scholarly journals Enhanced GSA-Based Optimization for Minimization of Power Losses in Power System

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Gonggui Chen ◽  
Lilan Liu ◽  
Shanwai Huang
Keyword(s):  
Power Systems ◽  
Power System ◽  
Reactive Power ◽  
Power Transmission ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Heuristic Method ◽  
Mixed Integer ◽  
Mixed Integer Nonlinear Optimization ◽  
Power Loss Reduction

Gravitational Search Algorithm (GSA) is a heuristic method based on Newton’s law of gravitational attraction and law of motion. In this paper, to further improve the optimization performance of GSA, the memory characteristic of Particle Swarm Optimization (PSO) is employed in GSAPSO for searching a better solution. Besides, to testify the prominent strength of GSAPSO, GSA, PSO, and GSAPSO are applied for the solution of optimal reactive power dispatch (ORPD) of power system. Conventionally, ORPD is defined as a problem of minimizing the total active power transmission losses by setting control variables while satisfying numerous constraints. Therefore ORPD is a complicated mixed integer nonlinear optimization problem including many constraints. IEEE14-bus, IEEE30-bus, and IEEE57-bus test power systems are used to implement this study, respectively. The obtained results of simulation experiments using GSAPSO method, especially the power loss reduction rates, are compared to those yielded by the other modern artificial intelligence-based techniques including the conventional GSA and PSO methods. The results presented in this paper reveal the potential and effectiveness of the proposed method for solving ORPD problem of power system.

scholarly journals Optimal Reactive Power Scheduling Using Cuckoo Search Algorithm

2017 ◽  
Vol 7 (5) ◽  
pp. 2349 ◽  
Author(s):  
Surender Reddy Salkuti
Keyword(s):  
Power System ◽  
Reactive Power ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Optimization Techniques ◽  
Mixed Integer ◽  
Integer Programming Problem ◽  
Scheduling Problem ◽  
Power Scheduling

<p>This paper solves an optimal reactive power scheduling problem in the deregulated power system using the evolutionary based Cuckoo Search Algorithm (CSA). Reactive power scheduling is a very important problem in the power system operation, which is a nonlinear and mixed integer programming problem. It optimizes a specific objective function while satisfying all the equality and inequality constraints. In this paper, CSA is used to determine the optimal settings of control variables such as generator voltages, transformer tap positions and the amount of reactive compensation required to optimize the certain objective functions. The CSA algorithm has been developed from the inspiration that the obligate brood parasitism of some Cuckoo species lay their eggs in nests of other host birds which are of other species. The performance of CSA for solving the proposed optimal reactive power scheduling problem is examined on standard Ward Hale 6 bus, IEEE 30 bus, 57 bus, 118 bus and 300 bus test systems. The simulation results show that the proposed approach is more suitable, effective and efficient compared to other optimization techniques presented in the literature.</p>

scholarly journals Reduction of Annual Operational Costs in Power Systems through the Optimal Siting and Sizing of STATCOMs

2021 ◽  
Vol 11 (10) ◽  
pp. 4634
Author(s):  
Oscar Danilo Montoya ◽  
Jose Eduardo Fuentes ◽  
Francisco David Moya ◽  
José Ángel Barrios ◽  
Harold R. Chamorro
Keyword(s):  
Power Systems ◽  
Power System ◽  
Reactive Power ◽  
Programming Model ◽  
Operating Cost ◽  
Mathematical Optimization ◽  
System Optimization ◽  
Point Of View ◽  
Mixed Integer ◽  
Annual Operating Cost

The problem of the optimal siting and placement of static compensates (STATCOMs) in power systems is addressed in this paper from an exact mathematical optimization point of view. A mixed-integer nonlinear programming model to present the problem was developed with the aim of minimizing the annual operating costs of the power system, which is the sum of the costs of the energy losses and of the installation of the STATCOMs. The optimization model has constraints regarding the active and reactive power balance equations and those associated with the devices’ capabilities, among others. To characterize the electrical behavior of the power system, different load profiles such as residential, industrial, and commercial are considered for a period of 24 h of operation. The solution of the proposed model is reached with the general algebraic modeling system optimization package. The numerical results indicate the positive effect of the dynamic reactive power injections in the power systems on annual operating cost reduction. A Pareto front was built to present the multi-objective behavior of the studied problem when compared to investment and operative costs. The complete numerical validations are made in the IEEE 24-, IEEE 33-, and IEEE 69-bus systems, respectively.

