ENHANCING POWER SYSTEM STABILITY THROUGH THE IMPLEMENTATION OF ADVANCED CONTROL STRATEGIES

Abstract

This paper examines how advanced control techniques can be implemented on improving stability of a power system with a growing penetration of renewable energy resources, and decentralization of the grid as well as the rising cyber-physical issues. It expects to calculate the effectiveness rates of these strategies, any obstacles in implementation, and the trends in the future regarding the change to resilient and sustainable power systems. The quantitative research design was used where the data was collected via a structured questionnaire to 315 electrical engineering professionals, such as power system engineers (38.1 percent), researchers (23.8 percent), and power system operators (14.3 percent). The responses provided by the participants in relation to challenges, familiarity with strategies, their effectiveness, adoption barriers and technologies of the future were analyzed using descriptive statistics and visual tools (bar charts, donut charts, and frequency tables). The biggest stability challenges were found to be renewable integration (81.0%) and frequency/voltage fluctuations (66.7%). The perceived effectiveness of AI/ML- based control (71.4 percent familiarity) and adaptive control (57.1 percent) was also high (66.7 percent combined Extremely/Very Effective). Major barriers to adoption were low cost (66.7%) and skill gap (57.1). The most significant perceived future technologies were AI/ML (42.9%) and energy storage (28.6%), and 66.7 percent of the results suggested they would probably invest in sophisticated plans in five years’ time. This research paper presents industry professionals opinions on the assessment of advanced control strategies that fill the gap between the theoretical research and practical implementation. It provides implementable policy and stakeholder recommendations to hasten the practicality of adaptive, data-driven solutions that facilitate grid stability within renewable-dominated systems.

Keywords

Power system stability, Advanced control strategies, Renewable energy integration, AI/ML-based control, Grid resilience