Summary:
In the face of the global climate crisis, countries worldwide are striving for climate neutrality, necessitating a shift from fossil fuels to renewable energy sources. This energy transition faces deep uncertainties, requiring strategic energy planning to consider them and their interrelationships to avoid suboptimal decisions based on incoherent scenarios. This study applies a novel robust optimization approach to incorporate correlations between primary energy prices and energy technology investment costs into openMASTER, a long-term energy planning model. Using Spain's 2030 decarbonization goals as a case study, we assess the impact of accounting for these correlations on strategic energy decisions. Our results reveal that decarbonization strategies significantly vary with the correlation level. A positive correlation leads to higher fossil fuel use and lower renewable deployment, while a negative correlation results in maximum renewable deployment and electrification. The uncorrelated scenario incurs higher costs, highlighting savings when correlations are introduced. This study also provides policy insights and recommendations for future energy planning.
Spanish layman's summary:
Este estudio aplica una nueva técnica para incorporar las correlaciones entre incertidumbres de precios de la energía y costes de las tecnologías en openMASTER, un modelo de planificación energética. El caso de estudio de la descarbonización del sistema energético español para 2030 muestra el impacto de estas correlaciones en las estrategias de planificación energética.
English layman's summary:
This study applies a novel robust optimization approach to incorporate correlations between uncertain energy prices and technology costs into openMASTER, a strategic energy planning. Applied to Spain's 2030 decarbonization goal, results show the impact of these correlations on energy planning strategies.
Keywords: Long-term energy planning, uncertainty, correlation, Spain, energy model.
Registration date: 20/06/2024
IIT-24-196WP
