Attia A. El-Fergany

Single and Multi-objective Optimal Power Flow Using Grey Wolf Optimizer and Differential Evolution Algorithms

Abstract This article applies the grey wolf optimizer and differential evolution (DE) algorithms to solve the optimal power flow (OPF) problem. Both algorithms are used to optimize single objective functions sequentially under the system constraints. Then, the DE algorithm is utilized to solve multi-objective OPF problems. The indicator of the static line stability index is incorporated into the OPF problem. The fuzzy-based Pareto front method is tested to find the best compromise point of multi-objective functions. The proposed algorithms are used to determine the optimal values of the continuous and discrete control variables. These algorithms are applied to the standard IEEE 30-bus and 118-bus systems with different scenarios. The simulation results are investigated and analyzed. The achieved results show the effectiveness of the proposed algorithms in comparison with the other recent heuristic algorithms in the literature.

Study impact of various load models on DG placement and sizing using backtracking search algorithm

A recently BSA-based approach is employed to assign DGs.Various load models are taken into consideration.The methodology is tested on the 69- and the 136-node two different radial distribution systems.Substantial decline in power losses and voltage scheme enhancement are cropped. In this article, a meta-heuristic technique based on a backtracking search algorithm (BSA) is employed to produce solutions to ascertain distributed generators (DGs). The objective is established to reduce power loss and improve network voltage profile in radial distribution networks by determining optimal locations and sizes of the DGs. Power loss indices and bus voltages are engaged to explore the initial placement of DG installations. The study cares with the DG type injects active and reactive power. The proposed methodology takes into consideration four load models, and their impacts are addressed. The proposed BSA-based methodology is verified on two different test networks with different load models and the simulation results are compared to those reported in the recent literature. The study finds that the constant power load model among various load models is sufficed and viable to allocate DGs for network loss and voltage studies. The simulation results reveal the efficacy and robustness of the BSA in finding the optimal solution of DGs allocation.

Artificial Bee Colony Algorithm to Allocate Fixed and Switched Static Shunt Capacitors in Radial Distribution Networks

Abstract This article introduces an efficient heuristic-based approach to assign static shunt capacitors along radial distribution networks using the artificial bee colony algorithm. The objective function is adapted to enhance the overall system static voltage stability index and to achieve maximum net yearly savings. Load variations have been considered to optimally scope the fixed and switched capacitors required. The numerical results are compared with those obtained using recent heuristic methods and show that the proposed approach is capable of generating high-grade solutions and validated viability.

Multi-objective Capacitor Allocations in Distribution Networks using Artificial Bee Colony Algorithm

This article addresses an efficient heuristic-based approach to assign static shunt capacitors along radial distribution networks using the artificial bee colony algorithm. The objective function is adapted to enhance the overall system static voltage stability index and to achieve maximum net yearly savings. Load variations have been considered to optimally scope the fixed and switched capacitors required. The numerical results are compared with those obtained using recent heuristic methods and show that the proposed approach is capable of generating high-grade solutions and validated viability.

Cuckoo Search-based Algorithm for Optimal Shunt Capacitors Allocations in Distribution Networks

Abstract In this article, a Cuckoo search optimization-based approach has been applied to allocate static shunt capacitors along radial distribution networks. The objective function is adapted to reduce the system peak losses, to support the system voltage profile, and to improve overall system power factor. Higher potential buses for capacitor placement are initially identified using a power loss index. At that moment, the proposed approach identifies optimal sizing and placement and takes the final decision for optimum location within the number of buses nominated with a minimum number of effective locations and with fewer injected VARs. The overall accuracy and performance of the proposed approach have been validated and tested on 33- and 69-bus radial distribution systems. The numerical results are compared with those obtained using recent heuristic methods, and statistical analysis proved that the problem-solving success of the cuckoo search are quite better than other heuristic methods.

Efficient Tool to Characterize Photovoltaic Generating Systems Using Mine Blast Algorithm

Abstract—The article proposes an efficient tool to characterize the photovoltaic generating systems. The mine blast algorithm is coupled with the proposed tool to define the parameters for commercial real photovoltaic cells. The objective function is adapted to minimize the absolute errors between the experimental measured and calculated current values to accurately estimate the photovoltaic parameters. The experimental, performance, and technical data of the commercial photovoltaic cells of many manufacturers with different photovoltaic types are used to confirm the viability of the proposed method. Both single-diode and double-diode models of solar cells are approached to certify the performance of the proposed methodology. The calculated I-V and P-V characteristics are well matched to measured data with insignificant absolute errors. The study finds that the single-diode equivalent circuit suffices to precisely model the photovoltaic cells. Numerical comparisons to the other competitive heuristic methods consolidate the significance of the proposed mine blast algorithm based method.

