The Application of Ant Colonies Algorithm in Optimal Positioning Wind Turbine Farms

Reduction of fossil fuel resources has made wind energy as one of the most prolific alternative energies in the world. Therefore, the design and operation of the wind turbine farms in many countries has become a priority. The place of installation of the wind turbines is one of the most important issues related to the design of these farms. Therefore, the characteristics of the relevant environmental and other restrictions that are usually linked to a couple of variables in the design of these sites are being considered. In this paper a new method based on Ant Colony algorithm for optimal positioning installation of wind turbine farms in the electrical distribution networks is provided. And the performance of the proposed method is tested and reviewed

The Application of Ant Colonies Algorithm in Optimal Positioning Wind Turbine Farms

Reduction of fossil fuel resources has made wind energy as one of the most prolific alternative energies in the world. Therefore, the design and operation of the wind turbine farms in many countries has become a priority. The place of installation of the wind turbines is one of the most important issues related to the design of these farms. Therefore, the characteristics of the relevant environmental and other restrictions that are usually linked to a couple of variables in the design of these sites are being considered. In this paper a new method based on Ant Colony algorithm for optimal positioning installation of wind turbine farms in the electrical distribution networks is provided. And the performance of the proposed method is tested and reviewed

Load frequency control scheme for a microgrid system with the application of hTLO-DE algorithm

Load frequency control (LFC) is a crucial feature of electric power systems to maintain a balance between power supply and load demand, thus avoiding a deviation of the grid frequency. The present work aims to implement an effective LFC scheme for a microgrid system consisting of a diesel generator (DEG), a wind turbine generator (WTG) and a battery storage system. Proportional-integral-double-derivative (PIDD) controllers are used to implement the proposed LFC scheme. The controller parameters are computed using an innovative hybrid teaching-learning-optimization differential-evaluation (hTLO-DE) algorithm. The main scope of the work lies in application of hTLO-DE optimized PIDD controllers in DEG-WTG-battery storage based MG system. The results obtained with PIDD controllers are compared with those obtained with the traditional PI and PID controllers. A critical analysis shows that the PIDD controller can provide better dynamic responses in terms of settling time and magnitude of oscillations compared to PI and PID controllers. The frequency responses of the system are studied under different scenarios of generation and load variations, which establishes the robustness of the proposed PIDD-based LFC scheme

Chaotic multi-objective optimization based design of fractional order PI{\lambda}D{\mu} controller in AVR system

In this paper, a fractional order (FO) PI{\lambda}D\mu controller is designed to take care of various contradictory objective functions for an Automatic Voltage Regulator (AVR) system. An improved evolutionary Non-dominated Sorting Genetic Algorithm II (NSGA II), which is augmented with a chaotic map for greater effectiveness, is used for the multi-objective optimization problem. The Pareto fronts showing the trade-off between different design criteria are obtained for the PI{\lambda}D\mu and PID controller. A comparative analysis is done with respect to the standard PID controller to demonstrate the merits and demerits of the fractional order PI{\lambda}D\mu controller.Comment: 30 pages, 14 figure

Modelling and control strategies for hydrokinetic energy harnessing

The high prices and depletion of conventional energy resources and the environmental concern due to the high emission of CO2 gases have encouraged many researchers worldwide to explore a new field in renewable energy resources. The hydrokinetic energy harnessing in the river is one of the potential energies to ensure the continuity of clean, reliable, and sustainable energy for the future generation. The conventional hydropower required a special head, lots of coverage area, and some environmental issues. Conversely, the hydrokinetic system based on free stream flowing is one of the best options to provide the decentralised energy for rural and small-scale energy production. Lately, the effort of energy harnessing based on hydrokinetic technology is emerging significantly. Nevertheless, several challenges and issues need to be considered, such as turbine selection for energy conversion, generalised turbine model and control strategies for the grid and non-grid connection. To date, no detailed information on which turbines and turbine model are most suited to be implemented that match Malaysia’s river characteristics. Besides, a large oscillation has occurred on the output current and power during dynamic steady state due to the water variation and fluctuation in the river. Hence, reducing the energy extraction and controller efficiency for stand-alone and grid-connected systems, respectively. Therefore, the study aims to analyse the different turbine's design, proposed the turbine model, and propose the potential control strategies for stand-alone and grid-connected hydrokinetic energy harnessing in the river. In this work, three types of vertical axis turbines, including the H-Darrieus, Darrieus, and Gorlov with twelve different NACA and NREL hydrofoils, were analysed using the QBlade and MATLAB software, respectively. The effect of symmetrical and non-symmetrical geometry profiles, hydrofoils thicknesses, and turbine solidities have been compared to choose one of the best option turbines based on the highest power coefficient (CP) and a torque coefficient (CM), respectively. Subsequently, the turbine power model generalised equation has been proposed to represent the hydrokinetic turbine characteristic using a polynomial estimation equation. On the other hand, the MPPT control strategy is employed for the off-grid system using the sensorless method. The circuit topology based on an uncontrolled rectifier with the DC boost converter is implemented to regulate the rectifier output voltage through duty ratio. Subsequently, the metaheuristic method based on the combination of the Hill-Climbing Search (HCS) MPPT algorithm and the Fuzzy Logic Controller has been proposed to produce a variable step size compared to the fixed step size in conventional HCS algorithm. On the contrary, the dynamic model of the grid-connected hydrokinetic system has been linearised for small-signal stability analysis. The eigenvalues analysis-based approached has been applied to evaluate the system stability due to the small disturbance. The PI controller with the eigenvalues tracing method has been proposed to improve the system stability by reducing the oscillation frequency. The research outcomes indicated that the H-Darrieus with NACA 0018 was the best turbine for energy conversion in the river. Besides, the HCS-Fuzzy MPPT algorithm improved the energy extraction up to 88.30 % as well as reduced 74.47 % the oscillation compared to the SS-HCS MPPT. The stability of grid-connected hydrokinetic energy harnessing was improved up to 63.63 % by removing the oscillation frequency at states of λ8,9,10,11 as well as reducing 40.1 % oscillation of the generator stator current at the rotor side controller (RSC)

