Optimal placement, sizing and operation of D-STATCOMs in power distribution systems using a Mixed-Integer Linear Programming model

Power distribution systems (PDS) face increasing challenges due to rising power demand, the integration of distributed generation (DG), and voltage stability concerns. To address these issues, this study proposes a novel Mixed-Integer Linear Programming (MILP) model for the optimal placement, sizing, and operation of D-STATCOMs in radial distribution systems. Unlike existing methods, the proposed approach incorporates multi-period optimization, considering daily active and reactive power demand curves to dynamically adjust reactive power support throughout the day. The model is implemented in AMPL and solved using the CPLEX solver, ensuring globally optimal solutions. Numerical validation is performed on three test systems: 33-bus, 69-bus, and a simplified 136-bus PDS from Presidente Prudente, Brazil. The results demonstrate that the MILP model achieves up to a 23% reduction in energy losses and provides economic benefits of up to 15%, while also enhancing voltage stability. Additionally, the study presents new results for the 136-bus test system, which had not been previously reported in the literature. The findings demonstrate the effectiveness and scalability of the proposed MILP model, making it a practical tool to optimize power distribution system performance. Future research may extend this approach to meshed networks and stochastic demand scenarios. • Mixed-Integer Linear Programming (MILP) model for planning and operation of D-STATCOM. • Multi-period optimization considers daily active and reactive power demand curves. • The MILP model ensures global optimality, surpassing traditional non-linear methods. • The MILP model is validated on the 33-bus, 69-bus, and 136-bus test systems. • The MILP model can be implemented using commercial optimization software.