scholarly journals Improved Coyote Optimization Algorithm for Optimally Installing Solar Photovoltaic Distribution Generation Units in Radial Distribution Power Systems

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-34 ◽  
Author(s):  
Thang Trung Nguyen ◽  
Thai Dinh Pham ◽  
Le Chi Kien ◽  
Le Van Dai

This paper proposes an improved coyote optimization algorithm (ICOA) for optimizing the location and sizing of solar photovoltaic distribution generation units (PVDGUs) in radial distribution systems. In the considered problem, four single objectives consisting of total power losses, capacity of all PVDGUs, voltage profile index, and harmonic distortions are minimized independently while satisfying branch current limits, voltage limits, and harmonic distortion limits exactly and simultaneously. The performance of the proposed ICOA method has been improved significantly since two improvements were carried out on the two new solution generations of the conventional coyote optimization algorithm (COA). By finding four single objectives from two IEEE distribution power systems with 33 buses and 69 buses, the impact of each proposed improvement and two proposed improvements on the real performance of ICOA has been investigated. ICOA was superior to COA in terms of capability of finding higher quality solutions, more stable search ability, and faster convergence speed. Furthermore, we have also applied five other metaheuristic algorithms consisting of biogeography-based optimization (BBO), genetic algorithm (GA), particle swarm optimization algorithm (PSO), sunflower optimization (SFO), and salp swarm algorithm (SSA) for dealing with the same problem and evaluating further performance of ICOA. The result comparisons have also indicated the outstanding performance of ICOA because it could find much better results than these methods, especially SFO, SSA, and GA. Consequently, the proposed ICOA is a very effective method for finding the optimal location and capacity of PVDGUs in radial distribution power systems.

Energies ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 174 ◽  
Author(s):  
Minh Duong ◽  
Thai Pham ◽  
Thang Nguyen ◽  
Anh Doan ◽  
Hai Tran

This paper presents an effective biogeography-based optimization (BBO) for optimal location and sizing of solar photovoltaic distributed generation (PVDG) units to reduce power losses while maintaining voltage profile and voltage harmonic distortion at the limits. This applied algorithm was motivated by biogeography, that the study of the distribution of biological species through time and space. This technique is able to expand the searching space and retain good solution group at each generation. Therefore, the applied method can significantly improve performance. The effectiveness of the applied algorithm is validated by testing it on IEEE 33-bus and IEEE 69-bus radial distribution systems. The obtained results are compared with the genetic algorithm (GA), the particle swarm optimization algorithm (PSO) and the artificial bee colony algorithm (ABC). As a result, the applied algorithm offers better solution quality and accuracy with faster convergence.


2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Varaprasad Janamala

AbstractA new meta-heuristic Pathfinder Algorithm (PFA) is adopted in this paper for optimal allocation and simultaneous integration of a solar photovoltaic system among multi-laterals, called interline-photovoltaic (I-PV) system. At first, the performance of PFA is evaluated by solving the optimal allocation of distribution generation problem in IEEE 33- and 69-bus systems for loss minimization. The obtained results show that the performance of proposed PFA is superior to PSO, TLBO, CSA, and GOA and other approaches cited in literature. The comparison of different performance measures of 50 independent trail runs predominantly shows the effectiveness of PFA and its efficiency for global optima. Subsequently, PFA is implemented for determining the optimal I-PV configuration considering the resilience without compromising the various operational and radiality constraints. Different case studies are simulated and the impact of the I-PV system is analyzed in terms of voltage profile and voltage stability. The proposed optimal I-PV configuration resulted in loss reduction of 77.87% and 98.33% in IEEE 33- and 69-bus systems, respectively. Further, the reduced average voltage deviation index and increased voltage stability index result in an improved voltage profile and enhanced voltage stability margin in radial distribution systems and its suitability for practical applications.


2021 ◽  
Vol 11 (2) ◽  
pp. 774 ◽  
Author(s):  
Ahmed S. Abbas ◽  
Ragab A. El-Sehiemy ◽  
Adel Abou El-Ela ◽  
Eman Salah Ali ◽  
Karar Mahmoud ◽  
...  

In recent years, with the widespread use of non-linear loads power electronic devices associated with the penetration of various renewable energy sources, the distribution system is highly affected by harmonic distortion caused by these sources. Moreover, the inverter-based distributed generation units (DGs) (e.g., photovoltaic (PV) and wind turbine) that are integrated into the distribution systems, are considered as significant harmonic sources of severe harmful effects on the system power quality. To solve these issues, this paper proposes a harmonic mitigation method for improving the power quality problems in distribution systems. Specifically, the proposed optimal planning of the single tuned harmonic filters (STFs) in the presence of inverter-based DGs is developed by the recent Water Cycle Algorithm (WCA). The objectives of this planning problem aim to minimize the total harmonic distortion (THD), power loss, filter investment cost, and improvement of voltage profile considering different constraints to meet the IEEE 519 standard. Further, the impact of the inverter-based DGs on the system harmonics is studied. Two cases are considered to find the effect of the DGs harmonic spectrum on the system distortion and filter planning. The proposed method is tested on the IEEE 69-bus distribution system. The effectiveness of the proposed planning model is demonstrated where significant reductions in the harmonic distortion are accomplished.


