Mohamed Menaa

Optimal load frequency control based on hybrid bacterial foraging and particle swarm optimization

This paper presents an application of a hybrid technique combining bacterial foraging with particle swarm optimization (BF-PSO) for determining the optimal values for the proportional-integral-derivation (PID) controller for a load frequency control (LFC) of two-area interconnected power system. This method is compared to the heuristic optimization method (PSO) and to bacterial foraging optimization (BFO) thereby to the traditional Ziegler-Nichols method. The results of PID-tuning are compared with the results of I, ID and PI controllers. The transient responses are shown due to step load disturbances in area-1. The main primary objective is to suppress all the fluctuations of the system frequency and tie line power flow.

Load Frequency Control in multi-area power system based on Fuzzy Logic-PID Controller

In an interconnected multi-area power system, as a power load demand varies randomly, in the case of any small sudden load change in any of the areas, both area frequency and tie-line power flow interchange also vary. The main goals of Load Frequency Control (LFC) are, to hold the frequency and the desired power output in the interconnected power system at the scheduled values and to control the change in the tie-line power flow between control areas. The purpose of this paper is to present basically an application of Fuzzy Logic Controller (FLC) based load frequency control using PID controller in multi-area interconnected power system. The fuzzy logic is employed to search for optimal values for the PID controller parameters. The three-area 9-unit model system is used for the simulation, and the transient responses are shown due to step load disturbances in area-1, area-2 and area-3. The main primary objective is to suppress all the fluctuation of the system frequency and tie-line power flow. By comparison to the conventional Ziegler-Nichols technique (Z-N) and to the heuristic Particle Swarm Optimization method (PSO), the effectiveness of the proposed method is confirmed.

Optimal load frequency control in interconnected power system using PID controller based on particle swarm optimization

Today load frequency control is becoming more important and significant in interconnected power system design and operation due to the complexity of power systems, changing structure, and emerging renewable energy sources. This paper presents an application of particle swarm optimization (PSO) algorithm for determining the optimal values for the proportional-integral-derivation (PID) controller for a load frequency control (LFC) of two-area interconnected power system having diverse sources of power generation. This method is compared to the traditional Ziegler-Nichols method. In order to analyze the load frequency control we propose to use a new method based on the implicit integration Trapezoidal rule and the iterative Newton-Raphson method. The two area power system is simulated for different load disturbances. The main primary objective is to suppress all the fluctuation of the system frequency and tie line power flow and the proposed method has proven to be very efficient.

Optimal load frequency control based on artificial bee colony optimization applied to single, two and multi-area interconnected power systems

This paper describes an application of Artificial Bee Colony (ABC) to load frequency control (LFC) in single, two and multi-area interconnected power systems. The proposed ABC algorithm is used to obtain the optimal values of the proportional-integral-derivation (PID) controller parameters based load frequency control (LFC). The principal function of the LFC loop is to control the frequency and active power. The main aim of this work is to suppress all the fluctuations of the system due to the disturbance and get back the frequency at nominal value. In order to analyze the system frequency and the tie-line power flow with the varying of the load, the simulation is performed under load disturbances. Simulation results showed good performance in terms of settling time and peak overshoot of the proposed approach compared to the traditional Ziegler-Nichols, Genetics Algorithm (GA), Particle Swarm Optimization (PSO) and Bacterial Foraging Optimization (BFO) methods, and the ability of the proposed algorithm to solve load frequency control problems under different disturbances is confirmed.

A novel optimized fuzzy-PID controller in two-area power system with HVDC link connection

This paper presents a new optimized fuzzy-PID controller to improve frequency stability in two-area interconnected power system with high voltage direct current (HVDC) link connection. A novel nature-inspired algorithm called Multi-Verse Optimizer (MVO) was employed to solve the optimal frequency regulation problem. To show the effectiveness of the proposed control strategy, the two-area interconnected Hokkaido-Honshu of Eastern Japan 50-Hz power system with Kita-Hon HVDC link was investigated for the simulation. The proposed MVO algorithm was used to satisfy two main objectives. Firstly, MVO was adopted to estimate the unknown parameters of the test system and model the HVDC link for the Load Frequency Control (LFC) analysis. Secondly, MVO was applied to optimize the suggested fuzzy-PID controller parameters including the scaling factors of fuzzy logic and the PID controller gains. The estimated unknown parameters of the simulated model were compared with other existing results in literature. The effects of the HVDC Link on system frequency are analyzed. Moreover, dynamic responses obtained from the simulation satisfy the LFC requirements and reveal that the proposed control strategy based on MVO algorithm enhance the frequency stability in terms of settling time and peak overshoots.

