Unified robust–stochastic dispatch for reliable net-zero microgrids under PV uncertainty

Reliable operation of net-zero microgrids requires dispatch strategies that remain sustainable under both probabilistic and worst-case variations of renewable generation and demand. Deterministic optimisation assumes perfect forecasts and collapses under real PV fluctuations or load uncertainty. Stochastic optimisation enhances adaptability by modelling probabilistic deviations, whereas robust optimisation guarantees feasibility under the most adverse conditions. Achieving true reliability, therefore, requires integrating both perspectives within a unified, uncertainty-aware methodology.This study develops a reliability-oriented optimisation and evaluation methodology that unifies deterministic, robust, stochastic, and stochastic–robust dispatch paradigms within a networked net-zero microgrid (N-NZMG) comprising photovoltaic (PV) generation, battery energy storage, and flexible loads. A continuous linear programming formulation ensures tractable computation while enforcing battery, network, and daily net-zero constraints. To enable fair comparison across uncertainty treatments, a normalised multi-criteria ranking scheme is introduced to convert heterogeneous performance indicators into unified dimensionless scores.Simulation results under Australian solar conditions demonstrate that deterministic dispatch maintains ideal performance only under perfect forecasts but rapidly deteriorates when PV output fluctuates. The robust strategy maintains feasibility across all irradiance levels while increasing battery cycling by about 17 %. The stochastic formulation effectively adapts to probabilistic PV fluctuations and load uncertainty, maintaining the net-zero balance within 10⁻⁴ kWh and limiting curtailment to below 0.05 %. The hybrid stochastic–robust case yields results comparable to those of the robust case, with enhanced resilience under severe variability.The proposed unified methodology advances the concept of reliable net-zero operation by showing how probabilistic adaptability and worst-case protection can jointly sustain microgrid performance during fluctuations in renewable and demand sources. It offers a structured and scalable pathway toward reliability-driven optimisation of renewable-dominated energy systems.