scholarly journals Gravitational Search Algorithm Based Technique for Voltage Stability Improvement

2018 ◽  
Vol 9 (1) ◽  
pp. 123
Author(s):  
Mohamad Khairuzzaman Mohamad Zamani ◽  
Ismail Musirin ◽  
Mohamad Sabri Omar ◽  
Saiful Izwan Suliman ◽  
Nor Azura Md. Ghani ◽  
...  
Keyword(s):  
Power System ◽  
Voltage Stability ◽  
Reactive Power ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Test System ◽  
Optimization Process ◽  
Optimal Reactive Power Dispatch ◽  
Reactive Power Dispatch ◽  
Gravitational Search

<p>Voltage instability problem has been known as a significant threat to power system operation since its occurrence can lead to power interruption. This phenomenon can be due to uncontrollable load increment, line and generator outage contingencies or unplanned load curtailment. Optimal reactive power dispatch involving reactive power support can be one of the options for improving voltage stability of a power system, which also requires optimization process. Optimal sizing and location can of reactive power support can avoid the system from experiencing over-compensated or under-compensated phenomena. The presence of optimization techniques has helped solving non-optimal phenomenon, nevertheless some setbacks have also been experienced in terms of inaccuracy and stuck in local optima. This paper presents the application of Gravitational Search Algorithm (GSA) technique in attempt to solve optimal reactive power dispatch problem in terms of reactive power support for voltage stability improvement. Optimization process tested on IEEE 14-bus Reliability Test System (RTS) has revealed its superiority with significant promising results in terms of voltage stability improvement in the test system. </p>

scholarly journals Efficient Operative Cost Reduction in Distribution Grids Considering the Optimal Placement and Sizing of D-STATCOMs Using a Discrete-Continuous VSA

2021 ◽  
Vol 11 (5) ◽  
pp. 2175
Author(s):  
Oscar Danilo Montoya ◽  
Walter Gil-González ◽  
Jesus C. Hernández
Keyword(s):  
Objective Function ◽  
Reactive Power ◽  
Programming Model ◽  
Search Algorithm ◽  
Solution Space ◽  
Distribution Networks ◽  
Optimal Placement ◽  
Mixed Integer ◽  
Solution Vector ◽  
The Impact

The problem of reactive power compensation in electric distribution networks is addressed in this research paper from the point of view of the combinatorial optimization using a new discrete-continuous version of the vortex search algorithm (DCVSA). To explore and exploit the solution space, a discrete-continuous codification of the solution vector is proposed, where the discrete part determines the nodes where the distribution static compensator (D-STATCOM) will be installed, and the continuous part of the codification determines the optimal sizes of the D-STATCOMs. The main advantage of such codification is that the mixed-integer nonlinear programming model (MINLP) that represents the problem of optimal placement and sizing of the D-STATCOMs in distribution networks only requires a classical power flow method to evaluate the objective function, which implies that it can be implemented in any programming language. The objective function is the total costs of the grid power losses and the annualized investment costs in D-STATCOMs. In addition, to include the impact of the daily load variations, the active and reactive power demand curves are included in the optimization model. Numerical results in two radial test feeders with 33 and 69 buses demonstrate that the proposed DCVSA can solve the MINLP model with best results when compared with the MINLP solvers available in the GAMS software. All the simulations are implemented in MATLAB software using its programming environment.

scholarly journals Simultaneous Placement and Sizing of Distributed Generation Units and Shunt Capacitors on Radial Distribution Systems Using Cuckoo Search Algorithm

