Marginal Cost of Energy Volatility in the Brazilian Interconnected Power System

From 2018 to 2022, on average, 70% of the Brazilian effective electric generation was produced by hydropower, 10% by wind power, and 20% by thermal power plants. Over the last five years, Brazil suffered from a series of severe droughts. As a result, hydropower generation was reduced, but demand growth was also declined as results of the COVID-19 pandemic and economic recession. From 2012 to 2022, the Brazilian reservoir system operated with, on average, only 40% of the active storage, but storage recovered to normal levels in the first three months of 2022. Despite large capacity of storage reservoirs, high volatility of the marginal cost of energy was observed in recent years. In this paper, we used two optimization models, NEWAVE and HIDROTERM for our study. These two models were previously developed for mid-range planning of the operation of the Brazilian interconnected power system. We used these two models to optimize the operation and compared the results with observed operational records for the period of 2018-2022. NEWAVE is a stochastic dual dynamic programming model which aggregates the system into four subsystems and 12 equivalent reservoirs. HIDROTERM is a nonlinear programming model that considers each of the 167 individual hydropower plants of the system. The main purposes of the comparison are to assess cooperation opportunities with the use of both models and better understand the impacts of increasing uncertainties, seasonality of inflows and winds, demand forecasts, decisions about storage in reservoirs, and thermal production on energy prices. © World Environmental and Water Resources Congress 2023.All rights reserved

Impacts of the COVID-19 pandemic on the Brazilian hydrothermal system

Hydropower has been the predominant source of electrical energy supply in Brazil, with significant increasing participation share of thermal and wind power plants. From 2000 to 2012, on average, 91% of Brazilian effective electric generation was provided by hydropower, while the reservoir system operated, on average, at 68% of the active storage. From 2013 to 2020, 73% was supplied by hydropower plants, with only 39% of active storage. Demand increase, delays in expanding the system, and a series of moderate to severe droughts occurred in Brazil over the last eight years have contributed to bringing the power system to its current state of low storage levels and intense dispatch of the thermal plants. The COVID-19 pandemic in 2020 hit the country hard and brought an abrupt reduction in energy demand, with persistent impacts expected for the coming years. On average, 7.5 GW or 9.7% reduction is expected for the next three years in power demand. To deal with the reduction in demand, a well-planned adaptation strategy is urgently needed. It is important to plan how to efficiently combine reduction of dispatching the most expensive thermal plants and recover water levels of reservoir storage and productivity in the complex hydrosystem with over 150 reservoirs. To determine the tradeoff and adaptation strategy, we use the HIDROTERM model, a nonlinear programming optimization model previously developed for planning the operation of the Brazilian hydrothermal system for analysis by comparing results with demand forecasts before and during the pandemic and under different hydrological scenarios. © ASCE.