Design and analysis of SSSC-based supplementary damping controller

Power-system stability improvement by a static synchronous series compensator (SSSC)-based damping controller is thoroughly investigated in this paper. The design problem of the proposed controller is formulated as an optimization problem, and real coded genetic algorithm (RCGA) is employed to search for the optimal controller parameters. Both local and remote signals with associated time delays are considered in the present study and a comparison has been made between the two signals. The performances of the proposed controllers are evaluated under different disturbances for both single-machine infinite-bus power system and multi-machine power system. Simulation results are presented and compared with a recently published modern heuristic optimization technique under various disturbances to show the effectiveness and robustness of the proposed approach.     

A novel adaptive deadbeat- based control for load frequency control of low inertia system in interconnected zones north and south of Scotland

An adaptive deadbeat (ADB) controller was developed to investigate its capability in providing a fast frequency response to an electrical power system. This controller was developed to meet the requirements of the National Grid System Operability Framework (SOF), which requires frequency to be accelerated in line with a fast rate of change of frequency (RoCoF) when a high rate of nonsynchronous machines are presented. The controller’s parameters were optimized using particle swarm optimization (PSO) to ensure a robust operation and to maintain the proper operation of the power system. The design of the ADB controller was then integrated with the multiarea model of the north and south zones of Scotland. This model was developed in order to conform to the future energy requirements scenario stated by National Grid whereby regional control can be provided in both the north and south of Scotland. In comparison with the standard PI and Fuzzy-PI controllers used in the four highlighted case studies, it was shown that the ADB controller was able to significantly reduce the RoCoF and deviation of frequency when a sudden loss of generation occurred in a low inertia zone. The ADB also showed high robustness against a wide range of operating conditions.     

Automatic generation control of a multi-area system using ant lion optimizer algorithm based PID plus second order derivative controller

This article presents the automatic generation control of an unequal three area thermal system. Single stage reheat turbines and generation rate constraints of 3%/min are considered in each control area. Controllers such as Integral (I), Proportional – Integral (PI), Proportional – Integral – Derivative (PID), and Proportional – Integral – Derivative Plus Second Order Derivative (PID + DD) are treated as secondary controllers separately. A nature inspired optimization technique called Ant Lion Optimizer (ALO) algorithm is used for simultaneous optimization of the controller gains. Comparison of dynamic responses of frequencies and tie line powers corresponding to ALO optimized I, PI, PID and PID + DD controller reveal the better performance of PID + DD controller in terms of lesser settling time, peak overshoots as well as reduced oscillations. Robustness of the optimum gains of best controller obtained at nominal conditions is evaluated using sensitivity analysis. Analysis exposed that the optimum PID + DD controller gains obtained at nominal are robust and not necessary to reset again for changes in loading, parameter like inertia constant (H), size and position of disturbance. Furthermore, the performance of PID + DD controller is found better as compared to PID controller against random loading pattern condition.     

Optimal multi-reservoir network control by two-phase neural network

An approach based on two-phase neural network (TPNN) is proposed for the optimal operation of multi-reservoir network control problems. The advantage of the proposed technique is that it takes into account the concurrent interaction among all the water release variables of the problem. Here, the main objective of this work is to figure out the optimal amounts of water releases from each hydro-plant during each interval in the interconnected system and to minimize and distribute uniformly the energy deficit if any. This TPNN approach is basically a two-stage solution method. In stage 1, the neural network is developed to bring the solution trajectory close to the boundary of the feasible region. In stage 2, the directional vector of the constraints is slowly shifted to the corresponding Lagrange multipliers and this moves the solution trajectory to the feasible region which satisfies all practical constraints. Application of this technique to a 10-reservoir network demonstrates efficacy of the proposed algorithm. It is concluded from the results that the proposed method with proper selection of network control parameters is very effective in providing a good optimal solution.     

Influencer-defaulter mutation-based optimization algorithms for predicting electricity prices

Efficient electricity price forecasting plays a significant role in our society. In this paper, a novel influencer-defaulter mutation (IDM) mutation operator has been proposed. The IDM operator has been combined with six well-known optimization algorithms to create mutated optimization algorithms whose performance has been tested on twenty-four standard benchmark functions. Further, the artificial neural network is integrated with mutated optimization algorithms to solve the electricity price prediction problem. The policymakers can identify appropriate variables based on the predicted prices to help future market planning. The statistical results prove the efficacy of the IDM operator on the recent optimization algorithms.     

