Impact of Slack Bus Compensation on Voltage Stability in Power Grids Integrated with Electric Vehicles: A Machine Learning Approach for Intelligent Management
Journal Title: Journal of Intelligent Management Decision - Year 2024, Vol 3, Issue 4
Abstract
The integration of Electric Vehicles (EVs) into modern power grids presents both challenges and opportunities. This study investigates the influence of slack bus compensation on the stability of voltage levels within these grids, particularly as EV penetration increases. A comprehensive simulation framework is developed to model various grid configurations, accounting for different scenarios of EV load integration. Historical charging data is meticulously analysed to predict future load patterns, indicating that heightened levels of EV integration lead to a notable decrease in voltage stability. Specifically, voltage levels were observed to decline from 230 V to 210 V under conditions of 100% EV penetration, necessitating an increase in slack bus compensation from 0 MW to 140 MW to sustain system balance. Advanced machine learning techniques are employed to forecast real-time load demands, significantly reducing both Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), thereby optimising slack bus performance. The results underscore the critical role of real-time load forecasting and automated control strategies in addressing the challenges posed by EV integration into power grids. Furthermore, the study demonstrates that intelligent systems, coupled with machine learning, can enhance power flow management and bolster grid stability, ultimately improving operational efficiency in the distribution of energy. Future research will focus on refining machine learning models through the utilisation of more granular data sets and exploring decentralized control methodologies, such as federated learning, thereby providing valuable insights for grid operators as the adoption of EVs continues to expand.
Authors and Affiliations
Harpreet Kaur Channi, Khushi Sehgal, Swapandeep Kaur
Keywords
Related Articles
- EP ID EP752399
- DOI https://doi.org/10.56578/jimd030401
- Views 17
- Downloads 0
Analysis of the Impact of Artificial Intelligence in Enhancing the Human Resource Practices
The lethal coronavirus illness (COVID-19) has evoked worldwide discussion. This contagious, sometimes fatal illness, is caused by the severe acute respiratory syndrome coronavirus 2. So far, COVID-19 has quickly spread t...
High-Performance Carbon Cycle Supply Data Sharing Method Based on Blockchain Multichain Technology
In the evolution of blockchain technology, the traditional single-chain structure has faced significant challenges, including low throughput, high latency, and limited scalability. This paper focuses on leveraging multic...
FMEA-QFD Approach for Effective Risk Assessment in Distribution Processes
This study applies the FMEA-QFD approach to assess risks in the distribution process, with a focus on warehouse and transport processes, which are commonly associated with user dissatisfaction and customer loss. The meth...
Integrated Multi-objective Optimization of Predictive Maintenance and Production Scheduling: Perspective from Lead Time Constraints
For the integrated optimization of job-shop production scheduling and predictive maintenance, this paper fully considers such constraints as product delivery time and changing machine failure rate, and establishes a mult...
Selection of Logistics Distribution Channels for Final Product Delivery: FUCOM-MARCOS Model
An analytical approach was adopted to ascertain the optimal distribution channel for Bingo LLC's final products, deploying a multifaceted decision-making framework that incorporated the Full Consistency Method (FUCOM) an...