Showing 7 results for Frequency Control
F. Daneshfar, H. Bevrani, F. Mansoori,
Volume 7, Issue 2 (6-2011)
Abstract
Bayesian Networks (BN) provides a robust probabilistic method of reasoning under uncertainty. They have been successfully applied in a variety of real-world tasks but they have received little attention in the area of load-frequency control (LFC). In practice, LFC systems use proportional-integral controllers. However since these controllers are designed using a linear model, the nonlinearities of the system are not accounted for and they are incapable to gain good dynamical performance for a wide range of operating conditions in a multi-area power system.
A strategy for solving this problem due to the distributed nature of a multi-area power system, is presented by using a BN multi-agent system.
This method admits considerable flexibility in defining the control objective. Also BN provides a flexible means of representing and reasoning with probabilistic information. Efficient probabilistic inference algorithms in BN permit answering various probabilistic queries about the system. Moreover using multi-agent structure in the proposed model, realized parallel computation and leading to a high degree of scalability.
To demonstrate the capability of the proposed control structure, we construct a BN on the basis of optimized data using genetic algorithm (GA) for LFC of a three-area power system with two scenarios.
F. Daneshfar, E. Hosseini,
Volume 8, Issue 4 (12-2012)
Abstract
Recently several robust control designs have been proposed to the load-frequency control (LFC) problem. However, the importance and difficulties in the selection of weighting functions of these approaches and the pole-zero cancellation phenomenon associated with it produces closed loop poles. Also the order of robust controllers is as high as the plant. This gives rise to complex structure of such controllers and reduces their applicability in industry. In addition conventional LFC systems that use classical or trial-and-error approaches to tune the PI controller parameters are more difficult and time-consuming to design.
In this paper, a bisection search method is proposed to design well-tuned PI controller in a restructured power system based on the bilateral policy scheme. The bisection search is a very simple and rapidly converging method in mathematics. It is a root-finding approach which repeatedly bisects an interval and then selects a subinterval in which a root must lie for further processing.
The new optimized solution performance has been applied to a 3-area restructured power system with possible contracted scenarios under large load demand and area disturbances. The results evaluation shows the proposed method achieves good performance compared with a powerful robust ILMI-based controller. Moreover, this newly developed solution has a simple structure, and is fairly easy to implement in comparison to other controllers, which can be useful for the real world complex power systems.
H. Rajabi Mashhadi, S. M. Eslami, H. Modir Shanechi,
Volume 10, Issue 3 (9-2014)
Abstract
The main goal of this paper is to study statistical indices and evaluate AGC indices in power system which has large penetration of the WTGs. Increasing penetration of wind turbine generations, needs to study more about impacts of it on power system frequency control. Frequency control is changed with unbalancing real-time system generation and load . Also wind turbine generations have more fluctuations and make system more unbalance. Then AGC loop helps to adjust system frequency and the scheduled tie-line powers. The quality of AGC loop is measured by some indices. A good index is a proper measure shows the AGC performance just as the power system operates. One of well-known measures in literature which was introduced by NERC is Control Performance Standards(CPS). Previously it is claimed that a key factor in CPS index is related to standard deviation of generation error, installed power and frequency response. This paper focuses on impact of a several hours-ahead wind speed forecast error on this factor. Furthermore evaluation of conventional control performances in the power systems with large-scale wind turbine penetration is studied. Effects of wind speed standard deviation and also degree of wind farm penetration are analyzed and importance of mentioned factor are criticized. In addition, influence of mean wind speed forecast error on this factor is investigated. The study system is a two area system which there is significant wind farm in one of those. The results show that mean wind speed forecast error has considerable effect on AGC performance while the mentioned key factor is insensitive to this mean error.