2021 ◽  
pp. 43-58
Author(s):  
Sunday Adeleke Salimon ◽  
Gafari Abiola Adepoju ◽  
Isaiah Gbadegesin Adebayo ◽  
Oluwadamilare Bode Adewuyi ◽  
Saheed Oluwasina Amuda
Keyword(s):  
Radial Distribution ◽  
Distribution Systems ◽  
Reactive Power ◽  
Search Algorithm ◽  
Stability Index ◽  
Cuckoo Search ◽  
Optimal Placement ◽  
Power Loss Reduction ◽  
Operational Test ◽  
Shunt Capacitors

This paper presents a Cuckoo Search (CS) algorithm-based methodology for simultaneous optimal placement and sizing of Shunt Capacitors (SCs) and Distributed Generations (DGs) together in radial distribution systems. The objectives of the work are to minimize the real power and reactive power losses while maximizing the voltage stability index of the distribution network subjected to equality and inequality constraints. Different operational test cases are considered namely installation of SCs only, DGs only, SCs before DGs, DGs before SCs, and SCs and DGs at one time. The proposed method has been demonstrated on standard IEEE 33-bus and a practical Ayepe 34-bus radial distribution test systems. The highest percentage power loss reduction of 94.4% and other substantial benefits are obtained when SCs and DGs are optimally installed simultaneously. Simulated results obtained from the proposed technique are compared with other well-known optimization algorithms and found to be more effective.

scholarly journals Modified SCA algorithm for SSSC damping Controller design in Power System

2017 ◽  
Vol 16 (1) ◽  
pp. 46-63 ◽  
Author(s):  
Bidyadhar Rout ◽  
B.B. Pati ◽  
S. Panda
Keyword(s):  
Power System ◽  
Transient Stability ◽  
Controller Design ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Differential Evolution Algorithm ◽  
Operating Conditions ◽  
Bench Mark ◽  
Single Machine Infinite Bus ◽  
System Stabilizer

This paper studies the improvement of transient stability of a single-Machine Infinite-Bus (SMIB) power system using Proportional Derivative (PD) type Static Synchronous Series Compensator (SSSC) and damping controllers. The design problem has been considered as optimisation problem and a modified version of recently proposed Sine Cosine Algorithm (SCA) has been employed for determining the optimal controller parameters. Proposed modified SCA (mSCA) algorithm is first tested using bench mark test functions and compared with SCA, and other heuristic evolutionary optimization algorithms like Grey Wolf optimization (GWO), Particle Swarm optimization (PSO), Gravitational Search algorithm (GSA) and Differential Evolution algorithm to show its superiority. The proposed mSCA algorithm is then applied to optimize simultaneously the PD type lead lag controller parameters pertaining to SSSC and power system stabilizer(PSS). The proposed controller provides sufficient damping for power system oscillation in different operating conditions and disturbances. Results analysis reveal that proposed mSCA technique provides higher effectiveness and robustness in damping oscillations of the power system and increases the dynamic stability more.

scholarly journals MINIMIZATION OF REAL POWER LOSS BY ENHANCED GRAVITATIONAL SEARCH ALGORITHM

2017 ◽  
Vol 5 (7) ◽  
pp. 623-630
Author(s):  
K. Lenin
Keyword(s):  
Local Minimum ◽  
Global Minimum ◽  
Reactive Power ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Gravitational Forces ◽  
Bee Colony ◽  
Gravitational Search ◽  
The Masses ◽  
Power Problem

In this paper, Enhanced Gravitational Search (EGS) algorithm is proposed to solve the reactive power problem. Gravitational search algorithm (GSA) results are improved by using artificial bee colony algorithm (ABC). In GSA, solutions are fascinated towards each other by applying gravitational forces, which depending on the masses assigned to the solutions, to each other. The heaviest mass will move slower than other masses and pull others. Due to nature of gravitation, GSA may pass global minimum if some solutions stuck to local minimum. ABC updates the positions of the best solutions that have obtained from GSA, preventing the GSA from sticking to the local minimum by its strong penetrating capability. The proposed algorithm improves the performance of GSA in greater level. In order to evaluate the performance of the proposed EGS algorithm, it has been tested on IEEE 57,118 bus systems and compared to other standard algorithms.

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