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The quality of electricity is one of the most discussed issues in the regulatory context, structured by guidelines that allow the assessment of efficiency in electricity supply. Regarding electricity distribution systems, it is essential to highlight the aspects associated with the definition of continuity indicators to measure the service provided by the utilities. The parameters used to calculate the indicators are set by specific agencies in each country based on studies and their characteristics. With the growth in demand for electricity, debates associated with reducing greenhouse gas emissions in the atmosphere, and the increase in Distributed Energy Resources (DERs) connected to the grid, a new trend related to the energy supply is verified. Given these new scenarios, this paper presents a literature review in the regulatory field of existing distribution systems in South American countries. The research proposes to analyze, compare, and expose the current models to evaluate their methods and indicators, including a complete case study in Brazil. This paper seeks to illustrate and point out perspectives, challenges, and future perspectives through the collected and analyzed data. [ABSTRACT FROM AUTHOR]

An electric power distribution utility is responsible for providing energy to consumers in a continuous and stable way. Failures in the electrical power system reduce the reliability indexes of the grid, directly harming its performance. For this reason, there is a need for failure prediction to reestablish power in the shortest possible time. Considering an evaluation of the number of failures over time, this paper proposes performing failure prediction during the first year of the pandemic in Brazil (2020) to verify the feasibility of using time series forecasting models for fault prediction. The long short-term memory (LSTM) model will be evaluated to obtain a forecast result that an electric power utility can use to organize maintenance teams. The wavelet transform has shown itself to be promising in improving the predictive ability of LSTM, making the wavelet LSTM model suitable for the study at hand. The assessments show that the proposed approach has better results regarding the error in prediction and has robustness when statistical analysis is performed. [ABSTRACT FROM AUTHOR]

The paper undertakes a dynamic analysis for service quality in the electricity distribution in Brazil between 2010 and 2014 based on Malmquist indexes constructed upon Data Envelopment Analysis (DEA) distance functions. The motivation for the less usual consideration of efficiency frontiers for service quality, that does not rely on traditional inputs and outputs but rather on quality indicators, builds on previous static applications in the context of telecommunications. The analysis considers undesirable technical indicators for quality as inputs and desirable consumer satisfaction indicators for quality as outputs in the efficiency frontier analysis. The bootstrap‐corrected Malmquist indexes indicated service quality deterioration in 38.1 per cent, quality stagnation in 40.5 per cent and quality improvement only in 21.4 per cent of the cases. When one decomposes the Malmquist index, the evidence does not suggest relevant frontier shifts and indicates a dominant role for the catch‐up effect. Finally, Malmquist indexes are regressed against variables that may portray heterogeneities, such as firm size, service area, density, ownership and regional dummies in terms of a well‐known two‐stage procedure. The mostly weak significance results reinforce the plausibility of the initial analysis. [ABSTRACT FROM AUTHOR]

Abstract The paper provides a diagnostic of service quality in electricity distribution in Brazil. Considering indicators related to customer complaints, average time for solving problems, and consumer satisfaction, there are some signs of deterioration over time. To address the multidimensional character of service quality, various well-established multivariate statistical analysis procedures are applied. A cluster analysis suggests that firms cluster into a small number of groups that are not directly related to the geographic region or firm size. A dynamic factor analysis for each firm provides mixed evidence, but in nearly 43% of the cases, important common patterns of indicators are found within firms. A canonical correlation analysis indicates a weak association between direct service quality and overall perceived satisfaction. The nature of firm heterogeneity can potentially provide guidance on how to incorporate service quality adjustments in the price-cap rule. Highlights • The paper provides a diagnostic of service quality in electricity distribution in Brazil. • Taking as a reference, indicators related to complaints, average time for solution of problems and consumer satisfaction, there are signs of deterioration over time. • Cluster analysis suggests that firms cluster into a small number of groups that are not directly related to geographic region or firm size. • Dynamic factor analysis for each firm provides mixed evidence, but in nearly 43% of the cases there are important common patterns of indicators within each firm. • Canonical correlation analysis indicates a weak association between direct service quality and global perceived satisfaction. [ABSTRACT FROM AUTHOR]

