the mode switching times and improving the fuel economy.

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