Applying Sequential Particle Swarm Optimization Algorithm to Improve Power Generation Quality

Swarm Optimization approach is a heuristic search method whose mechanics are inspired by the swarming or collaborative behaviour of biological populations. It is used to solve constrained, unconstrained, continuous and discrete problems. Swarm intelligence systems are widely used and very effective in solving standard and large-scale optimization, provided that the problem does not require multi solutions. In this paper, particle swarm optimisation technique is used to optimise fuzzy logic controller (FLC) for stabilising a power generation and distribution network that consists of four generators. The system is subject to different types of faults (single and multi-phase). Simulation studies show that the optimised FLC performs well in stabilising the network after it recovers from a fault. The controller is compared to multi-band and standard controllers

Performance of optimal hierarchical type 2 fuzzy controller for load–frequency system with production rate limitation and governor dead band

AbstractControlling load–frequency is regarded as one of the most important control-related issues in design and exploitation of power systems. Permanent frequency deviation from nominal value directly affects exploitation and reliability of power system. Too much frequency deviation may cause damage to equipment, reduction of network loads efficiency, creation of overload on communication lines and stimulation of network protection tools, and in some unfavorable circumstances, may cause the network collapse. So, it is of great importance to maintain the frequency at its nominal value.It would be useful to make use of the type 2 fuzzy in modeling of uncertainties in systems which are uncertain. In the present article, first, the simplified 4-block type-2 fuzzy has been used for modeling the fuzzy system. Then, fuzzy system regulations are reduced by 33% with the help of hierarchy fuzzy structure. The simplified type-2 fuzzy controller is optimized using the Cuckoo algorithm. Eventually, the performance of the proposed controller is compared to the Mamdani fuzzy controller in terms of the ISE, ITSE, and RMS criteria

Self-Adaptive Virtual Inertia Control-Based Fuzzy Logic to Improve Frequency Stability of Microgrid With High Renewable Penetration

Maintaining frequency stability of low inertia microgrids with high penetration of renewable energy sources (RESs) is a critical challenge. Solving this challenge, the inertia of microgrids would be enhanced by virtual inertia control-based energy storage systems. However, in such systems, the virtual inertia constant is fixed and selection of its value will significantly affect frequency stability of microgrids under different penetration levels of RESs. Higher frequency oscillations may occur due to the fixed virtual inertia constant or unsuitable selection of its value. To overcome such a problem and provide adaptive inertia control, this paper proposes a self-adaptive virtual inertia control system using fuzzy logic for ensuring stable frequency stabilization, which is required for successful microgrid operation in the presence of high RESs penetration. In this concept, the virtual inertia constant is automatically adjusted based on input signals of real power injection of RESs and system frequency deviations, avoiding unsuitable selection and delivering rapid inertia response. To verify the efficiency of the proposed control method, the contrastive simulation results are compared with the conventional method for serious load disturbances and various rates of RESs penetration. The proposed control method shows remarkable performance in transient response improvement and fast damping of oscillations, preserving robustness of operation

Performance Enhancement of Automatic Generation Control by Developing a Detailed Load Frequency Control Model and an Adaptive Performance Index Criterion

The imbalance between electrical loads and power supplied by the system generators causes the frequency deviations in a power system. Maintaining the frequency close to its nominal value as well as in its allowed deviation range is the first objective of the automatic generation control (AGC). Nowadays, in interconnected power systems, several control areas are connected to each other by tie-lines and power is transferred between control areas based on a specific schedule. The second objective of automatic generation control is to keep the tie-lines power flow close to their secluded values.;An accurate and realistic load frequency control (LFC) model is very essential to have an effective and adaptive AGC strategy. The first objective of this thesis is to present the importance of considering communication delay in LFC model missing in most of the studies investigating AGC and its performance using different methods and optimization techniques. The second objective of this thesis is to present a comprehensive LFC model, which contains all of the physical constraints such as governor dead-band, generation rate and delay of communication links. The third objective is to evaluate different controllers and performance index criteria used in conventional AGC. Finally, the last objective is to introduce an adaptive performance index criterion cable of defining settling time and overshoot which cannot be applied by other performance index criteria.;Different optimization methods have been used to optimize the performance of AGC such as genetic algorithm, fuzzy logic and neural networks. Genetic algorithm has been used widely in LFC studies so it is chosen to be employed in this study to optimize the performance of controllers in the utilized AGC scheme. Integrator controller is the most common controller employed in LFC studies because of its design simplicity, however, in this thesis proportional-integral-derivative (PID) controller is employed to obtain the best performance.;This study shows that without a precise and detailed LFC model, results of different techniques or strategies used in AGC will not be accurate and practical even when they are derived by optimization methods. Moreover, it is shown that PID controller has the best performance in comparison with other controllers used in LFC studies when physical constraints are not considered in the LFC model. Furthermore, a robust GA based control system is designed considering all of physical constraints for a three-area power system and the simulation results show that it can track the load change and restore the frequency of all control areas to the nominal value effectively. Different performance index criteria are evaluated and results show that in specific cases they cannot be completely accurate or reliable to assess the performance of AGC schemes. Finally, an effective and adaptive performance index is introduced and simulation results validate its effectiveness and reliability