Information from the abstract
Escalating energy demand and the evolving landscape of power transmission have intensified the operational pressures on electrical grids, specifically during N-1 contingency events. The unexpected loss of a single transmission circuit often precipitates critical system instabilities, including power flow congestion, voltage degradation, and heightened transmission losses. While conventional grid expansion remains the standard for maintaining reliability, its implementation is frequently hindered by lengthy permitting processes, significant capital investment, and regulatory complexities. This research offers an alternative by presenting a robust optimization-based framework for the strategic placement and sizing of a battery energy storage system (BESS) within the Electricity Generating Authority of Thailand (EGAT) transmission network. Focusing on the N-1 contingency resulting from the 115 kV Thatako Substation (TTKS)–Bueng Sam Phan Substation (BGSS) circuit outage during peak load hours, this study introduces the musk ox optimizer (MOO) to solve the complex, non-linear allocation problem. The objective function is formulated to minimize cumulative system costs while enforcing strict network operational envelopes. Simulation results indicate that the optimized BESS configuration achieves compliant grid performance, successfully restoring the post-fault bus voltage, enhancing voltage profile, reducing transmission losses, and mitigating peak line loading. These findings demonstrate that the proposed MOO-based strategy provides a physically compliant, flexible, and robust non-wire alternative for transmission constraint management, confirming its viability as a sustainable, low-environmental-impact framework for enhancing modern grid resilience and utility development.
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This record has an Impact Signal of 71/100 based on recency, source, collaboration, and bibliographic signals. It prioritizes monitoring and is not a judgment of research quality.
Related topics: Optimal Power Flow Distribution · Electric Power System Optimization · Microgrid Control and Optimization
Thai researcher and institutional participation
Sirote Khunkitti · Mukravee Thongnoi · Apirat Siritaratiwat · Chiang Mai University · King Mongkut's Institute of Technology Ladkrabang
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