Comparison of Uncertainty Management Approaches in the Planning of Hybrid Solar Generation and Storage Systems as Non-Wire Alternatives

Demand electrification is creating new operating conditions in distribution networks—such as congestion, overloads, and voltage issues—that have traditionally been addressed through network expansion planning (NEP). As an alternative, this work proposes the use of non-wire alternatives (NWAs) based on hybrid photovoltaic–storage (ESS) plants and analyzes their siting and sizing under uncertainty conditions. To this end, a MINLP model with a DistFlow representation is formulated to determine generation and storage locations and capacities, minimizing investment while satisfying current and voltage limits. Different uncertainty management methodologies are compared: robust optimization, equivalent probabilistic profile, weighted multi-scenario, and multi-scenario with penalty. The results on the CIGRE MV network show that the robust approach guarantees feasibility in the worst case, albeit with a high investment cost. In contrast, methods based on averages or simple weightings fail to adequately capture adverse conditions, while the multi-scenario optimization with expected penalty emerges as the most effective option, balancing investment and overload reduction. In conclusion, the explicit consideration of uncertainty in NWA planning is essential to obtaining realistic and adaptable solutions, with the expected penalty formulation standing out as the most efficient alternative for network operators.