ISSN: 1304-7191 | E-ISSN: 1304-7205
Reliability and performance assessment of smart grid integrated with distributed renewable energy sources: A 13-bus case study using MATLAB
1University of Engineering & Management, Jaipur, Rajasthan
Sigma J Eng Nat Sci - DOI: 10.14744/sigma.2026.2153

Abstract

Large-scale integration of RES, including wind and solar, is necessary for the worldwide change to low-carbon along with renewable energy systems. Although these resources have significant favorable effects on the environment and the economic growth, their inherent unpredictability and irregularity pose problems for grid stability, dependability, and power quality. Particularly in distribution networks with a high RES penetration, fluctuation in RE can cause voltage fluctuations, power supply and load demand mismatches, and increased operational uncertainty. Flexible technologies like Battery Energy Storage Systems (BESS) and smart grid solutions are necessary to address these problems. By storing extra energy and supplying it during times of low generation, BESS helps control renewable variability. Real-time monitoring, intelligent control, and enhanced system coordination are all provided by smart grids.
Effective management is essential in hybrid distributed generation systems, which combine grid support, solar, and wind power. Maintaining stability, minimizing power losses, and reducing congestion all depend on this. However, problems with protection coordination, reverse power flow, and an increased demand for precise forecasting and reliability assessment techniques are brought about by the widespread use of distributed generation. This study investigates methods for improving renewable-integrated power systems' efficiency, resilience, and dependability. This paper presents the real time 13 bus system study in which various cases has been studied and reliability indies calculated and studied with help of power world simulator and MATLAB. The results show that the proposed system improves reliability, with SAIFI reduced by 28%, SAIDI reduced by 36%, and LOEE reduced by 4%, while ASAI improves to 0.99954. The research also aims to help build strong, adaptable, and sustainable energy systems that can support high levels of renewable energy.