Forecasting and data analysis

The objective is to develop a computational model specified from a complete and conceptually robust mathematical formulation, capable of projecting the evolution of demand and prices for energy and backup capacity for both the free and regulated markets, considering the insertion of distributed generation.

The model is structured in Julia. To re-establish the dynamic between the regulated and free markets, a stochastic market equilibrium is used, which integrates multi-stage stochastic optimization and game theory. For the modeling of the agents, it is considered that each of them seeks to maximize their risk-adjusted expected revenue, using the CVaR metric. To establish the equilibrium, the maximization of Welfare is used, that is, to maximize the sum of the objective functions of all agents, respecting the risk profile of each one, with MOPED being used for modeling the constraints. Furthermore, the developed model is integrated with the OptGen (expansion optimization) and OptFolio (contracting optimization from the agent’s perspective) models, to evaluate how the generator’s perspective differs from the centralized planner’s view regarding the viability of building new generation capacity, and to determine the expansion with the lowest systemic cost.

Support in the execution of Research and Development activities for Subproject 3 – Impact Analysis of the Electric Energy Distribution Tariffs Modernization Project (R&D Modern Tariff)

The Modern Tariff project was conceived with the objective of analyzing different tariff methodologies for the Distribution segment and proposing appropriate methodologies for the Brazilian case. These new methodologies are capable of addressing the challenges faced by the sector in the context of technological transition and changes in consumer behavior. The project is put into practice through three subprojects.

Subproject 1 – Sectoral Strategic Vision focuses on taking a strategic look at the changes occurring in the international electricity sector to observe the main trends and challenges worldwide. From this international perspective, Subproject 1 seeks to translate these trends to the context of the Distribution segment of the Brazilian Electric Sector (SEB), resulting in scenarios for the diffusion of distributed energy resources.

Based on the analyzed strategic scenario, Subproject 2 – Tariff Design Methodologies for Wire Service and Implementation Challenges aims to evaluate existing tariff design methodologies to propose new tariff modalities for the SEB, considering the scenarios of distributed resource diffusion. Given its importance and complexity, the scope of Subproject 2 is addressed by two executors: one dealing with short-term tariff proposals and the other with the elaboration of long-term tariff proposals. In this sense, various proposals for wire tariff methodologies are simulated using real data from the Brazilian context. Furthermore, in this subproject, simulation tools are generated to facilitate the analysis of the proposals by sector agents and disseminate knowledge. Also within the scope of Subproject 2, a sample survey is conducted with residential and commercial low-voltage consumers in urban and rural areas with national geographical coverage. The survey allows for evaluating consumer understanding of their tariff and bill, as well as consumer acceptance of new forms of pricing.

Finally, Subproject 3 – Regulatory Impact Analysis qualitatively and quantitatively evaluates the impacts of each proposed tariff modality resulting from Subproject 2 on agents in the consumption, generation, and distribution segments. The impact analysis considers technical and regulatory aspects of the Brazilian electricity sector and the development of software to evaluate consumer behavior regarding the possibility of meeting demand response or inserting distributed generation and storage in their homes.

The objective of this project is to propose a methodology and a computational model in Excel to identify and reify the risks of each generation investment alternative so that they can be compared on the same basis, thus assisting agents in their investment decisions. It is proposed to use a methodology based on the risk-return concept to compare all projects, where the IRR under risk conditions is determined, taking into account the complementarity resulting from a diversified portfolio. The focus is on renewable energy projects, but the computational system is generic enough to accommodate other generation sources, as well as synergies with Light’s portfolio.

Initially, a mapping of risk factors and project pricing is carried out: at this stage, the main risk factors of each generation technology are identified, such as hydrological risk, environmental risk, construction risk, technological risk, exchange rate, and fuel. For each of these items, it is proposed to translate the risk factors into scenarios with their respective probabilities of occurrence. In this way, the system allows the user to model the uncertainty of the investment cost through scenarios with different investment cost values, each associated with different probability values. Additionally, the user can generate different scenarios for the evolution of indexers, in order to capture the risk of investment indexing and combine it with other risks also modeled. The regulatory agency (in the Brazilian case, ANEEL) establishes a series of strict financial penalties in case of delay in the plant’s entry into operation. The modeling of these penalties and the simulation of possible delay scenarios are included in this system. The user can model the uncertainty in the plant’s entry-into-operation date through scenarios with different delay periods and different costs associated with this delay (this cost can even be linked to the PLD), each associated with different probability values. With this, the user can simulate the impact on the project’s profitability of these possible delays, combining this risk with other risks also modeled. Subsequently, a model for evaluating investments under uncertainty is proposed, which determines the competitiveness of a generation project by considering its risks, uncertainties, and according to the entrepreneur’s degree of risk aversion. Finally, the last part proposes a methodology for comparing different generation investment technologies by considering their intrinsic uncertainties and risks, illustrating how to calculate the risk premium of each investment alternative and verifying the impact of each project’s intrinsic uncertainty on the variance of its expected return. The methodology can also be extended to analyze a portfolio of projects, determining the gain from combining different generation asset investments in the same portfolio versus the individual candidate projects.

This R&D project investigates the factors that interfere with the performance of the MRE, includes a case study in the São Francisco river basin, and identifies consumptive uses from meteorological data and satellite images and the net evaporation of reservoirs. To achieve this, it applies artificial intelligence techniques.

Development of a methodology for valuing the energetic, electrical, and systemic attributes of using BESS (Battery Energy Storage Systems) in the National System, aiming to increase flexibility, reliability, and resilience in the presence of intermittent renewable sources.