A novel hybrid LUS–TLBO optimized fuzzy-PID controller for load frequency control of multi-source power system

Sahu, Binod Kumar; Pati, Tridipta Kumar; Nayak, Jyoti Ranjan; Panda, Sidhartha; Kar, Sanjeeb Kumar

doi:10.1016/j.ijepes.2015.07.020

Cited by 183 publications

(88 citation statements)

References 27 publications

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“…In the case where X ii is superior to X i , X i is moved towards X ii as indicated in Equation (18). Otherwise, it is moved away from X ii as in Equation (19). If student X new performs better by following Equation (18) or (19), it will be accepted into the population.…”

Section: Teaching Learning-based Optimizationmentioning

confidence: 99%

“…Otherwise, it is moved away from X ii as in Equation (19). If student X new performs better by following Equation (18) or (19), it will be accepted into the population. The algorithm will continue its iterations until reaching the maximum number of generations.…”

Section: Teaching Learning-based Optimizationmentioning

confidence: 99%

“…Moreover, it has fewer adjustable parameters and requires only two commonly used parameters, the population size and the number of generations or iterations. Because of its advantages, TLBO has been researched and applied in various optimization problems [18,19]. The TLBO method is based on the teaching and learning process, and its inspiration is the influence a teacher has on the output of the students in the class.…”

Section: Introductionmentioning

confidence: 99%

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Structure Optimization of Stand-Alone Renewable Power Systems Based on Multi Object Function

2016

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This paper presents a methodology for the size optimization of a stand-alone hybrid PV/wind/diesel/battery system while considering the following factors: total annual cost (TAC), loss of power supply probability (LPSP), and the fuel cost of the diesel generator required by the user. A new optimization algorithm and an object function (including a penalty method) are also proposed; these assist with designing the best structure for a hybrid system satisfying the constraints. In hybrid energy system sources such as photovoltaic (PV), wind, diesel, and energy storage devices are connected as an electrical load supply. Because the power produced by PV and wind turbine sources is dependent on the variation of the resources (sun and wind) and the load demand fluctuates, such a hybrid system must be able to satisfy the load requirements at any time and store the excess energy for use in deficit conditions. Therefore, reliability and cost are the two main criteria when designing a stand-alone hybrid system. Moreover, the operation of a diesel generator is important to achieve greater reliability. In this paper, TAC, LPSP, and the fuel cost of the diesel generator are considered as the objective variables and a hybrid teaching-learning-based optimization algorithm is proposed and used to choose the best structure of a stand-alone hybrid PV/wind/diesel/battery system. Simulation results from MATLAB support the effectiveness of the proposed method and confirm that it is more efficient than conventional methods.

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Section: Teaching Learning-based Optimizationmentioning

confidence: 99%

Section: Teaching Learning-based Optimizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Structure Optimization of Stand-Alone Renewable Power Systems Based on Multi Object Function

2016

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“…LFC is one of the most important processes during the operation of a power system. The energy balance between the generation and loads is controlled by means of a numerical value obtained from sensors that measure the grid frequency [3,4]. For this reason, to solve the load frequency problem, several control methods have been proposed by previous researchers.…”

Section: Introductionmentioning

confidence: 99%

Use of the Genetic Algorithm-Based Fuzzy Logic Controller for Load-Frequency Control in a Two Area Interconnected Power System

2017

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Abstract:The use of renewable energy resources has created some problems for power systems. One of the most important of these is load frequency control (LFC). In this study, in order to solve the LFC problem, modern control methods were applied to a two area multi source interconnected power system. A photovoltaic solar power plant (PV-SPP) was also connected, in order to identify the harmful effects on the frequency of the system. A new Genetic-based Fuzzy Logic (GA-FL) controller was designed to control the frequency of the system. For comparison, conventional proportional-integral-derivative (PID), fuzzy logic (FL), and Genetic Algorithm (GA)-PID controllers were also designed. The new control method exhibited a better performance than the conventional and other modern control methods, because of the low overshoot and short settling time. All simulations were realized with the Matlab-Simulink program.

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“…Hybrid firefly algorithm and pattern search techniques were realized for the AGC multi-area power system [14]. Hybrid local unimodal sampling (LUS)-TLBO-based approach has been employed for LFC of multi-source power system [15]. Quasi-oppositional harmony search (QOHS) algorithm has been employed for LFC of multi-source multi-area power system [16].…”

Section: Introductionmentioning

confidence: 99%

Application of flower pollination algorithm in load frequency control of multi-area interconnected power system with nonlinearity

Jagatheesan¹,

Anand

Samanta

et al. 2016

Neural Comput & Applic

110

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This work presents an application of bio-inspired flower pollination algorithm (FPA) for tuning proportional-integral-derivative (PID) controller in load frequency control (LFC) of multi-area interconnected power system. The investigated power system comprises of three equal thermal power systems with appropriate PID controller. The controller gain [proportional gain (K p ), integral gain (K i ) and derivative gain (K d )] values are tuned by using the FPA algorithm with one percent step load perturbation in area 1 (1 % SLP). The integral square error (ISE) is considered the objective function for the FPA. The supremacy performance of proposed algorithm for optimized PID controller is proved by comparing the results with genetic algorithm (GA) and particle swarm optimization (PSO)-based PID controller under the same investigated power system. In addition, the controller robustness is studied by considering appropriate generate rate constraint with nonlinearity in all areas. The result cumulative performance comparisons established that FPA-PID controller exhibit better performance compared to performances of GA-PID and PSO-PID controller-based power system with and without nonlinearity effect.

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A novel hybrid LUS–TLBO optimized fuzzy-PID controller for load frequency control of multi-source power system

Cited by 183 publications

References 27 publications

Structure Optimization of Stand-Alone Renewable Power Systems Based on Multi Object Function

Structure Optimization of Stand-Alone Renewable Power Systems Based on Multi Object Function

Use of the Genetic Algorithm-Based Fuzzy Logic Controller for Load-Frequency Control in a Two Area Interconnected Power System

Application of flower pollination algorithm in load frequency control of multi-area interconnected power system with nonlinearity

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