An efficient operation of a micro grid using heuristic optimization techniques: Harmony search algorithm, PSO, and GA

Author(s):  
Kyu-Ho Kim ◽  
Sang-Bong Rhee ◽  
K. Y. Lee
Author(s):  
Mimoun Younes ◽  
Fouad Khodja ◽  
Riad Lakhdar Kherfene

Environmental legislation, with its increasing pressure on the energy sector to control greenhouse gases, is a driving force to reduce CO2 emissions, forced the power system operators to consider the emission problem as a consequential matter beside the economic problems, so the economic power dispatch problem has become a multi-objective optimization problem. This paper sets up an new hybrid algorithm combined in two algorithm, the harmony search algorithm and ant colony optimization (HSA-ACO), to solve the optimization with combined economic emission dispatch. This problem has been formulated as a multi-objective problem by considering both economy and emission simultaneously. The feasibility of the proposed approach was tested on 3-unit and 6-unit systems. The simulation results show that the proposed algorithm gives comparatively better operational fuel cost and emission in less computational time compared to other optimization techniques.


2021 ◽  
Vol 6 (4) ◽  
Author(s):  
Ibrahim Abdulwahab ◽  
Shehu A. Faskari ◽  
Talatu A. Belgore ◽  
Taiwo A. Babaita

This paper presents an improved hybrid micro-grid load frequency control scheme for an autonomous system. The micro-grid system comprises of renewable and non-renewable energy-based Power Generating Units (PGU) which consist of Solar Photovoltaic, WT Generator, Solar Thermal Power Generator, Diesel Engine Generator, Fuel Cell (FC) with Aqua Electrolizer (AE). However, power produce from renewable sources in microgrid are intermittent in supply, hence make it difficult to maintain power balance between generated power and demand. Therefore, Battery energy storage system, ultra-capacitor and flywheel energy storage systems make up the energy storage units. These separate units are selected and combined to form two different scenarios in this study.  This approach mitigates frequency fluctuations during disturbances (sudden load changes) by ensuring balance between the generated power and demand. For each scenario, Moth flame optimization algorithm optimized Proportional-Integral controllers were utilized to control the micro-grid (to minimize fluctuations from the output power of the non-dispatchable sources and from sudden load change). The results of the developed scheme were compared with that of Quasi-Oppositional Harmony Search Algorithm for overshoot and settling time of the frequency deviation. From the results obtained, the proposed scheme outperformed that of the quasi-oppositional harmony search algorithm optimized controller by an average percentage improvement of 35.95% and 28.76% in the case of overshoot and settling time when the system step input was suddenly increased. All modelling analysis were carried out in MATLAB R2019b environment. Keywords—Frequency Deviation, Micro-grid, Moth flame optimization algorithm, Quasi-Oppositional Harmony Search Algorithm.


2011 ◽  
Vol 474-476 ◽  
pp. 1666-1671
Author(s):  
Yi Wen Wang ◽  
Min Yao

A new meta-heuristic optimization algorithm–harmony search is conceptualized using the musical improvisation process of searching for a perfect state of harmony. Although several variants and an increasing number of applications have appeared, one of its main difficulties is how to select suitable parameter values. In this paper, we proposed a novel algorithm to dynamically adapt the harmony memory consideration rate (HMCR) and pitch adjustment rate (PAR) and distance bandwidth (BW). The experimental results revealed the superiority of the proposed method to the original HS, improved harmony search (IHS) and global-best harmony search (GHS).


2013 ◽  
Vol 2013 ◽  
pp. 1-16 ◽  
Author(s):  
S. K. Saha ◽  
R. Dutta ◽  
R. Choudhury ◽  
R. Kar ◽  
D. Mandal ◽  
...  

In this paper, opposition-based harmony search has been applied for the optimal design of linear phase FIR filters. RGA, PSO, and DE have also been adopted for the sake of comparison. The original harmony search algorithm is chosen as the parent one, and opposition-based approach is applied. During the initialization, randomly generated population of solutions is chosen, opposite solutions are also considered, and the fitter one is selected asa prioriguess. In harmony memory, each such solution passes through memory consideration rule, pitch adjustment rule, and then opposition-based reinitialization generation jumping, which gives the optimum result corresponding to the least error fitness in multidimensional search space of FIR filter design. Incorporation of different control parameters in the basic HS algorithm results in the balancing of exploration and exploitation of search space. Low pass, high pass, band pass, and band stop FIR filters are designed with the proposed OHS and other aforementioned algorithms individually for comparative optimization performance. A comparison of simulation results reveals the optimization efficacy of the OHS over the other optimization techniques for the solution of the multimodal, nondifferentiable, nonlinear, and constrained FIR filter design problems.