The current electricity default rates in continental countries, such as Brazil, pose risks to the economic stability and investment capabilities of distribution utilities. This situation results in higher electricity tariffs for regular customers. From a regulatory perspective, the key issue regarding this challenge is devising incentive mechanisms that reward distribution utilities for their operational and investment choices, aiming to mitigate or decrease electricity non-payment rates and avoid tariff increases for regular customers. Despite adhering to the principles of incentive regulation, the Brazilian Electricity Regulatory Agency (ANEEL) uses a methodological approach to define regulatory targets for electricity defaults tied to econometric models developed to determine targets to combat electricity non-technical losses (NTLs). This methodology has been widely criticized by electricity distribution utilities and academics because it includes many ad hoc steps and fails to consider the components that capture the specificities and heterogeneity of distribution utilities. This study proposes a fuzzy inference-based model for defining regulatory default targets built independently of the current methodological approach adopted by ANEEL and aligned with the principles of incentive regulation. An empirical study focusing on the residential class of electricity consumption demonstrated that it is possible to adopt a specific methodology for determining regulatory default targets and that the fuzzy inference approach can meet the necessary premises to ensure that the principles of incentive regulation and the establishment of regulatory targets are consistent with the reality of each electricity distribution utility. [ABSTRACT FROM AUTHOR]

In this paper, an extended impedance-based fault-location formulation for generalized distribution systems is presented. The majority of distribution feeders are characterized by having several laterals, nonsymmetrical lines, highly unbalanced operation, and time-varying loads. These characteristics compromise traditional fault-location methods performance. The proposed method uses only local voltages and currents as input data. The current load profile is obtained through these measurements. The formulation considers load variation effects and different fault types. Results are obtained from numerical simulations by using a real distribution system from the Electrical Energy Distribution State Company of Rio Grande do Sul (CEEE-D), Southern Brazil. Comparative results show the technique robustness with respect to fault type and traditional fault-location problems, such as fault distance, resistance, inception angle, and load variation. The formulation was implemented as embedded software and is currently used at CEEE-D's distribution operation center. [ABSTRACT FROM AUTHOR]

Over the past decade, electric power systems have been restructured based on different models to introduce competition among market participants. Transmission open access for suppliers and customers is one of the most prevailing unbundling services. Usually, a connection tariff is established based on different market factors, including the actual usage of the transmission network. In Brazil, most vertically integrated companies owned by the federal and state governments were unbundled, and new transmission companies are being created. These companies make their assets available to the independent system operator, designated as Operador Nacional do Sistema Elétrico (ONS). One of the main objectives of ONS is to manage transmission services, over a certain voltage level, to ensure nondiscriminatory access to the grid. All transmission users, including regional distribution companies, pay wheeling transmission charges at each delivery or connection point with the major Brazilian network administrated by ONS. This paper presents a methodology for determining the optimal amount of transmission system usage (ATSU) that must be contracted by a regional distribution company, at each connection point. In the proposed approach, the maximum flow at each connection is represented as a random variable in order to obtain the distribution probability of the transmission charges as a function of the ATSU parameter. Besides providing the optimal amounts to be contracted, the proposed probabilistic methodology allows quantifying the risks of violation of each contract and estimating possible penalties. All methodology development steps are described and illustrated through numerical examples. An application to a typical Brazilian regional distribution company is also discussed. [ABSTRACT FROM AUTHOR]

In this paper, a methodology was developed to analyze the results of energy efficiency programs used in the electricity distribution sector in Brazil. Analyzing the gains obtained through the investments made, and classifying which actions resulted in the best performance, contributed to decision making on the best allocation of investments to obtain the greatest energy savings. The Brazilian Energy Efficiency program was analyzed with a developed non-parametric model, using the data envelopment analysis method, and the categories of projects with better performance were determined. A database of the results from 1704 projects, from 2008 to 2016 in the Energy Efficiency program in Brazil's electricity distribution sector, was used. The results obtained show that the best performance was achieved by projects in the industrial and cogeneration categories; however, in Brazil these constitute only 4.24% of the projects presented and 5.28% of the total investments in the last eight years, indicating a need to review the regulatory strategies for energy efficiency in this country. [ABSTRACT FROM AUTHOR]