A novel robust automatic generation control in interconnected multi-area power system based on bat inspired algorithm

This paper deals with the design of a new robust controller to solve automatic generation control (AGC) problems in interconnected multi-area power system using the meta-heuristic Bat Inspired Algorithm (BA). The novel design approach based on Bat algorithm is proposed to reach the optimal values of the Proportional-Integral-Derivation (PID) controller parameters in order to improve the load frequency control (LFC) and automatic voltage regulator (AVR). The three equal area thermal interconnected power system is considered for the simulation. The superiority of the proposed approach is demonstrated by comparing the results with some recently published techniques such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Bacteria Foraging Optimization (BFO), Artificial Bee Colony (ABC) and Ziegler-Nichols based PID controller for the same interconnected power system. Robustness analysis is carried out by varying the step load disturbance in each area, to demonstrate the capability of the proposed Bat Inspired Algorithm (BA) to solve AGC problems (LFC / AVR) and optimized PID controller.

A novel optimal frequency control strategy for an isolated wind–diesel hybrid system with energy storage devices:

This article presents the design of a new effective control strategy to enhance frequency stability of an isolated micro-grid-based wind–diesel hybrid system. The suggested control methodology involves load frequency control coordinated with battery energy storage systems. A recently developed meta-heuristic algorithm called multi-verse optimizer was applied to design an intelligent load frequency control scheme in the aim to handle the frequency fluctuation due to load changes and wind farm integration. The multi-verse optimizer algorithm was used to optimize the proportional–integral–derivative controller parameters for the load frequency control loop. The proposed controller was coordinated with two different kinds of storage system, which are redox flow batteries and electric vehicles. To demonstrate the effectiveness of the proposed control strategy, the simulation was performed under step load changes and then was extended with doubly-fed induction generator wind farm integration. Furthermore, to show the potential of multi-verse optimizer algorithm, a comparative study was done with other approaches available in the literature. In addition, robustness analysis was carried out. The obtained simulation results show that the proposed strategy is a very effective means for providing robust load frequency control controller and to avoid hybrid system instability. Furthermore, the system frequency can be improved using an optimal power management of the stored energy in both redox flow batteries and electric vehicles to compensate the load frequency control capability of the diesel groups, which allow to the possibility of integration of a large penetration of wind farms. In summary, the proposed control strategy may be helpful to identify the needed load frequency control capacity in the presence of dispersed generation’s units.

Design of intelligent load frequency control strategy using optimal fuzzy-PID controller

This paper proposes a robust control strategy involving a novel optimised fuzzy-PID controller tuning by particle swarm optimisation (PSO) algorithm. The proposed control strategy was suggested to design an intelligent load frequency control (LFC) scheme in multi-area interconnected power system. The PSO algorithm was employed to optimise the fuzzy-PID controller parameters including the scaling factors of fuzzy logic and the PID controller gains for minimisation of both system frequency deviation and tie-line power changes during load disturbances using the integral time multiply absolute error (ITAE) as objective function. To demonstrate the effectiveness of the proposed control strategy, the three-area 9-unit interconnected power system was used for the simulation. The superiority of the proposed approach was shown by comparing the obtained results to other strategies available in literature. Initially, the simulation was performed using the same controllers in each area, and then was extended with different controllers in each area. The comparative study demonstrates the potential of the proposed control strategy and shows its robustness to enhance frequency stability.

Frequency stability enhancement in two-area deregulated power system based competitive electricity markets with redox flow batteries and power flow controllers

This paper presents the design of an effective control strategy for frequency stability enhancement in two-area Thermal-Thermal power system under deregulated environment based Competitive Electricity Markets. The suggested control strategy involves an intelligent Load Frequency Control (LFC) based optimized PID controller employing Firefly Algorithm (FA). Additionally, the LFC loop was coordinated with Redox Flow Batteries (RFB). Moreover, to improve the tie-line power flow stability and compensate LFC capacity, impacts of two kinds of power flow controllers namely the Interline Power Flow Controller (IPFC) and Unified Power Flow Controller (UPFC) have been also investigated. The developed test system comprises: GENCOs, TRANSCOs and DISCOs, where the simulation was performed under deregulated market structure by considering the concept of DISCOs Participation Matrix (DPM). To show the effectiveness of the proposed control strategy, three scenarios were presented. Initially, the simulation was carried out under Pool-co Transaction and then under Bilateral Transaction and finally the study was extended under Contract Violation. Furthermore, to demonstrate the potential of the proposed methodology a comparative study was done. The obtained simulation results from this work show that the proposed control strategy presents a very effective means for providing robust ancillary frequency control in a deregulated power system.