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Showing 7 results for Shayeghi

H. Shayeghi, A. Ghasemi,
Volume 12, Issue 4 (December 2016)

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 13, Issue 4 (December 2017)

This paper presents an online two-stage Q-learning based multi-agent (MA) controller for load frequency control (LFC) in an interconnected multi-area multi-source power system integrated with distributed energy resources (DERs). The proposed control strategy consists of two stages. The first stage is employed a PID controller which its parameters are designed using sine cosine optimization (SCO) algorithm and are fixed. The second one is a reinforcement learning (RL) based supplementary controller that has a flexible structure and improves the output of the first stage adaptively based on the system dynamical behavior. Due to the use of RL paradigm integrated with PID controller in this strategy, it is called RL-PID controller. The primary motivation for the integration of RL technique with PID controller is to make the existing local controllers in the industry compatible to reduce the control efforts and system costs. This novel control strategy combines the advantages of the PID controller with adaptive behavior of MA to achieve the desired level of robust performance under different kind of uncertainties caused by stochastically power generation of DERs, plant operational condition changes, and physical nonlinearities of the system. The suggested decentralized controller is composed of the autonomous intelligent agents, who learn the optimal control policy from interaction with the system. These agents update their knowledge about the system dynamics continuously to achieve a good frequency oscillation damping under various severe disturbances without any knowledge of them. It leads to an adaptive control structure to solve LFC problem in the multi-source power system with stochastic DERs. The results of RL-PID controller in comparison to the traditional PID and fuzzy-PID controllers is verified in a multi-area power system integrated with DERs through some performance indices.

A. Younesi, H. Shayeghi,
Volume 15, Issue 1 (March 2019)

The purpose of this paper is to design a supplementary controller for traditional PID controller in order to damp the frequency oscillations in a micro-grid. Q-learning, which is used for supervise a classical PID controller in this paper, is a model free and a simple solution method of reinforcement learning (RL). RL is one of the branches of the machine learning, which is the main solution method of Markov decision process (MDPs). The proposed control mechanism is consisting of two main parts. The first part is a classical PID controller which is fixed tuned using Salp swarm algorithm. The second part is a Q‑learning based control strategy which is consistent and updates its characteristics according to the changes in the system continuously. Eventually, a hybrid micro-grid is considered to evaluate the performance of the suggested control method compared to classical PID and fractional order fuzzy PID (FOFPID) controllers. The considered hybrid system is consisting of renewable energy resources such as solar-thermal power station (STPS) and wind turbine generation (WTG), along with several energy storage devices such as batteries, flywheel and ultra-capacitor with physical constraints and time delays. Simulations are carried out in various realistic scenarios considering system parameter variations along with changing in operating conditions. Results indicate that the proposed control strategy has an excellent dynamic response compared to the traditional PID and FOFPID controllers for damping the frequency oscillations in different operating conditions.

S. Pourjafar, H. Shayeghi, H. Madadi Kojabadi, M. Maalandish, F. Sedaghati,
Volume 16, Issue 1 (March 2020)

In this work, a non-isolated high step up DC-DC converter using coupled inductor and voltage multiplier cell is proposed. The proposed converter conversion ratio is efficiently extended by using a coupled inductor. An interleaved configuration of two diode-capacitor cells is applied to step up the voltage conversion ratio and decrease the voltage stress across the switches. Also, in the suggested converter high voltage gain is provided by low turn ratio of the coupled inductor which decreases the volume of cores. Moreover, the reverse recovery problem of output diode is diminished by recycling the leakage inductance energy of the coupled inductor. It causes to increase the overall system efficiency. Furthermore, the voltage multiplier cells lead to clamp the voltage spikes through the switch, when the switch turns off. The comparison between the suggested converter and similar converters is provided to verify its advantages. To validate the effectiveness of the suggested converter, a 200W laboratory prototype with 20V input and 150V output voltages operating at 25kHz switching frequency is carried out and experimental test consequences are given.

H. Shayeghi, A. Younesi,
Volume 16, Issue 4 (December 2020)

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.

H. Shayeghi, S. Pourjafar, F. Sedaghati,
Volume 17, Issue 2 (June 2021)

This work introduces a new non-isolated buck-boost DC-DC converter. Interleaved configuration of the suggested structure increases the voltage conversion ratio. The voltage rate of the suggested converter can be stepped-up and stepped down for lower values of duty-cycle, which causes to decrease in the conduction losses of the system. The voltage conversion ratio of the recommended structure is provided with low maximum voltage throughout the semiconductor elements. Additionally, utilizing only one power switch facilitates converter control. Using a single power MOSFET with small conducting resistance, RDS-ON, increases the overall efficiency of the recommended topology. To verify the performance of the presented converter, technical description, mathematical survey, and comparison investigation with similar structures are provided in the literature. Finally, a laboratory scheme with a 100W load power rate at 50 kHz switching frequency is carried out to demonstrate the effectiveness of the proposed converter.

H. Shayeghi, Y. Hashemi,
Volume 17, Issue 3 (September 2021)

The main idea of this paper is proposing a model to develop generation units considering power system stability enhancement. The proposed model consists of two parts. In the first part, the indexes of generation expansion planning are ensured. Also, small-signal stability indexes are processed in the second part of the model. Stability necessities of power network are supplied by applying a set of robustness and performance criteria of damping. Two parts of the model are formulated as two-objective function optimization that is solved by adaptive non-dominated sorting genetic method-III (ANSGM-III). For better decision-making of the final solution of generation units, a set of Pareto-points have been extracted by ANSGM-III. To select an optimal solution among Pareto-set, an analytical hierarchy style is employed. Two objective functions are compared and suitable weights are allocated. Numerical studies are carried out on two test systems, 68-bus and 118-bus power network. The values of generation expansion planning cost and system stability index have been studied in different cases and three different scenarios. Studies show that, for example, in the 68-bus system for the case of system load growth of 5%, the cost of generation expansion planning for the proposed model increased by 7.7% compared to the previous method due to stability modes consideration and the small-signal stability index has been improved by 6.7%. The proposed model is survived with the presence of a wide-area stabilizer (WAS) for damping of oscillations. The effect of WAS latency on expansion programs is evaluated with different amounts of delay times.

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© 2022 by the authors. Licensee IUST, Tehran, Iran. This is an open access journal distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.