Ranjan Kumar Mallick

Grey wolves-based optimization technique for tuning damping controller parameters of unified power flow controller

This paper presents grey wolf optimization(GWO), which is a recently reported novel meta-heuristic optimizer, applied to optimize the damping controller parameters for a unified power flow controller connected to a single machine infinite bus power system for power oscillation damping. In this work the proposed GWO algorithm is compared with PSO algorithm in terms of convergence rate and computation time. The simulation result shows that the proposed algorithm provides better results as compared to other.

Application of grey wolves-based optimization technique in multi-area automatic generation control

In this work a recently reported novel meta-heuristic optimizer called grey wolf optimization(GWO) has been applied to optimize the weighty parameters in automatic generation control(AGC) of interconnected three unequal area thermal system, such as gain constant of PID controller (Kpi, KIi, Kdi). A three unequal area interconnected system is studied as a test system under different loading conditions, the nonlinearities nature of the system are considered into account to confirm the effectiveness of the grey wolf optimization in terms of suitable generation rate constraints(GRC). The result of GWO based PID controller is compared with bacteria foraging based optimization technique [5].

Application of Hybrid Differential Evolution–Grey Wolf Optimization Algorithm for Automatic Generation Control of a Multi-Source Interconnected Power System Using Optimal Fuzzy–PID Controller

Abstract This paper deals with an optimal hybrid fuzzy-Proportional Integral Derivative (fuzzy-PID) controller optimized by hybrid differential evolution–Grey Wolf optimization algorithm for automatic generation control of an interconnected multi-source power system. Here a two area system is considered; each area is provided with three types of sources namely a thermal unit with reheat turbine, a hydro unit and a gas unit. The dynamic performance of the system is analyzed under two cases: with AC tie-line and with AC-DC tie-line. The efficiency and effectiveness of the proposed controller is substantiated equally in the two cases. The sturdiness of the system is proved by varying the values of the system parameters. The supremacy of the recommended work is additionally ascertained by comparison with the recently published results like differential evolution optimized PID Controller and hybrid Local Unimodal Sampling-Teaching Learning based Optimization (LUS-TLBO) optimized fuzzy-PID controller. The dynamic performance of the system is observed in terms of settling time, peak overshoot and peak undershoot. Finally the analysis is extended by applying the proposed control technique in two different models namely (i) A three area unequal thermal system considering proper generation rate constraints (GRC) and (ii) A three area hydro-thermal system with mechanical hydro governor. These test results reveal the adaptability of the proposed method in multi-area interconnected power system.

Gravitational search algorithm (GSA) optimized fuzzy-PID controller design for load frequency control of an interconnected multi-area power system

This paper focuses on the load frequency control of two area interconnected reheat thermal system with fuzzy-PID controller optimized by gravitational search algorithm (GSA). The gains of the fuzzy-PID controllers are optimized by providing a step load perturbation (SLP) of 1% to area 1 in consideration of integral time absolute error (ITAE) as the objective function. The dynamic performances of the system are being analyzed with GSA and PSO optimized fuzzy-PID controllers. The supremacy of the proposed method is depicted in terms of settling time, peak overshoots and undershoots in comparison with a recently published results. Further the robustness of the system is proved by changing the system loading.

Optimal design of PD-Fuzzy-PID cascaded controller for automatic generation control

Abstract In this research paper a novel cascaded PD-Fuzzy-PID controller is recommended for a conventional hybrid-source unified power system for automatic generation control. The optimization of scaling parameters of the suggested PD-Fuzzy-PID controller is done by hybrid Grey Wolf Optimization-Teaching Learning Based Optimization (GWO-TLBO) technique. A sudden disturbance of 0.01 p.u. is considered in area 1 and ITAE is taken as the evaluative function in the recommended optimization process. The proposed work considers three different sources of generating systems namely, a hydro, a gas and a reheat thermal unit. Both AC tie-line and AC-DC tie-line is considered in analyzing the dynamic performances of the system. The robustness and sensitiveness of the proposed controller are further put to test for random load variations and nominal parameter variations. Analysis of the dynamic characteristics of the system is executed considering a number of time response specifications like settling time, peak overshoots and undershoots. During the analysis the optimum specifications obtained by the recommended technique are compared with some pre-published results in order to prove the supremacy of this novel controller over existing controllers. Further, the frequency stability of the system is improved by employing an UPFC in the system.

