S. Sivasakthi, R. K. Santhi, N. Murali Krishnan, S. Ganesan, S. Subramanian,
Volume 13, Issue 2 (6-2017)
Abstract
The increasing concern of global climate changes, the promotion of renewable energy sources, primarily wind generation, is a welcome move to reduce the pollutant emissions from conventional power plants. Integration of wind power generation with the existing power network is an emerging research field. This paper presents a meta-heuristic algorithm based approach to determine the feasible dispatch solution for wind integrated thermal power system. The Unit Commitment (UC) process aims to identify the best feasible generation scheme of the committed units such that the overall generation cost is reduced, when subjected to a variety of constraints at each time interval. As the UC formulation involves many variables and system and operational constraints, identifying the best solution is still a research task. Nowadays, it is inevitable to include power system reliability issues in operation strategy. The generator failure and malfunction are the prime influencing factor for reliability issues hence they have considered in UC formulation of wind integrated thermal power system. The modern evolutionary algorithm known as Grey Wolf Optimization (GWO) algorithm is applied to solve the intended UC problem. The potential of the GWO algorithm is validated by the standard test systems. Besides, the ramp rate limits are also incorporated in the UC formulation. The simulation results reveal that the GWO algorithm has the capability of obtaining economical resolutions with good solution quality.
B. Mamipour Matanag, N. Rostami, S. Tohidi,
Volume 17, Issue 2 (6-2021)
Abstract
This paper proposes a new method for direct control of active power and stator flux of permanent magnet synchronous generator (PMSG) used in the wind power generation system. Active power and stator flux are controlled by the proposed discrete time algorithm. Despite the commonly used vector control methods, there is no need for inner current control loops. To decrease the errors between reference and measured values of active power and stator flux, the space vector modulation (SVM) is used, which results in a constant switching frequency. Compared to vector control, the proposed direct control method has advantages such as higher dynamic response due to elimination of inner current control loops and no need to coordinate system transformation blocks as well as the PI controllers and their adjustment. Moreover, permanent magnet flux vector and several machine parameters such as stator inductances are not required which can improve the robustness of the control system. The proposed method can be used in both types of surface-mounted and interior PMSGs. The effectiveness of the proposed method in comparison to the vector control method with optimized PI coefficients by the particle swarm algorithm is evaluated. Simulation results performed in MATLAB/Simulink software show that higher dynamic response with lower active power and the stator flux ripple are achieved with the proposed method.