Summary: Fraud in electrical energy consumption represents a critical economic burden for utility companies around the world. Despite systematic efforts to mitigate electricity theft, this practice persists mostly in developing countries where companies rely on traditional detection methods. In Brazil it is estimated that around 7% of the total electrical energy available for consumption in 2016 was lost due to frauds. Here we describe an efficient and scalable system to predict fraudulent behavior and guide in loco inspections. We compared the performances of several machine learning algorithms using consumption and inspection data provided by CPFL Energia. We show that proper feature engineering and boosted classification trees trained with XGBoost are able to extract patterns related to fraud occurrence and to achieve predictive power of practical consequences. Moreover, we demonstrate how Shapley additive explanation (SHAP) values can be employed to build user friendly explanations. Together, the proposed model and its explainers contribute not only to reveal potentially fraudulent behavior but also to understand root causes, what can be used to devise robust mitigation strategies. [ABSTRACT FROM AUTHOR]

This paper evaluates the economic (electric power rates and utilities revenues), environmental (GHG emissions), social (job creation) and political (tax collection) impacts of a wider diffusion of photovoltaic distributed generation (PVDG) and energy efficiency (EE) measures on the markets of electric power distribution utilities in Brazil. The impacts are calculated for three substantially different power distribution utilities, which are representative of the types of utilities found in the country. Key indicators were selected to reflect the main interests of the following stakeholders: power distribution utilities, the government (Federal, State and Municipal) and low-voltage consumers. The results show that the most important issues that should be addressed concerning a large diffusion of EE measures are tax collection and tariff rises. The simulations show that tariff rises can be hampered by EE actions targeted to specific locations and specific actions. The most important impact of PVDG diffusion is on tariff rises, considering the current regulatory framework in the country. On the other hand, the net jobs creations of EE measures and, particularly, PVDG are significant and the cost of job creation in relation to fiscal waiver by investment on PVDG is cost-effective. The GHG emissions avoided by the higher levels of PVDG and EE in 2040, simulated in this study, showed to be significant for both EE measures and PVDG. • Description of Key indicators selected to reflect the main interests of utilities, the government and consumers. • Quantify impacts on indicators. • Analysis and discussion of impacts on indicators. [ABSTRACT FROM AUTHOR]

The purpose of this study is to evaluate the efficiency indices for 60 Brazilian electricity distribution utilities. These scores are obtained by DEA (Data Envelopment Analysis) and Bayesian Stochastic Frontier Analysis models, two techniques that can reduce the information asymmetry and improve the regulator's skill to compare the performance of the utilities, a fundamental aspect in incentive regulation schemes. In addition, this paper also addresses the problem of identifying outliers and influential observations in deterministic nonparametric DEA models. [ABSTRACT FROM AUTHOR]

Definitions of methodologies to regulate the quality of electricity supply services are a topic under active discussion in Brazil and worldwide. There are various ways to define limits and quality service goals. In Brazil, the regulation of limit indicators for consumer unit sets is carried out by the National Electric Energy Agency. Its latest revision took place in 2014, under the framework of Public Announcement No. 29/2014. The primary contribution of this research is the proposition of an artificial intelligence-assisted methodology, specifically utilizing machine-learning techniques capable of organizing and selecting the most relevant attributes for representing similar consumer sets. Tests were conducted with real data from the 2020 system. The results demonstrated that this methodology can select attributes from different categories, achieving data representativeness and clustering scores superior to those attained with attributes selected by the current ANEEL methodology. Furthermore, the proposed methodology exhibits greater replicability compared to the current approach. These outcomes contribute to the modernization of quality regulation in the electricity distribution sector, benefiting all stakeholders in the industry. [ABSTRACT FROM AUTHOR]

The evaluation of the quality of electric power distribution services in Brazil is regulated and monitored by the National Electric Energy Agency ANEEL, which uses metrics related to the duration frequency of power interruptions that occur in the power utilities' networks. The methodology applied by the agency to establish financial compensation due to violations of the quality standards does not take into consideration the consumers' production industry when establishing compensation for the transgression of service quality indicators. This study will analyze a case study of a group of industrial consumers linked to agribusiness in the southern region of Brazil, which have strongly seasonal use of distribution networks and are scattered in large, dispersed areas. Based on the evaluation of the impact of service quality indicators on financial compensation, a regulatory mechanism is proposed in the form of an interruptible tariff duly quantified in the form of a non-linear programming problem to find a discount range for uninterruptible tariffs. The results obtained with the real data for the group of irrigating consumers demonstrate the feasibility regarding the application of the proposed approach, whether due to the discounts offered or even the repercussions of the calculated financial amounts. [ABSTRACT FROM AUTHOR]

