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Speaker: Sergio Bruno
Title: Strategic risk management: A framework for renewable generation investment under uncertainty
Abstract: Renewable investment may be fostered by applying risk management techniques such as forward contracting, diversification and optimal investment timing. By trading contracts and exploiting the seasonal complementarity of the renewable sources, it is possible to reduce risk exposure. The problem of investment in renewable energy plants may be seen as a multistage stochastic optimization model with integer variables, which is very hard to solve. The main approaches in the current literature simplify the problem by reducing the dimensionality of the scenario tree or by assuming simplifying hypothesis on the stochastic processes. We introduce a renewable investment valuation framework, considering the main uncertainty sources and portfolio investment alternatives. We also present a method to solve, by applying decomposition techniques, the problem of optimal investment in seasonal complementary renewable plants in the Brazilian energy market. This is a multistage stochastic and non-convex problem. Investment policies are devised using an algorithm based on Stochastic Dual Dynamic Programming. Integrality constraints are considered in the forward step, where policies are evaluated, and relaxed in the backward step, where policies are built, to ensure convexity of the recourse functions. We use a Markov Chain to model dependence structure of the stages. Performance evaluation is carried out using the original data, validating our heuristic.  The framework is able to represent the characteristics of the Brazilian FTE and may be applied to similar markets. We incorporate risk aversion with coherent measures of risk.
Joint work with S. Ahmed, A. Shapiro and A. Street.
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Speaker: Arthur Brigatto
Title: On the cost and side effects of time inconsistency in long-term
hydrothermal planning
Abstract: Long-term hydrothermal operation planning makes use of the
stochastic dual dynamic programming (SDDP) algorithm to obtain the optimal
policy. For computational tractability sake, SDDP models often neglect
system details, crucial in the short-term implemented unit dispatch.
Different planned and implemented policies are time inconsistent and might
lead to potentially dangerous system states, which ultimately compromise
the efficiency on the use of system resources. In this talk we describe a
methodology to assess the cost of time inconsistent policies in
hydro-thermal power systems planning. We illustrate side effects of
considering inconsistent policies for some relevant sources of
inconsistency and discuss ways and new algorithms for mitigating them.
Joint work with A. Street and D. Valladão.