Analysis of multi-layered composite cylinders under hygrothermal loading

In this study, a general stress analysis is developed for thick or thin multi-layered composite cylinders under hygrothermal loadings. The layers are oriented symmetrically and antisymmetrically for [0°/90°]₂, [30°/−30°]₂, [45°/−45°]₂ and [60°/−60°]₂ orientations. The solution is carried out on composite cylinders for plane-strain, open end and closed end conditions. Uniform and parabolic temperature distributions are chosen for the thermal loads. All the integration constants are found from the radial stress and displacement in the normal direction of layers. The hygrothermal and other mechanical properties are measured on a glass-epoxy composite layer. Some analytical solutions are compared with the finite element solutions, in which commercial software ANSYS 7.0 is utilized, and close results are obtained between them.     

Hybrid BFOA–PSO algorithm for automatic generation control of linear and nonlinear interconnected power systems

In the bacteria foraging optimization algorithm (BFAO), the chemotactic process is randomly set, imposing that the bacteria swarm together and keep a safe distance from each other. In hybrid bacteria foraging optimization algorithm and particle swarm optimization (hBFOA–PSO) algorithm the principle of swarming is introduced in the framework of BFAO. The hBFOA–PSO algorithm is based on the adjustment of each bacterium position according to the neighborhood environment. In this paper, the effectiveness of the hBFOA–PSO algorithm has been tested for automatic generation control (AGC) of an interconnected power system. A widely used linear model of two area non-reheat thermal system equipped with proportional-integral (PI) controller is considered initially for the design and analysis purpose. At first, a conventional integral time multiply absolute error (ITAE) based objective function is considered and the performance of hBFOA–PSO algorithm is compared with PSO, BFOA and GA. Further a modified objective function using ITAE, damping ratio of dominant eigenvalues and settling time with appropriate weight coefficients is proposed to increase the performance of the controller. Further, robustness analysis is carried out by varying the operating load condition and time constants of speed governor, turbine, tie-line power in the range of +50% to ?50% as well as size and position of step load perturbation to demonstrate the robustness of the proposed hBFOA–PSO optimized PI controller. The proposed approach is also extended to a non-linear power system model by considering the effect of governor dead band non-linearity and the superiority of the proposed approach is shown by comparing the results of craziness based particle swarm optimization (CRAZYPSO) approach for the identical interconnected power system. Finally, the study is extended to a three area system considering both thermal and hydro units with different PI coefficients and comparison between ANFIS and proposed approach has been provided.     

Erosive Wear Study of PPLSF/Glass Fiber ReinforcedHybrid Laminates

This work is focused to examine the erosive performance of hybrid Palmyra palm leaf stalk fiber (PPLSF)/glass polyester laminate against solid particle bombardment. A hand lay-up method was adopted for the fabricating four piles of five distinct laminates with different stacking order glass and PPLSF layers. Amongst them, one group of pure PPLSF and pure E-glass laminates were fabricated. The hybrid laminates were exposed to high speed stream of solid sand particle at three distinct impact velocities (48, 70 and 82 m/s) and four different angles of impingement (30°, 45°, 60° and 90°). The effect of particle velocity, angle of impingement and stacking order on both wear rate and efficiency were highlighted. The experimental assessment reveals a significant improvement in erosive wear resistance properties due to hybridization of PPLSF with E-glass. Again, the laminates with PPLSF layer as skin and glass as core layer exhibited better erosive wear resistance properties than other types of laminates. Further, a maximum value of erosion at lower velocity (48 m/s) is also noticed at 45° impingement angle. However, at high velocity of impact 70 m/s and 82 m/s, the maximum rate of erosion has been shifted from 45° impact angle to 60° impact angle. The alternation of this semi-ductile character to semi-brittle character is evidenced by analyzing the experimental data. Further to justify the mode of erosion, the eroded surface samples were inspected by scanning electron microscope (SEM).