Inherent Risk Analysis of Power Supply Management: Case of Belize’s System Operator and Third-Party Actors

System operators (SOs) manage power supply, focusing on risk management. In small emerging economies, proactive risk management is crucial as major disruptions require SOs to redirect resources into recovery efforts. Therefore, SOs prioritize risk reduction, proactively minimizing the possibility of major disruption to ensure the industry's long-term advancement. However, SOs frequently focus on residual risk mitigation while ignoring their exposure to inherent risk. This study investigated the inherent risks associated with power supply management using the SO's operations and pertinent third parties. It used a seasonal multivariate strategy to identify risk factors, create univariate distribution models, and generate multivariate distributions using the copula method. Joint risk exposure was calculated using different percentile metrics for each scenario, allowing for a comparison of exposure levels. The study found that risk variables can sometimes reinforce or offset each other, impacting exposure behaviour. Exposure levels indicate periods of increased or decreased exposure to risk variables. Copula-modelled interdependencies captured larger exposure levels but had lower unit likelihoods, presenting less conservative exposure forecasts for SO managers. Case 1 exhibited the highest exposure levels in the early dry season (0.237 and 0.179), while case 2 showed peak exposure levels in the late wet season (1.009 and 0.948), along with cases 3 (0.977 and 0.908) and 4 (0.950 and 0.879).