Análise de risco na formação de decisões de pré-despacho em sistemas com elevada penetração eólica

Abstract

The Unit Commitment Problem (UC) in power generation is a difficult problem, traditionally modeled with a mixed-integer optimization formulation. What makes it especially difficult is the time-dependency of the generation decisions, caused by ramping limitation constraints applied mostly to thermal generation, as well as minimum shut down and start up times. The main types of uncertainty are usually taken in account: in the actual load values and the (un)reliability of the generators. The uncertainty in generator availability has been met with a specification of operational reserve policy. The uncertainty in load, taking in account that its magnitude is usually small, is in many cases simply ignored. With the significant inclusion of wind power in the portfolio of a county or region, it is no longer adequate to deal with the UC problem in the traditional way. The uncertainty in wind generation is at least one order of magnitude higher than the uncertainty in load. Moreover, the wind behavior includes the possibility of strong ramping, with important stressing effect on thermal generation. Dealing with such challenges in a business-as-usual manner is doomed to produce sub-optimal solutions and to put the system in jeopardy or cause substantial financial loss with costly emergency actions. The transition to models that take risk in account supposes a change in paradigm in the decisionmaking process in the UC process. Without clear guidelines, operators will tend to over-protect – while under commercial pressure, they may run excessive risks. To help in the transition to a UC decision-making process under uncertainty, this thesis contributes to the set of planning paradigms and makes an attempt to organize the comparative analysis and results and conclusions reached, from an illustrative case built around the IEEE RTS 30-bus system. The results show that the Pareto-optimal front, in a stochastic cost vs. risk space, may not be convex, which precludes the use of simplistic trade-off approaches. The conclusion, as a contribution from this thesis, is unmistakable: a stochastic programming approach is not adequately informative on the risks run as consequence of system operator decisions on unit commitment, in systems with a high penetration of wind power. Models that follow the Risk Analysis paradigm are necessary, in order to quantify the costs of hedging (protecting against adverse scenarios). Furthermore, by relying on an explicit multiple criteria representation, the thesis shows how this risk aversion perspective, in terms of undesired events, may be blended with a stochastic optimization perspective of average gain or expense On the planning matter, embedding the risk in the operating cost annually capitalized assists the decision-making in investments in system planning.