Multi-objective Allocation of Multi-type Distributed Generators along Distribution Networks Using Backtracking Search Algorithm and Fuzzy Expert Rules

Abstract This article presents a methodology for a multi-objective optimal allocation of multi-type distributed generators in radial distribution networks based on a backtracking search algorithm. The study aims to prove the validity and the strength of the backtracking search algorithm multi-objective method on distributed generator allocation. The multi-objective function is expressed to minimize the network power losses, to consolidate the static voltage stability indices, and to ameliorate the buss voltage profile. The indicators of loss sensitivity factors and bus voltage magnitudes are incorporated to establish set of fuzzy expert rules to assort the preliminary buses for distributed generator placement. The proposed methodology allows the fuzzy decision maker to decide the best compromise solution among the offered Pareto-optimal solutions. The salient features of the backtracking search algorithm are demonstrated and marked on 33- and 94-node radial distribution networks with various scenarios. The cropped results are compared with those reported by others in the literature, validating and signifying the proposed approach. The study finds that the type-3 distributed generator unit (delivers P and injects Q) is most preferred to reduce power losses along network lines and to boost both the bus voltage profile and voltage stability indices.

Water cycle algorithm-based economic dispatcher for sequential and simultaneous objectives including practical constraints

Abstract The article presents an efficient methodology based-on water cycle algorithm (WCA) to solve single and multiple objectives of economic load dispatch (ELD) aiming to generate the optimal value of the active generated power for each unit. Three objectives are adopted for optimisation either sequentially or concurrently; they are: (i) fuel cost considering valve-ripple effect, (ii) emission rate, and (iii) total network loss. The generating unit prohibited zones along with ramp rate limits and generating unit power limits specify the inequality constraints of the problem while maintaining system power balance. Usually, optimisation of simultaneous multiple objectives produces set of non-dominated Pareto-front solutions. To help the decision maker, the best compromise solution is carefully picked among optimal Pareto-front points. The proposed WCA-based methodology is demonstrated on three test cases with various complexities and under number of objective scenarios. Numerical results and further subsequent comparisons to other challenging optimisers indicate the viability and confirm the strength of the proposed WCA-based ELD method.

Reactive power compensation in distribution networks using cuckoo search algorithm

This manuscript presents a cuckoo search optimisation-based approach to allocate static shunt capacitors along radial distribution networks. The objective function is adapted to reduce the system peak losses and to improve the system voltage profile. Higher potential buses for capacitor placement are initially identified using power loss index. The proposed approach identifies optimal sizing and placement and takes the final decision for optimum location. The overall accuracy and reliability of the approach have been validated and tested on radial distribution systems with differing topologies and of varying sizes and complexities. The results are compared with those obtained using recent heuristic methods and show that the proposed approach is capable of producing high-quality solutions with good performance of convergence.

Improved performance of PEM fuel cells stack feeding switched reluctance motor using multi-objective dragonfly optimizer

In this article, a switched reluctance motor (SRM) powered by autonomous stacked proton exchange membrane fuel cells (PEMFC)’s stack with the purpose of optimizing their operating performances is addressed. Three key performance indices are examined that include: (1) torque per ampere ratio, (2) torque smoothness factor and (3) average starting torque. The later mentioned adapted indices characterize the objective functions that can be optimized individually and concurrently using a novel application of multi-objective dragonfly approach (MODA). The MODA is applied to generate the optimal turn (on/off) angles of H-bridge converter and the gains of a proportional-integral speed controller. A Pareto front optimal solutions are made, and the final best compromise solution is carefully chosen. The terminal voltage of the PEMFC is fine controlled by a boost converter, to overcome the noticeable decline of its voltage profile with the increase in loading current. The system under study is demonstrated at various loading conditions with necessary comparisons to other recent competing methods complete with subsequent discussions. The cropped numerical results indicate that PEMFC energy saving, reduction in SRM torque ripples and PEMFC current ripples can be enhanced. In addition, higher average starting torque of the SRM is realized.