Modeling hourly electricity dynamics for policy making in long-term scenarios

Energy policies are often related to the global effort in reducing greenhouse gas emissions through increased use of renewable energies in electricity production. The impact of these policies is usually calculated by energy planning tools. However, the modeling methodologies most currently used are not adequate to simulate long-term scenarios while considering the hourly dynamics of supply and demand. This paper presents an extension of the TIMES energy planning tool for investment decisions in electricity production that considers seasonal, daily and hourly supply and demand dynamics. The inclusion of these dynamics enables the model to produce more accurate results in what concerns the impact of introducing energy efficiency policies and the increased use of renewable energies. The model was validated in São Miguel (Azores, Portugal) for the years 2006-2009, where a comparison with real data showed that the model can simulate the supply and demand dynamics. Further, the long-term analysis shows that the inclusion of these dynamics contributes to a better assessment of the renewable energy potential, suggests the postponement of investments in new generation capacity, and demonstrates that using fine time resolution modeling is very valuable for the design of effective policy measures under high renewable penetration energy systems.