Benchmarking Copula-Based Scenario Models and Risk Criteria for Multi-Market BESS Scheduling in the Greek Electricity Market

This study presents an observed-day-ahead computational benchmark comparing Gaussian, Student-t, first-tree-truncated Gaussian D-vine, and single-parameter Clayton scenarios under expected-value (EV), lower-tail conditional value-at-risk (CVaR), and finite-scenario maximin scheduling of a 20 MWh/10 MW battery in the Greek electricity market. The day-ahead trajectory is fixed, and recourse decisions use complete daily scenarios. An 84-day experiment provides descriptive economic comparisons at finite solver gaps. An additional twelve-date assessment yields 67 accepted solutions out of 144, without a common accepted date across all four copulas under EV or CVaR. Independent recalculation verifies seven accepted EV–CVaR pairs with sampled lower-tail mean increases of EUR 0.17–10.40/day. These changes are interpreted descriptively in view of their magnitude relative to the objective gaps. Full-training D-vine ordering reproduces the historical chain for the supplied input. Source reconciliation identifies first-quarter-hour selection and a one-hour balancing-series offset across 5040 nominal rows in the exact workbook used by the additional experiment. The comparisons are conditional on this representation and assumed balancing-opportunity bounds; the retained records leave uncertainty about the source units and battery-specific interpretation. The study integrates dependence diagnostics, scheduling objectives, numerical precision, and input provenance within a computational benchmark, with operational market performance beyond its empirical scope.