R&D&I Projects
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Analysis for the Improvement of Horoseasonal Signals
The proposal starts with the main potential causes of production cost differences at different hours of the day and months of the year: variations in short-term marginal costs, differences in loss indices, elevation of the tailrace of hydroelectric plants, and inflexible production during the early morning hours. In this stage, the potential impact of each of these possible sources of cost variations is estimated.
Next, a methodology for applying existing tools is developed with the aim of obtaining hourly and seasonal signals for energy, based on marginal costs, incorporating all items identified as relevant in the first stage that are feasible for consideration within the current possibilities of system modeling. The methodology is being evaluated with a view to its possible incorporation into the tariff realignment process within the scope of the periodic tariff review.
Calculation and Revision of Physical Guarantee Certificates in Brazil
Broadly, the R&D project proposes that the distribution of the hydraulic block among hydroelectric plants be carried out based on each plant’s spot income (a methodology known as Marginal Benefit), considering an adjustment to correctly calculate the downstream benefit of existing reservoirs. As a result, it is observed that the new distribution methodology results in a fairer allocation of the GF, increasing the value for plants with reservoirs.
Carbon capture in bioelectricity plants
– Identification of biomasses with potential for large-scale electric power generation
– Conceptual examination of the technical yields of converting these biomasses into electricity
– Construction of a technology landscape for carbon capture in industrial plants
– Conducting a proof of concept for carbon capture
– Financial modeling of the business with risk analysis
– Elaboration of a business case
Carbon Footprint Methodology for Generation and Distribution Systems
The development of a methodology for the Carbon Footprint follows the same process, regardless of the nature of the energy company (distributor or generator). The differences lie in the results of each of the stages described below. Variables such as company size, geographical dispersion, or operational complexity alter the need for work hours and available resources.
Case Study: Modeling Steel, Descarbonization, Options in Brazil
Cash Flow Assessment Model for Generation Projects with Alternative Sources
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.
Combinatorial Auction System for Capacity and Energy Products in the Brazilian Electricity Sector
Demand, Price, and Capacity Forecasting for Energy Markets
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.
Development of a Platform for Managing Availability and Commercialization Risks of Power Generation
In order to adapt the tool to the company’s reality and the actual environment it is subject to, latent risk factors are mapped and modeled, which are integrated into the platform to consider them when outlining new strategies and performing analyses.
The platform is designed to be compatible with a global risk management policy of the company. In other words, this environment is capable of incorporating the constraints and objectives specified for the generation sector, stemming from a corporate risk policy adopted by the company as a whole, and supplying it with the results obtained through both performance indicators and outcome scenarios. In this regard, risk measures and their applicability in realistic contexts are researched to provide risk indicators that are easy to interpret financially and have great power over the control of the modeled risks.
For this purpose, training courses on risk management and the practical use of this platform are provided, with the aim of equipping decision-makers with knowledge and intuition about the models and techniques that the company has at its disposal.
Development of the Natural Gas Market in Brazil for Electric Power Generation
Economic and Socio-environmental Model for the Production of Hydrogen and Low-Carbon Products in the Sugarcane Industry
Feasibility and Regulatory Aspects of Hydrogen Produced via Electrolysis
Generation Assessment System (Genesys) – Software Redevelopment
Hourly Stochastic Operation and Power Reserve for the Brazilian Interconnected System (SIN) with Renewable Source Uncertainties
The number of constraints in the stochastic dispatch problem is reduced due to the affine rules technique. The first set of equations and constraints in the model represents a ‘reference operational trajectory,’ given by the maximum likelihood estimate of the weighted scenarios for demand, renewables, etc. A second, additional set of equations and constraints represents the fact that the actual values of renewable production and demand, each hour, are different from the forecasts. As a consequence, an operational adjustment (a deviation from the reference trajectory) is necessary. The decision variables of the optimization problem under uncertainty are the adjustment coefficients for each generator (similar to Automatic Generation Control), known in the literature as affine decision rules. The final problem corresponds to a large-scale mixed-integer programming (MIP) model. An additional result of the model is the dynamic generation reserve.
Increase in Expansion Auctions in the Institutional Model of the Electric Sector
Insertion of Battery Storage Systems into the Main Grid
Integrated and Flexible Transmission Systems Planning
Integration of Storage to Support Wind Power Generation
Investigation of the factors that interfere with the performance of the MRE
Life Cycle Assessment in Electricity Generation and Storage in Brazil: A Socio-environmental and Energy Approach
The following electricity generation and storage systems are evaluated: (i) Hydroelectric power plants; (ii) Natural gas thermoelectric plants; (iii) Sugarcane biomass generation plants; (iv) Solar photovoltaic plants; (v) Wind power plants; (vi) Pumped-storage hydropower plants; (vii) Lithium-ion batteries.
