<![CDATA[This study proposes a risk-based arrester placement optimization method to improve the protection of substation systems against lightning and switching surges, using the NSGA-II (Non-Dominated Sorting Genetic Algorithm II) algorithm and Electromagnetic Transients (EMT) simulation. The main objective of this study is to reduce the Expected Annual Risk (EAR) related to equipment damage and operational costs through optimal arrester placement, while minimizing the Life-Cycle Cost (LCC) of the substation protection system. EMT simulation is used to model the system response to lightning and switching surge events, while NSGA-II is used to solve a multi-objective optimization problem, considering various potential locations and different arrester ratings. The optimization results show a clear trade-off between cost and risk reduction, with the best solution providing the optimal balance between risk reduction and lifecycle cost. Several critical locations, such as transformer terminals and incomer lines, were identified as priorities for arrester installation, as they offer significant risk reduction at relatively low cost. The reduction in peak equipment-damaging voltage (BIL) after mitigation with arresters also showed substantial improvement. Sensitivity analysis showed that the protection design remained effective despite variations in external parameters such as lightning density and soil resistivity. With this approach, utilities can make more informed decisions about selecting arrester locations and types that meet their budgets and protection needs, significantly reducing the risk of system failure. The results of this study can guide electricity companies in implementing more efficient and economical substation protection policies, while extending equipment life and improving distribution network reliability.]]>