Author(s):  
Khai Phuc Nguyen ◽  
Goro Fujita ◽  
Vo Ngoc Dieu

Abstract This paper presents an application of Cuckoo search algorithm to determine optimal location and sizing of Static VAR Compensator. Cuckoo search algorithm is a modern heuristic technique basing Cuckoo species’ parasitic strategy. The Lévy flight has been employed to generate random Cuckoo eggs. Moreover, the objective function is a multiobjective problem, which minimizes loss power, voltage deviation and investment cost of Static VAR Compensator while satisfying other operating constraints in power system. Cuckoo search algorithm is evaluated on three case studies and compared with the Teaching-learning-based optimization, Particle Swarm optimization and Improved Harmony search algorithm. The results show that Cuckoo search algorithm is better than other optimization techniques and its performance is also better.


Author(s):  
DSNM Rao ◽  
Niranjan Kumar

This paper discusses economic load dispatch Problem is modeled with non-convex functions. These are problem are not solvable using a convex optimization techniques. So there is a need for using a heuristic method. Among such methods Teaching and Learning Based Optimization (TLBO) is a recently known algorithm and showed promising results. This paper utilized this algorithm to provide load dispatch solutions. Comparisons of this solution with other standard algorithms like Particle Swarm Optimization (PSO), Differential Evolution (DE) and Harmony Search Algorithm (HSA). This proposed algorithm is applied to solve the load dispatch problem for 6 unit and 10 unit test systems along with the other algorithms. This comparisional investigation explored various merits of TLBO with respect to PSO, DE, and HAS in the field economic load dispatch.


2016 ◽  
Vol 17 (5) ◽  
pp. 555-566 ◽  
Author(s):  
H. E. Keshta ◽  
A. A. Ali ◽  
E. M. Saied ◽  
F. M. Bendary

Abstract Large-scale integration of wind turbine generators (WTGs) may have significant impacts on power system operation with respect to system frequency and bus voltages. This paper studies the effect of Static Var Compensator (SVC) connected to wind energy conversion system (WECS) on voltage profile and the power generated from the induction generator (IG) in wind farm. Also paper presents, a dynamic reactive power compensation using Static Var Compensator (SVC) at the a point of interconnection of wind farm while static compensation (Fixed Capacitor Bank) is unable to prevent voltage collapse. Moreover, this paper shows that using advanced optimization techniques based on artificial intelligence (AI) such as Harmony Search Algorithm (HS) and Self-Adaptive Global Harmony Search Algorithm (SGHS) instead of a Conventional Control Method to tune the parameters of PI controller for SVC and pitch angle. Also paper illustrates that the performance of the system with controllers based on AI is improved under different operating conditions. MATLAB/Simulink based simulation is utilized to demonstrate the application of SVC in wind farm integration. It is also carried out to investigate the enhancement in performance of the WECS achieved with a PI Controller tuned by Harmony Search Algorithm as compared to a Conventional Control Method.


Author(s):  
R. Sagayaraj ◽  
S. Thangavel

This paper is an extension of our previous work, which discussed the difficulty in implementing different methods of resistance emulation techniques on the hardware due to its control constant estimation delay. In order to get rid of the delay this paper attempts to include the meta-heuristic methods for the control constants of the controller. To achieve the minimum Total Harmonic Disturbance (THD) in the AC side of the converter modern meta-heuristic methods are compared with the traditional methods. The convergence parameters, which are primary for the earlier estimation of the control constants, are compared with the measured parameters, tabulated and tradeoff inference is done among the methods. This kind of implementation does not need the mathematical model of the system under study for finding the control constants. The parameters considered for estimation are population size, maximum number of epochs, and global best solution of the control constants, best THD value and execution time. MatlabTM /Simulink based simulation is optimized with the M-file based optimization techniques like Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Cuckoo Search Algorithm, Gravity Search Algorithm, Harmony Search Algorithm and Bat Algorithm.


2013 ◽  
Vol 32 (9) ◽  
pp. 2412-2417
Author(s):  
Yue-hong LI ◽  
Pin WAN ◽  
Yong-hua WANG ◽  
Jian YANG ◽  
Qin DENG

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