International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 11 Issue: 06 | Jun 2024
p-ISSN: 2395-0072
www.irjet.net
Optimal Integration of Distributed Energy Resources in Distribution Network Using Nature Inspired Artificial Intelligence Techniques Apoorva Rajpoot, M. Tech Student, Department of Electrical Engineering, Government Women Engineering College, Ajmer. Pushpendra Singh, Assistant Professor, Department of Electrical Engineering, Government Women Engineering College, Ajmer. ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract— This research proposes a unique technique to optimize the integration of distributed energy resources (DERs) inside distribution networks, with the goal of improving system performance and meeting ancillary service requirements. This study employs Metaheuristic Optimization Techniques, especially a hybrid ABC-WOA algorithm, to determine the ideal position and size of DERs. The proposed model's effectiveness is assessed using detailed simulations of benchmark distribution systems, including the IEEE 33-bus and 69-bus test networks. Using MATLAB 2021a and the MATPOWER 7.1 toolbox, the optimization procedure exhibits remarkable convergence behavior, as shown in convergence graphs for both systems. The findings show considerable improvements in voltage profile and a decrease in active power losses after the installation of DGs, demonstrating the efficacy of the suggested strategy. Detailed analyses, including voltage magnitudes, active power losses, and comparison tables displaying the locations and capacities of the DGs, demonstrate the ABC-WOA-based optimization model's practical feasibility and benefits in improving the integration of DERs into distribution networks. Key Words: Distributed energy resources (DERs), Distribution network, Metaheuristic optimization techniques, ABC-WOA algorithm, System performance, Optimization, Voltage profile.
1. INTRODUCTION In recent years, there have been several improvements in the electric power industry. Customers are becoming pickier about dependability and power quality, while distribution network operators (DNOs) are being forced to increase energy efficiency to save costs as a result of the current trend toward deregulation in the power industry. Shunt capacitors (SCs) and distributed generators (DGs) are two examples of distributed energy resources (DERs) that are crucial for obtaining increased energy efficiency in distribution system functioning. To meet smart grid efficiency objectives of loss reduction and high-quality electricity provided to the end user, integrated solutions to well-formulated challenges that reflect the reality on the ground where all such devices coexist are needed[1]. While
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improper DER placement may raise system losses as well as network capital and operating costs, optimal DER placement can enhance network performance in terms of better node voltage profiles, decreased power flows, reduced feeder losses, improved power quality, and reliability of electric supply. Regardless of the specific motivation for a DNO, such as permitting the connection of more DG capacity, decreasing energy losses, or enhancing network dependability, the DG planning tools need to include fundamental network limitations like voltage and heat thresholds[2]. In recent times, there have been several efficacious endeavors to address the issue of the ideal distribution of either SCs or DGs independently[3]. Nevertheless, the deployment strategy of DERs in tandem is more feasible and can independently configure and manage the flow of both reactive and actual power in a distribution network (DN) [4]. Using analytical or heuristic techniques, this simultaneous allocation method and have shown the mutual influence of these devices on the distribution network's performance. An analytical method for the simultaneous installation of SCs and DGs to minimize investment costs. By using an analytical technique to identify voltage support zones, they narrowed the search area, and then used a hybrid ABC-WOA to address the issue. ABC-WOA technique was used to ascertain the ideal position and amount of distributed generation (DG) power factor in order to reduce power losses under different circumstances[5].It has been shown that the results have significantly improved in terms of loss reduction and voltage profile improvement. A heuristic method in which the best candidate sites are found by a node sensitivity analysis, and the capacity of the SCs/DGs is then found through the recommendation of a heuristic curve fitting procedure. To address this multi-objective optimization issue, a combined imperialist competitive algorithm (ICA)–genetic algorithm (GA) approach. Using this strategy, dispersed resource placement and size are initially determined by the ICA, and these solutions are then further refined by the GA operators[6].
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