Power
Nicholas Kwesi Prah II; Elvis Twumasi; Emmanuel Asuming Frimpong
Abstract
The Combined Economic Emission Dispatch (CEED) is an important consideration in every power system. In this paper, a modified Mayfly Algorithm named Modified Individual Experience Mayfly Algorithm (MIE-MA) is used to solve the CEED optimization problem. The modified algorithm enhances the balance between ...
Read More
The Combined Economic Emission Dispatch (CEED) is an important consideration in every power system. In this paper, a modified Mayfly Algorithm named Modified Individual Experience Mayfly Algorithm (MIE-MA) is used to solve the CEED optimization problem. The modified algorithm enhances the balance between exploration and exploitation by utilizing a chaotic decreasing gravity coefficient. Additionally, instead of the MA relying solely on the best position, it calculates the experience of a mayfly by averaging its positions. The CEED problem is modeled as a nonlinear optimization problem constrained with four equality and inequality constraints and tested on a grid-connected microgrid that consists of four dispatchable distributed generators and two renewable energy sources. The performance of the MIE-MA on the CEED problem is compared to Particle Swarm Optimisation (PSO), an MA variant that incorporates a levy flight algorithm named IMA and Dragonfly Algorithm (DA) using the MATLAB R2021a software. The MIE-MA achieved the best optimum cost of 11306.6 $/MWh, compared to 12278.0 $, 12875.8$, and 17146.4$ of the DA, IMA, and PSO respectively. The MIE-MA also achieved the best average optimum cost over 20 runs of 12163.48 $, compared to 12555.36 $, 13419.67 $, and 17270.08 $ of the DA, IMA, and PSO respectively. The hourly cost curve of the MIE-MA was also the best compared to the other algorithms. The MIE-MA algorithm thus achieves superior optimal values with fewer iterations.
Power
Elvis Twumasi; Yussif Seini Abdul-Fatawu; Emmanuel Asuming Frimpong
Abstract
The optimal size and location of series capacitors is a critical challenge in a distribution network. In this paper, a novel approach for enhancing voltage stability in distribution networks through the optimal sizing and placement of series capacitors is proposed. The study introduces a technique to ...
Read More
The optimal size and location of series capacitors is a critical challenge in a distribution network. In this paper, a novel approach for enhancing voltage stability in distribution networks through the optimal sizing and placement of series capacitors is proposed. The study introduces a technique to determine the optimal lines for connecting series capacitors based on line reactance and current. A modified Elephant Herding Optimization (MEHO) algorithm was used to determine the reactance sizes of the series capacitors and the best lines to place them for optimum system performance. To evaluate the effectiveness of the proposed method, three series capacitors are placed and sized in the standard IEEE 33-bus radial distribution system for stability enhancement. A comparison is conducted between the proposed MEHO algorithm-based approach, the original Elephant Herding Optimization (EHO) algorithm, and the IGWO-TS-based methods reported in the literature. The evaluation is performed by analyzing the system voltage profile, total system losses, and system voltage deviation index under varying loading conditions of 30%, 100%, and 120% of the system nominal loading. Results demonstrate that the proposed MEHO algorithm-based approach outperforms the other two methods significantly in all the scenarios, highlighting its effectiveness in voltage stability enhancement in distribution networks.