This paper provides a new approach for solving the problem of network reconfiguration in the presence of Whale Optimization Algorithm (WOA). It is aimed at reducing actual power loss and enlightening the voltage profile in the supply system. The voltage and branch current capacity constraints have been included in the objective function evaluation. The method has been evaluated at three separate heuristic algorithms on 33-bus radial distribution systems to demonstrate the performance and effectiveness of the proposed method. In this paper the comparison of performance of two latest optimization techniques such as Whale Optimization Algorithm (WOA) with classic optimization techniques such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The new optimization technique produces better result compare to other two optimization logarithm..


Author(s):  
Mounika Kannan ◽  
Kirithikaa Sampath ◽  
Srividhya Pattabiraman ◽  
K Narayanan ◽  
Tomonobu Senjyu

Abstract Abnormal Voltages in electrical distribution system is a threat to power system security and may cause equipment damages. Reconfiguration aids in the proper distribution of load and thus improving the voltage profile. The multi objective framework including node voltage deviation as primary objective and power loss and reliability as secondary objectives is formulated. The novel meta heuristic method based on binary particle swarm optimization (BPSO) is employed to find the optimal radial distribution network configuration for an assortment of objective function. The effect of inertia weight, position and population of swarm is deeply investigated. The proposed method has been verified on IEEE 33 and 69 bus radial distribution systems and found to be effective in minimizing node voltage deviation. The impact of the reconfigured system on voltage deviation, power loss and reliability has been studied extensively. BPSO calculations are found to be simple and has good Convergence characteristics in comparison with other meta heuristic techniques.


2019 ◽  
Vol 2019 ◽  
pp. 1-20 ◽  
Author(s):  
Khalid Mohammed Saffer Alzaidi ◽  
Oguz Bayat ◽  
Osman N. Uçan

Distributed generators (DGs) are currently extensively used to reduce power losses and voltage deviations in distribution networks. The optimal location and size of DGs achieve the best results. This study presents a novel hybridization of new metaheuristic optimizations in the last two years, namely, salp swarm algorithm (SSA) and whale optimization algorithm (WOA), for optimal placement and size of multi-DG units in radial distribution systems to minimize total real power losses (kW) and solve voltage deviation. This hybrid algorithm is implemented on IEEE 13- and 123-node radial distribution test systems. The OpenDSS engine is used to solve the power flow to find the power system parameters, such power losses, and the voltage profile through the MATLAB coding interface. Results describe the effectiveness of the proposed hybrid WOA-SSA algorithm compared with those of the IEEE standard case (without DG), repeated load flow method, and WOA and SSA algorithms applied independently. The analysis results via the proposed algorithm are more effective for reducing total active power losses and enhancing the voltage profile for various distribution networks and multi-DG units.


Author(s):  
Miloš Milovanović ◽  
Jordan Radosavljević ◽  
Bojan Perović ◽  
Milorad Dragičević

This paper presents the results of power flow calculations in the presence of harmonics in radial distribution systemsobtained using the decoupled harmonic power flow (DHPF) algorithm. In this algorithm, the interaction among the harmonicfrequencies is assumed to be negligible and hence the calculations are separately performed for every harmonic order of interest. Adetailed methodology for calculating current and voltage high order harmonics, harmonic losses and total harmonic distortion ofvoltage of the electrical distribution networks in the frequency domain is presented. The standard backward/forward sweep method isused for solving the power flow problem at the fundamental frequency. Furthermore, some practical and approximated models ofnetwork components in harmonic analysis are given. The performance of the DHPF approach is studied and evaluated on two standardtest systems with nonlinear loads, the distorted IEEE 18-bus and IEEE 33-bus. Nonlinear loads are treated as harmonic current sourcesthat inject harmonic currents into the system. The DHPF algorithm is verified by comparing its results with those generated bysoftware tools for the analysis of transmission, distribution and industrial power systems (i.g. ETAP and PCFLO). Simulation resultsshow the accuracy and efficiency of the applied procedure for solving the harmonic power flow problem.


Author(s):  
Hazim Sadeq Mohsin Al-Wazni ◽  
Shatha Suhbat Abdulla Al-Kubragyi

This paper presents a hybrid algorithm by applying a hybrid firefly and particle swarm optimization algorithm (HFPSO) to determine the optimal sizing of distributed generation (DG) and distribution static compensator (D-STATCOM) device. A multi-objective function is employed to enhance the voltage stability, voltage profile, and minimize the total power loss of the radial distribution system (RDS). Firstly, the voltage stability index (VSI) is applied to locate the optimal location of DG and D-STATCOM respectively. Secondly, to overcome the sup-optimal operation of existing algorithms, the HFPSO algorithm is utilized to determine the optimal size of both DG and D-STATCOM. Verification of the proposed algorithm has achieved on the standard IEEE 33-bus and Iraqi 65-bus radial distribution systems through simulation using MATLAB. Comprehensive simulation results of four different cases show that the proposed HFPSO demonstrates significant improvements over other existing algorithms in supporting voltage stability and loss reduction in distribution networks. Furthermore, comparisons have achieved to demonstrate the superiority of HFPSO algorithms over other techniques due to its ability to determine the global optimum solution by easy way and speed converge feature.


Sign in / Sign up

Export Citation Format

Share Document