Finally, a computational tool is built to support decisions regarding the expansion of electricity generation in Brazil.
Methodology for determining the Distribution System Usage Amount (MUSD) procurement strategy
The technique employed is based on:
Stochastic approach: creation of temporally and spatially coherent scenarios for the internal generation and load of the distribution system and the rest of the NIS (National Interconnected System).
Sampling: both time series and non-parametric sampling techniques are used for sampling generation and load scenarios.
Integration: the internal system of the distributor and its relations with the NIS are integrated to create load and generation scenarios.
Simulation horizon: the multi-year simulation horizon (4 years) is discretized into 15-minute time intervals, and power flow simulations are performed for each temporal discretization.
Analysis: firstly, all cases corresponding to 15-minute temporal discretizations are probed by linearized power flow without losses, and then simulations are run for the most severe cases at the connection points, with loss representation.
Integrated contracting: the MUSD/MUST (Maximum Contracted Demand/Maximum Contracted Energy) is contracted under a risk criterion using a classic mathematical programming approach.
Methodology for Selecting Locations for the Implementation of Pumped-Storage Hydropower Plants
Mineral Coal Supply Optimization System for Thermal Power Plants (MOCCA)
Modelagem de Termelétricas e Terminal de Regaseificação para Nomeação de Cargas de GNL sob Incertezas
Modernization of Electricity Distribution Tariffs
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.
New regulatory models for compensating future distributors
This involves mapping and analyzing international experiences in the regulation of electricity distribution aimed at the insertion of DERs and distributed service platforms, followed by a diagnosis of the current regulation in Brazil vis-à-vis the international experience. With these inputs, and considering an analysis of the trends and impacts of Distributed Energy Resources on the electricity sector (and, in particular, on the electricity distribution activity) and distributed service platforms, an initial proposal for improving the current regulation of energy distribution is constructed. This proposal is then subjected to a qualitative analysis (through SWOT matrices) and a quantitative analysis (with the two simulation models built in the project). The results of these analyses lead to the consolidation of the final version of the proposal for improving distribution regulation.
Planning for Generation-Transmission Expansion with Pumped-Storage Hydropower Plants
Project META II – Price Formation
Proposals of Methodologies for Offer Price Formation in Brazil
Regulatory Incentives for Digital Solutions to Improve Hydropower Generation Performance
Software for the Assessment of Hydropower Potential and Division of Falls
The model’s objective function maximizes the economic benefits of the hydrographic basin’s energy development, considering the costs of civil works, electromechanical equipment, and socio-environmental aspects of the candidate projects. The formulation of this mathematical problem and the search for solution methods is, without a doubt, the most original aspect of this project. There are also other original aspects, such as: (i) The development of a computational architecture for distributed execution (in the cloud) during the candidate project construction phase, which requires intensive computational processing to execute Geographic Information System (GIS) functions; and (ii) The automatic generation of project budgets through unit costs (informed by the user) and quantities of the different structures of the candidate projects (i.e., dams, spillways, turbines, etc.) that are dimensioned according to the Eletrobrás Inventory Manual.
Technical-Commercial Insertion of Solar Photovoltaic Generation in the Distribution Grid
UK Pact – Energy Transition and Industrial Descarbonization in Brazil – Support the Steel Industry to Achieve Sectoral Mitigation Goals
Wind Turbine Integrated with Solar, Storage, and Hydraulic Energy Sources as a Development Platform
This project develops an intelligent hybrid generation system for R&D, focused on a control capable of stable and optimized operation and maintenance. The central pillar of this innovation is the development of the STORM (Stochastic Optimization for Renewable Energy Management) model, which uses real-time simulators and stochastic optimization algorithms to ensure qualified performance based on temporal forecasts on a scale of hours, days and months.
Solar and wind intermittency in power plants can cause instabilities throughout the electrical system and the local grid. Recent technological solutions point to the integrated use of wind and solar plants at the same location. This project, through the intelligence of the STORM model, contributed to a smarter integration of the national energy system and one better suited to local characteristics, based on wind energy integrated with other energy conversion processes. Equipment and systems are introduced that represent an innovative alternative for improving the quality, efficiency and reliability of the electrical power generation system. The project is thus configured as a platform for the development of solutions to improve intelligent and integrated operation, supervision and control, providing the best emerging technologies for the electricity sector.
