Demand-side transformation in renewable energy integration: coordinated scenario planning using system dynamics

Effective energy analysis requires examining current and projected consumption of both conventional and renewable sources. Scenario planning (SP) also plays a key role in anticipating how energy sources may evolve. However, system dynamics models lack a structured method for embedding key drivers into scenario design, while SP alone cannot represent the complex feedbacks needed for accurate forecasting. To address these limitations, this study proposes a coordinated scenario planning with system dynamics modeling (CSP-SDM) approach, using an enhanced system dynamics model in Vensim to capture interactions among demographic trends, economic indicators, production patterns, and energy variables. It deploys a scenario design strategy to capture the influence and interdependence among key variables via Mactor software, and K-Means clustering to identify those most critical to scenario outcomes. Clustering of key drivers and prediction power are rigorously validated, demonstrating well-defined groupings and notable predictive accuracy. Scenario Wizard is employed to develop consistent exploratory scenarios, each offering distinct perspectives beyond the baseline scenario, which is grounded in historical data trends (1993–2022). The model integrates demand-side, government, and private sector dynamics. The baseline projects only 11.08 TWh of growth, locked in by low electricity prices, high energy intensity, and limited grid modernization. In contrast, the Adapting to Constraints scenario achieves 28.5 TWh, demonstrating the gains from incremental change. The Balancing Act scenario, more than doubles this output to 57.4 TWh by prioritizing efficiency alongside investment. However, the most transformative outcome is delivered by the Harmony of Acceleration scenario, which unlocks 100.4 TWh of renewable demand.