The evolution of existing electricity grids to smart grids is aimed at accommodating increasing shares of renewable generation thus contributing for the de-carbonization of economy, offering more diversified services to consumers, enhancing different types of markets (energy, capacity, ancillary services) and improving the system's overall efficiency. As the economic characteristics of the electricity sector tend to discourage investments in smart grids, many countries have adopted incentive policies to foster the deployment of new technologies, which vary according to the particular characteristics of each country. Therefore, the design of specific public policies for Brazil must consider not only the motivations involved, but also the existing challenges for the implementation of smart grids and the socio-economic context. Moreover, the relevance of the proposed policies can be seen from different perspectives. This justifies the need to elicit information from multiple stakeholders for decision support purposes. This paper presents and assesses a set of policies identified by different stakeholders as having a potential to foster the development of smart grids in Brazil. The methodology to shape this set of policies consisted of a thorough literature review of international experiences, combined with meetings with experts in several domains. Then, these policies were assessed by applying a Delphi questionnaire aiming at measuring their effectiveness in fulfilling the objectives associated with investments in smart grids. A first conclusion is that all policies were assessed as having a positive impact taking into account each of the objectives, differing only in the priority to be assigned to each one. The policies that were considered more relevant were: "Incentive Policies for Promoting Demand-Side Management, Distributed Generation and Storage", "Regulatory Changes to Foster Innovation in the Energy Sector" and "Regulation of New Business Models". Among the policies with the worst scores, "Mandatory Rollout of Smart Meters" and "Establishing Quality Standards for the Telecommunications Industry" were ranked as the two lower-ranked policies, i.e., they were assigned lower priority under all objectives. [ABSTRACT FROM AUTHOR]

This paper analyzes the policy landscape of a new configuration for the electricity sector, distributed electricity generation, DG, which was introduced in 2012 and regulated in Brazil by the National Electricity Regulation Agency (ANEEL) through a net-metering regulation. The present analysis focuses on the landscape surrounding the policy problem definition and the subsequent policy goals which were established by the national regulator as primarily related to removing barriers to grid access. The policy context surrounding DG in Brazil is analyzed within the broader scope of electricity planning goals, which is a responsibility of the Ministry of Mines and Energy and still shows strong preference to the centralized regime. The design of the net-metering mechanism and the impact of ANEEL's resolution in terms of the number and spatial distribution of the projects across states are also explored. Lastly, an econometric approach is taken by creating a linear regression model to decipher the determinants of successful policy deployment between states. The analysis shows that the electricity rates have an important impact, while the application of a state tax ICMS has negative effects on project uptake. The strength of solar resources was not a significant variable. [ABSTRACT FROM AUTHOR]

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Purpose: To explore financial alternatives to implement PV power generation projects based on the provisions of Normative Resolution n. 482/2012 of the Brazilian Electricity Regulatory Agency (Aneel). This regulation sets forth the general conditions to the access of microand minigeneration granted to the electric energy distribution systems through the energy product offset method. Originality/gap/relevance/implications: This paper discusses the need for regulatory changes, greater government participation in the granting of financial and tax incentives so that PV solar power technology in distributed generation can be financially viable for residential consumers. Key methodological aspects: Investment analysis in PV systems used the Net Present Value (NPV) valuation method. The research assessed two scenarios for Grid-Connected PV Systems (GCPVSs), with different solar power usage levels for a residential consumer. Summary of key results: The results point to a low financial viability in the implementation of distributed microgeneration projects, suggesting the need to remove the tax burden and reduce financing costs. Key considerations/conclusions: The study shows the need of flexibilization of the Brazilian regulatory model, with changes that enable the expansion of renewable energy offers, with positive economic outcomes for tariff affordability. Tariff benefits from distributed microgeneration can positively reflect on captive customers, provided that investment risks are reduced. [ABSTRACT FROM AUTHOR]

