Paper Description Problem Statement: As Mauritius aggressively pursues its goal of 60% renewable energy by 2030, the national grid faces a "stability paradox. " While increasing the number of solar PV parks provides more energy, it also increases the frequency of rapid power ramps caused by the island’s volatile micro-climates. Current strategies, such as the geographic dispersion model proposed by Hookoom and Ramgolam (2022), successfully reduce the overall variance of power output but do not provide a predictive or operational framework for sizing system components like Battery Energy Storage Systems (BESS) against real-time climatic shifts. Methodology & Innovation: This paper introduces an innovative, three-tiered monitoring architecture that treats the atmosphere as a dynamic filter. We categorize data into three distinct layers: Exo-atmospheric (Space Weather): Determining the raw potential before it enters the Mauritian airspace. Atmospheric Attenuation: Quantifying cloud-cover density as a stochastic variable. Ground-Level Actualization: Integrating local variables like wind speed and temperature to assess final inverter efficiency. By mapping this "Space-to-Ground" journey, we apply Queuing Theory (specifically the M/M/c/K model) to the grid. In this model, energy units (photons) are treated as "customers" arriving at the grid "server. " Using a multi-year dataset (2024–2026) across 11 Mauritian locations—ranging from the high-attenuation Central Plateau (Henrietta/Curepipe) to the high-stability coastal zones (Le Morne) —we simulate thousands of "arrival" scenarios. Key Findings: The research demonstrates that intermittency is not a singular island-wide problem but a localized "queuing" challenge. By utilizing the proposed Attenuation Factor (), grid operators can move away from static storage mandates. The paper provides a mathematical proof that integrating Space Weather data into BESS control logic can reduce the required reserve margin by approximately 12%, significantly lowering the Levelised Cost of Electricity (LCOE) for future renewable projects in Mauritius. Contribution to Literature: This work complements existing geographic optimization research by adding a vertical, stochastic layer. It shifts the academic conversation from "where to place solar parks" to "how to intelligently buffer them" using queuing physics and real-time climatic alternatives. It is a critical resource for policymakers at the Central Electricity Board (CEB) and researchers focusing on Small Island Developing States (SIDS).
THUPSEE et al. (2026) studied this question.