Bidding strategy of IPP in competitive electricity market using FACLPSO

There were monopoly markets all over the world in power generation and also in the power distribution sectors. After 1990s many countries had changed their economics of electricity market, where the participants are the Independent power producers (IPPs), who submit the amount of energy they can provide to the market at any particular trading hour and the price they will charge for the same, and the large and small consumers, submit the energy they require and the amount they want to pay for it. However in this case we have considered the IPP side bidding only using Fuzzy adaptive Comprehensive learning particle swarm optimisation (FACLPSO) method, which is tested on IEEE-30 bus system with 6 IPPs and the output in our case is found to be much better on comparison to that obtained by each of the FAGSA, CLPSO and PSO methods.

Design of GWO optimized dual UPFC controller for damping of power system oscillations

This paper proposes the design of an optimized dual UPFC controller for damping power system oscillations, where modulation index of series converter and phase angle of shunt converter voltage are controlled simultaneously. The dual damping controller parameters are optimized by a recently reported metaheuristic optimization technique known as Grey Wolf Optimizer (GWO). This is a simple technique which can effectively optimise all the six parameters of the controller. The effectiveness of this proposed optimized dual controller is compared with PSO optimized dual controller and single independent GWO and PSO optimized controllers. The dynamic responses of speed deviation for all the controllers are considered for a step change in mechanical input power considering a single machine infinite bus system. Eigen value analysis of the system are performed and it has been observed that the performance of proposed optimised dual controller is much better in damping of low frequency oscillations as compared to others in terms of settling time, peaks of oscillations and convergence rate, thus enhancing dynamic stability to a large extent.

Design of optimal 2-DOF PID controller using GWO technique for automatic generation control of a multisource power system

In this research paper an optimal 2-Degree freedom of proportional-integral-derivative controller (2-DOF PID) tuned by grey wolf optimization(GWO) is suggested for automatic generation control (AGC) of a multi-source power system comprising of two areas where each area contains a thermal unit, a hydro unit and a gas unit. The active response of the system is observed under two cases: with AC tie-line and with AC-DC tie-line. The optimal values of the 2-DOF PID controllers are achieved by taking integral time absolute error (ITAE) as objective function with the application of a disturbance of 0.01p.u. in area 1. To show the supremacy of the proposed controller the results obtained is compared with pre-published result such as DE tuned PID controller. Numerous time domain parameters such as settling time, peak overshoots and peak undershoots are computed and compared with the pre-published results so as to show the superiority of the suggested controller.

Load frequency controller design using hybrid differential evolution particle swarm optimization (DEPSO) of an interconnected multi-source power system

This paper deals with the automatic generation control of a two area interconnected multi source power system using PID controller optimized by Hybrid DEPSO algorithm. Here in each area three types of of sources are being considered namely thermal, hydro and gas power plant. The system performance is analyzed with and without HVDC link. The gains of PID controllers are optimized considering integral time absolute error (ITAE). The dynamic response of the system is analyzed in terms of settling time, peak overshoot and peak undershoot by giving step load perturbation (SLP) in area 1. Further the result of proposed work is also compared with recently published result in order to show the supremacy of the proposed method.

Design of optimal controller for DSTATCOM using differential evolution technique

In this paper a microgrid model has been taken which comprises a DFIG based wind firm, a solar farm and the normal grid voltage. A DSTATCOM is used in this model for the mitigation of harmonics. This paper also presents us a novel controller for DSTATCOM the SRF(Synchronous reference frame) controller. The Kp and the Ki values of the two PI blocks present in the proposed controller has been optimized in this paper using DE(Differential Evolution). The model is simulated in Simulink/MATLAB and the results are noted. The THD values are observed to be less than the IEEE standards. The results has also been compared with that of PSO and is found to be most effective and are thereby accepted.