One key aspect of electricity quality is the continuity of supply, assessed based on duration and interruption frequency indicators. In Brazil, these indicators are used to assess utility performance, including tariff reviews. This paper proposes adopting a stochastic frontier analysis to benchmark the continuity indicators. Based on Bayesian inference, the model can consider the temporal dynamics of utility performance in terms of gains from economies of scale due to market expansion. The results show that performance targets defined by the proposed methodology are compatible with those defined by the regulatory body. • Adoption of a Stochastic Frontier Analysis in benchmarking the continuity indicators of electric utilities. • Estimated on the basis of the Bayesian inference, is also capable of considering the temporal dynamics of the performance of electric utilities. • The dynamic aspect of efficiency is also of major importance for tariff review. • The results showed that the performance targets defined by the proposed methodology are compatible with those defined by the regulatory body. [ABSTRACT FROM AUTHOR]

Non-technical losses (NTLs) are one of the main problems that electricity distribution utilities face in developing regions such as Latin America, the Caribbean, sub-Saharan Africa, and South Asia. Particularly in Brazil, based on the socioeconomic and market variables concerning all the distribution utilities, the National Electric Energy Agency (ANEEL) has formulated several specifications of econometric models for panel data with random effects, all aimed at determining an index that reflects the difficulty of combating NTLs according to the intrinsic characteristics of each distribution area. Nevertheless, given the exhaustive search for combinations of explanatory variables and the complexity inherent to defining regulatory NTL targets, this process still requires the evaluation of many models through hypothesis and goodness-of-fit tests. In this regard, this article proposes an automatic model-selection technique for panel data regressions to better assist the Agency in establishing NTL regulatory targets for the distribution of utilities in this country. The proposed technique was applied to panel data containing annual observations from 62 Brazilian electricity distribution utilities from 2007 to 2017, thus generating 1,097,789 models associated with the regression types in the panel data. The main results are three selected models that showed more adherence to the actual capacity of Brazilian distribution utilities to reduce their NTLs. [ABSTRACT FROM AUTHOR]

This work addresses the maintenance workforce planning in electric power distribution utilities. A two-phase optimization procedure is proposed to consider the strategic (long-term) and tactical/operational (medium/short-term) planning. In the first phase (strategic planning), a bi-objective optimization problem is solved to locate depots and to size the number of repair teams at each depot. One of the objectives includes operating and capital expenses, while the other one is based on continuity indicators related to the interruption in the electrical energy supply. In order to solve this problem, we use a memetic algorithm which combines a metaheuristic with a mixed-integer linear programming (MILP) model. On the other hand, the second phase (tactical/operational planning) consists of solving other MILP model to determine, for each depot, the required number of electricians (now based on more detailed forecasts) and define their work schedules, minimizing the wage costs and hiring/firing expenses. The results show that a larger number of solutions can be found through the memetic algorithm compared to the purely metaheuristic approach. The proposed optimization algorithm is part of an innovative web-based system developed during a research and development project and it is now available for eleven Brazilian power distribution utilities. • The paper presents an innovative two-phase optimization algorithm for workforce planning not only in power distribution utilities but also in any other utilities that have field teams serving vast geographic regions (i.e., large transmission systems operators). • A two-phase optimization procedure is proposed to consider the strategic (longterm) and tactical/operational (medium/short-term) planning. In the first phase (strategic planning), a bi-objective optimization problem is solved to locate depots and to size the number of repair teams at each depot. This module uses a memetic algorithm which combines a metaheuristic with a mixed-integer linear programming (MILP) model. • The second phase (tactical/operational planning) consists of solving other MILP model to determine, for each depot, the required number of electricians (now based on more detailed forecasts) and define their work schedules, minimizing the wage costs and hiring/firing expenses. • The proposed algorithm is evaluated by means of a real case study related to the workforce planning problem for an electric distribution utility in Brazil (Energisa Sergipe). [ABSTRACT FROM AUTHOR]