H. Shayeghi, A. Ghasemi,
Volume 12, Issue 4 (12-2016)
Abstract
Microgrids is an new opportunity to reduce the total costs of power generation and supply the energy demands through small-scale power plants such as wind sources, photo voltaic panels, battery banks, fuel cells, etc. Like any power system in micro grid (MG), an unexpected faults or load shifting leads to frequency oscillations. Hence, this paper employs an adaptive fuzzy P-PID controller for frequency control of microgrid and a modified multi objective Chaotic Gravitational Search Algorithm (CGSA) in order to find out the optimal setting parameters of the proposed controller. To provide a robust controller design, two non-commensurable objective functions are formulated based on eigenvalues-domain and time-domain and multi objective CGSA algorithm is used to solve them. Moreover, a fuzzy decision method is applied to extract the best and optimal Pareto fronts. The proposed controller is carried out on a MG system under different loading conditions with wind turbine generators, photovoltaic system, flywheel energy, battery storages, diesel generator and electrolyzer. The simulation results revealed that the proposed controller is more stable in comparison with the classical and other types of fuzzy controller.
H. Shayeghi, A. Younesi,
Volume 16, Issue 4 (12-2020)
Abstract
The main objective of this paper is to model and optimize the parallel and relatively complex FuzzyP+FuzzyI+FuzzyD (FP+FI+FD) controller for simultaneous control of the voltage and frequency of a micro-grid in the islanded mode. The FP+FI+FD controller has three parallel branches, each of which has a specific task. Finally, as its name suggests, the final output of the controller is derived from the algebraic summation of the outputs of these three branches. Combining the basic features of a simple PID controller with fuzzy logic that leads to an adaptive control mechanism, is an inherent characteristic of the FP+FI+FD controller. This paper attempts to determine the optimal control gains and Fuzzy membership functions of the FP+FI+FD controller using an improved Salp swarm algorithm (ISSA) to achieve its optimal dynamic response. The time-domain simulations are carried out in order to prove the superb dynamic response of the proposed FP+FI+FD controller compared to the PID control methods. In addition, a multi-input-multi-output (MIMO) stability analysis is performed to ensure the robust control characteristic of the proposed parallel fuzzy controller.
F. Amiri, M. H. Moradi,
Volume 17, Issue 4 (12-2021)
Abstract
In this paper, a coordinated control method for LFC and SMES systems based on a new robust controller is designed. The proposed controller is used to compensate for frequency deviations related to the power system, to prevent excessive power generation in conventional generators during load disturbances, and to reduce power fluctuations from wind power plants. The new robust controller does not require the measurement of all the power system states and it only uses the output feedback. It also has a higher degree of freedom than the conventional robust controllers (conventional output feedback) and thus it helps improve the system control. The proposed control method is highly robust against load and distributed generation resources (wind turbine) disturbances and it is also robust against the uncertainty of the power system parameters. The proposed method is compared under several scenarios with the coordinated control method for LFC and SMES systems based on Moth Swarm Algorithm-optimized PID controller, the LFC system based on Moth Swarm Algorithm-optimized PID controller with SMES, the coordinated control method for LFC and SMES systems based on Robust Model Predictive Control, and the LFC system based on optimized PID controller without SMES and it puts on satisfactory performance. The simulation was performed in MATLAB.
Trung Kien Do, Thanh Long Duong,
Volume 21, Issue 1 (3-2025)
Abstract
Frequency instability is one of the causes of severe disturbances in the power system, including load shedding and widespread blackouts. Especially in modern power systems, frequency instability has even more serious consequences due to the propagation occurring in interconnected regions. Load frequency control (LFC) is a powerful tool in power system operation to ensure that the frequency is always within the allowable limits. The control parameters of LFC must be optimally adjusted for stable system operation. However, researchers are currently unable to find a suitable and robust method for optimal tuning of LFC control parameters. The paper proposes the Puma Optimizer (PO) algorithm to optimize the parameters of PID, FOPID, and FOPTID+1 controllers for solving the LFC problem. The proposed PO algorithm is evaluated through two models of single-area and two-area power systems with different power sources, including thermal power, hydropower, and gas power. The simulation results show that the integral time absolute error (ITAE) value of the proposed PO method is smaller by 5.25%, 18.16%, 28.35%, and 59.92% compared to Particle Swarm Optimization (PSO), Crested Porcupine Optimization (CPO), Newton-Raphson-based optimization (NRBO), and Global Neighborhood Algorithm (GNA), respectively. The results obtained demonstrate that the PO algorithm is a reliable and efficient tool for finding solutions to the LFC problem.
