We are glad to invite you to a seminar by Dr. David Pozo, titled “Hierarchical Optimization and Equilibrium in Energy System Planning”
Proactive or anticipative transmission and generation expansion planning models have been proposed to jointly model the interactions among deregulated electricity market participants making market-driven investment decisions. Several works have shown that a Transmission Network Planner can increases social welfare by anticipating line expansion planning to generation expansion equilibrium and market outcomes. However, transmission expansion decisions may lead to suboptimal solutions when the generation expansion equilibrium problem have multiple solutions (i.e., leading to higher total costs and lower social welfare). We propose a methodology that serves as a tool for Regulators and Network Planners to study the potential impacts of proactive expansion planning on generation expansion decisions. The resulting formulation is stated as a mathematical program subject to an equilibrium problem with equilibrium constraints (EPEC). We also propose a new approach to derive tractable EPEC solutions with global optimality guaranteed based on a column-and-row generation algorithm. Our numerical results show that a proactive investment plan can lead to higher total cost than not investing at all the because of the existence of multiple market-driven generation expansion equilibria. Regarding computational time results, we show that the proposed algorithm significantly reduces the time of computation up to two orders of magnitude with respect to existing methodologies.
Dr. David Pozo is Electrical Engineer (2006) and Ph.D. (2013) both from the University of Castilla-La Mancha, Spain. He is currently a Research Fellow at Pontifical Catholic University of Chile and a Research Associate at Pontifical Catholic University of Rio de Janeiro. He has been visiting researcher at Hong Kong University and University of Southampton. His interests include power systems economics, electricity markets, game theory, hierarchical optimization problems and stochastic MPEC and EPECs models.
If you like to participate and for further information or questions, please Liliya Abaimova.