This paper proposes a new hybrid approach for short-term energy price prediction. This approach combines auto-regressive integrated moving average (ARIMA) and neural network (NN) models in a cascaded structure and uses explanatory variables. A two step procedure is applied. In the first step, the selected explanatory variables are predicted. In the second one, the energy prices are forecasted by using the explanatory variables prediction. Further, the proposed model considers a multi-step ahead price prediction (12 weeks-ahead) and is applied to Brazilian market, which adopts a cost-based centralized dispatch with unique characteristics of price behavior. The results show good ability to predict spikes and satisfactory accuracy according to error measures and tail loss test when compared with traditional techniques. Thus, the model can be an attractive tool to mitigate risks in purchasing power. [ABSTRACT FROM AUTHOR]

This paper shows efficiency indices for 60 Brazilian electricity distribution utilities. The efficiency scores are gauged by three DEA models. For both models, these quantities are evaluated under different contexts. One treats with respect to the regulator perspective. The others examine an alternative approach based on cluster analysis and restrictions on factor weights. It is worth pointing out that these developments can reduce the information asymmetry and improve the regulator's skill to compare the performance of the utilities, a fundamental in incentive regulation schemes. [ABSTRACT FROM AUTHOR]

Abstract: The typical electrical distribution system shows a passive characteristic in relation to power flows (i.e. unidirectional power flows from substation to loads along the feeder). However, with the inclusion of solar photovoltaic (PV) generators along the feeder, this behavior is changed, and characteristics related to power quality, such as voltage level and total harmonic distortion (THD), may be affected. This paper presents the analysis of power quality in a feeder of the urban grid in the city of the Florianopolis, Brazil, with the integration of grid-connected PV systems as distributed generation. The analysis of power quality is based on real measurements of THD on an existing 12kWp PV pilot plant installed in the urban environment, and power flow simulations of a hypothetical PV system of 4.2MWp distributed in the same area, using the ANAREDE software. The power flow simulations allowed assessing the voltage level, the direction of power flow and loading of the distribution lines. The introduction of limited amounts of PV generation as distributed generation in the urban environment was found to be beneficial in several aspects: better voltage profile; power loss reduction and improvement in total harmonic distortion of the voltage (THDv). Furthermore, photovoltaics as a distributed generation source can also postpone feeder capacity upgrading investments. [Copyright &y& Elsevier]

Abstract: In Brazil, more than 14million people have benefited from the rural electrification program Luz Para Todos (LPT — Light for all), mainly through grid-extension. A new off-grid model is now required if remote areas in the Amazon region are to fully benefit from the program. In this paper, we explore the institutional and financial schemes that support LPT and their suitability for delivering off-grid solutions in the Amazon region. Our conclusions draw attention to the need for more local and site specific solutions, and new regulatory frameworks to allow the participation of new actors. We argue that the uniqueness of the Amazon region justifies renewable technologies focused on local needs and potential, adaptation of the LPT institutional framework and rethinking of funding channels. An off-grid approach will enhance the inclusion of remote areas in universal access goals while adjustments will help guarantee the sustainability of the electrification program. [Copyright &y& Elsevier]

Abstract: Underground distribution systems are normally exposed to permanent faults, due to specific construction characteristics. In these systems, visual inspection cannot be performed. In order to enhance service restoration, accurate fault location techniques must be applied. This paper describes an extended impedance-based fault location algorithm for underground distribution systems. The formulation is developed on phase frame and calculates the apparent impedance using only local voltage and current data. The technique also provides an iterative algorithm to compensate the typical capacitive component current of underground cables. Test results are obtained from numerical simulations using a real underground distribution feeder data from the Electrical Energy Distribution State Company of Rio Grande do Sul (CEEE-D), southern Brazil. Comparative results show the techniques accuracy and robustness in respect to fault type, distance and resistance. [Copyright &y& Elsevier]

