An Approach to Representing Wind Uncertainties in the Long-Term Operation Planning of Systems with Hydropower Predominance

Intermittent sources, especially wind, have experienced accelerated growth - in the last decade, wind power grew 13 times in Brazil, reaching 19 GW of installed capacity in 726 wind farms and became the second largest source in the electricity mix (10%). According to the Ten Year Expansion Plan, in 2029 the wind power installed capacity will increase more than 2.5 times, reaching 39,500 MW (17.3% of the country's electricity mix).

 In Brazil, expansion and long term operation planning studies have been carried out since 1998 with the support of the NEWAVE model, which has been used in the routine and official activities of sector entities: generation dispatch by the National System Operator; calculation of the spot prices by the Whole Sale Energy Market Entity; expansion planning by the Ministry of Mines and Energy and the Energy Research Company; parameters of public auctions for the purchase of electricity by the Electricity Regulatory Agency; as well as by utilities of the power industry to develop corporate strategies.

 Currently, in accordance with the guidelines of the Electricity Regulatory Agency, the representation of wind generation in the NEWAVE model is currently carried out in a simplified manner, based on the monthly average of the last five years of net generation of each wind farm, aggregated by sub-system and load level, for the entire planning horizon.

 The objective of this work is to describe an approach to be used by the Brazilian power industry to represent the uncertainties of monthly wind power production in the SDDP algorithm applied in the long-term operation planning model, keeping the large-scale stochastic problem still computationally viable, when applied to large interconnected systems, especially with hydroelectric predominance, as is the case of the Brazilian system.

 The approach consists of four main stages: (i) statistical clustering of wind regimes and definition of equivalent wind farms; (ii) evaluation of monthly transfer functions (MTFs) between wind speed and power production; (iii) an integrated model for the generation of monthly multivariate synthetic series of inflows and winds, considering the correlations between wind speeds, between inflows and between wind speeds and inflows; and (iv) representation of the monthly wind power obtained through MTFs in the SDDP algorithm.

 Initial results obtained from the application of the proposed approach to actual configurations of the Brazilian interconnected power system are presented and discussed.