Power systems
Abbas-Ali Zamani
Abstract
The large-scale integration of renewable generation into microgrids can lead to decreased inertia, resulting in high rates of change of frequency and frequency instability. This issue is even more complex in islanded MGs that incorporate a high proportion of RGs and need to deliver power to loads in ...
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The large-scale integration of renewable generation into microgrids can lead to decreased inertia, resulting in high rates of change of frequency and frequency instability. This issue is even more complex in islanded MGs that incorporate a high proportion of RGs and need to deliver power to loads in islanded mode. To address this problem, a virtual inertia control scheme can be employed to enhance system inertia and maintain frequency stability. In this article, we propose a novel control strategy named the optimal nonlinear fractional-order PI-based virtual inertia controller, which integrates a nonlinear fractional-order PI controller into the conventional VIC loop. The designed ONFOPI+VI controller, which considers both inertia and damping properties, is optimized using the Coot optimization algorithm. Furthermore, an alternative control methodology, denoted as OFOPI+VI, has been developed to analyze and evaluate the outcomes obtained from the proposed ONFOPI+VI control structure. This paper compares the performance of the proposed ONFOPI+VI strategy to that of the OFOPI+VI and other VIC techniques for different RG and load variations under various scenarios. Simulation results and detailed analyses confirmed that the ONFOPI+VI controller significantly outperformed conventional methods, yielding at least a 30% improvement in IAE and a 20% improvement in ITAE compared to other control techniques.
Control
Morteza Janfaza; Abbas-Ali Zamani
Abstract
A new framework for controlling load frequency in a complex, interconnected power system with multiple sources has been developed. This framework combines a fuzzy logic controller (FLC) and a tilted integral derivative (TID) controller, creating a self-tuning fuzzy tilted integral derivative (STFTID) ...
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A new framework for controlling load frequency in a complex, interconnected power system with multiple sources has been developed. This framework combines a fuzzy logic controller (FLC) and a tilted integral derivative (TID) controller, creating a self-tuning fuzzy tilted integral derivative (STFTID) controller. The purpose of this controller is to conduct and reduce load frequency perturbations during the operation of a multi-area interconnected multi-source power system. The STFTID controller is optimized using a particle swarm optimization algorithm to minimize the frequency fluctuations effectively. Investigations of the proposed STFTID controller were performed for power systems with generation units of a conventional system and renewable energy sources. In the design process of the STFTID controller, various nonlinearities, uncertainties, and fluctuations are considered to simulate practical challenges. These challenges include generation rate constraints, governor deadband, and communication time delays (as the sources of nonlinearity), as well as fluctuations caused by step load switching and the connection of renewable power plants to the system. The STFTID controller is compared with the proportional integral derivative (PID), titled integral derivative (TID), and integral tilted-derivative (I-TD) controllers. Simulation results show that the developed STFTID controller significantly enhances the system frequency control under various applied conditions, including multi-step load perturbation, renewable power plant integration, communication time delays, and generation rate constraints.
Control
Mohammad Shahi; Mohammad Reza Sohrabi; Sadegh Etedali; Abbas-Ali Zamani
Abstract
This research proposes an innovative process to locate devices in elevation using structural results in uncontrolled and controlled (passive and active) states, considering Soil-Structure Interaction (SSI) effects, especially for soft soil. Also, a Proportional Integral Derivative (PID) controller with ...
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This research proposes an innovative process to locate devices in elevation using structural results in uncontrolled and controlled (passive and active) states, considering Soil-Structure Interaction (SSI) effects, especially for soft soil. Also, a Proportional Integral Derivative (PID) controller with active single and multiple control devices is used for tall buildings under earthquakes. In addition, the simultaneous and non-simultaneous tuning of the design parameters are examined. The results of applying PID with a Multiple Active Tuned Mass Damper (MATMD) compared with the Single-Active Tuned Mass Damper (SATMD) show that the proposed process of locating the control devices reduces responses significantly. It also reduces the computational efforts of the optimization noticeably. The results of the non-simultaneous tuning of design parameters in all states also indicate an increase in the instability potential of the structure compared with simultaneous tuning. On the other hand, the reduction of the Root Mean Square (RMS) of the responses compared with the uncontrolled state confirms the effective performance of the system during earthquakes. Therefore, this research helps researchers gain a new design vision of how to locate control devices in tall buildings without optimization calculations and how to set parameters in the presence of SSI effects.
Power systems
Mehdi Shafiee; Abbas-Ali Zamani; Mehdi Sajadinia
Abstract
In power systems planning, economic load dispatch considering the uncertainty of renewable energy sources is one of the most important challenges that researchers have been concerned about. Complex operational constraints, non-convex cost functions of power generation, and some uncertainties make it ...
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In power systems planning, economic load dispatch considering the uncertainty of renewable energy sources is one of the most important challenges that researchers have been concerned about. Complex operational constraints, non-convex cost functions of power generation, and some uncertainties make it difficult to solve this problem through conventional optimization techniques. In this article, an improved dynamic differential annealed optimization (IDDAO) meta-heuristic algorithm, which is an improved version of the dynamic differential annealed optimization (DDAO) algorithm has been introduced. This algorithm has been used to solve the economic emission load dispatch (EELD) problem in power systems that include wind farms, and the performance of the proposed technique was evaluated in the IEEE 40-unit and 6-unit standard test systems. The results obtained from numerical simulations demonstrate the profound accuracy and convergence speed of the proposed IDDAO algorithm compared to conventional optimization algorithms including, PSO, GSA, and DDAO, while independent runs indicate the robustness and stability of the proposed algorithm.
