Bidirectional softlinking for optimal energy planning
More Info
expand_more
Abstract
The urgent transition to other forms of energy production, delivery and consumption has induced investments in new technologies such as renewable energy sources, storage units and demand response programs. Investments in these assets represent long-term commitments (e.g. 40 years ahead) from civil society, governmental institutions and capital investors. For the latter, traditional long-term investment models and their assumptions have been proven to be sufficiently accurate for decision making. Two core assumptions in these models are that electric demand profiles have recognizable patterns and that the generation side is able to fully follow them.
Nonetheless, with the introduction of the aforementioned technologies in the energy mix, these assumptions may become obsolete. For instance, renewable energy sources are intermittent, storage flattens peaks and valleys of demand curves and demand response introduces randomness in electric consumption. In comparison to long-term investments, however, these operations are much shorter in time (e.g. minutes, hours, days) and they are thus captured by the so-called power system models or short-term operations models.
In this context, this thesis evaluates possible effects that short-term operations may have on long-term investment decisions. To this end, this works first covers the models and computational tools typically used to define long-term investments and short-term operations in the electricity sector. Subsequently, a thorough research is conducted to explore possible methods that allow long-term investment models and short-term operations models to exchange relevant information to achieve a specific target. Among these methods, this work advocates for the bidirectional softlinking (BSL) due to the flexibility it offers to both models to be individually expanded and the ability to keep them apart, as independent entities. This thesis hence shows the potential of BSL, the challenges to adopt this mechanism and the guidelines for future research endeavors that could scale up the applicability of the method to actual power system planning with the inclusion of the aforesaid new technologies.