Despite presenting a considerable potential for photovoltaic (PV) solar energy conversion, many times larger than the country’s current and future energy needs, PV generation still plays a negligible role in the Brazilian energy mix, lacking a proper market, legislation and incentives to make use of this benign energy source. The still high capital costs involved in PV project implementation, associated with the perception that grid-connected PV is only suitable for developed countries, are the typical arguments used to justify the lack ofinterest in PV as an energy alternative for urban grid support in metropolitan areas. It is possible to demonstrate that in the near future, the price of energy generated by a residential consumer with a roof-mounted, grid-connected PV system can be lower than the corresponding residential tariff paid by this electricity consumer to the local distribution utility. It is then argued that, from this moment on, this consumer has the right to decide for the least-cost alternative, and that the Brazilian legislation has the duty of enabling this option. In this article we present the situation in Brazil regarding the application of grid-connected PV, and we demonstrate the potential benefits of this energy generation technology. We also summarize the current legislation and commercialization aspects related to grid-connected PV installations. Furthermore, the paper presents bottlenecks to a more widespread use of PV generation in the Brazilian energy mix, and identifies the need for the creation of an incentive mechanism that can assist in bridging the gap to grid parity, which is expected to take place in Brazil in the coming decade. [ABSTRACT FROM AUTHOR]

• Analysis of the impact of the Covid-19 pandemic on the Brazilian electricity market. • Application of the Optimization Tariff Model in the context of the pandemic. • Analysis of the efficacy of the public policy designed by the Brazilian government. • Presentation of a new public policy that present advantages over the current one. This paper evaluates the impact of the COVID-19 pandemic on the Brazilian distribution electricity market by applying a socioeconomic regulatory model called Optimized Tariff Model. The model quantifies the impact of the pandemic on the consumer's quality of life and also on the economic performance of power distribution companies. Results indicate that both consumers and power distribution companies have been significantly affected in Brazil, especially companies that did not have access to the public policy proposed by the government, as they exhibited economic losses of more than 1 (GR$) in total. After analyzing the impact of the new coronavirus and the actions of the government in this context, an alternative mitigation measure (public policy) is proposed based on the Optimized Tariff Model and its feasibility examined. The alternative mitigation measure is also compared to the public policy proposed by the government and proved to be advantageous in some respects such as making bank loans unnecessary. [ABSTRACT FROM AUTHOR]

In 1993, the Brazilian electricity sector initiated a restructuring process by unbundling the generation, transmission, and distribution components of the existing companies. This ultimately led to the privatization of most distribution assets and some of the generation assets. However, little attention was paid in the process to the expansion of services to low-income and rural areas. This paper characterizes the main policy, institutional and regulatory barriers that have negative impacts on electricity supply to low-income consumers in rural and urban areas in the country. It also analyzes the effect of the power sector reform and discusses existing institutional arrangements that may affect the policy goal of universal access to electricity. Finally, it provides recommendations for feasible developments in policy, regulatory and institutional arrangements that would facilitate the expansion of electricity supply to low-income consumers and rural areas. [Copyright &y& Elsevier]

While most of the research work in the field of electrical engineering was aroused by the scientific challenges to be overcome, it is fair to recognize that the practical importance of engineering hinges on its economic impact on the market, the whole society and the environment. Thus, nowadays economic modeling, analysis and optimization of the electricity market is of the utmost significance. This work presents an aggregated economic analysis of the Brazilian electricity distribution companies using an economic model of a regulated market. The fundamental agents (consumer, power utility, government, society) are represented in the TAROT—Optimized Tariff Model, which is applied to the majority of the distribution companies in Brazil, based on public real data available from ANEEL—the Brazilian electrical energy regulatory agency. This reveals the economic flows in the regulated market of each company and also presents their financial status in terms of over-investments or under-investments compared to optimal investments and positive, negative or zero economic value added of each company. Moreover, the model analysis shows the socioeconomic welfare added to society in face of different optimization objectives. [ABSTRACT FROM AUTHOR]

This study investigates the role of aligning tariff adjustments and quality incentives in a Price cap regulatory regime. According to theory costs and quality are positively related. If additional resources are needed to improve service quality, a high cost high quality utility could be at a disadvantage when tariffs are adjusted by an X-factor that does not include quality. The regulator of the electricity distribution sector of Brazil has set up a public ranking of utilities according to quality compliance at the same time that a quality component is added to the X-factor, in 2013. We develop a stochastic cost frontier integrating all components of the X-factor to rank the utilities based on this integrated efficiency. Comparing this rank with the regulator's public rank we argue that the resulting differences highlight the importance of using the same factors to rank and adjust tariffs in the sector. Otherwise, incentives would be misplaced with respect to factors used in cost adjustments. In addition, our findings reveal that the utilities' cost behavior with respect to quality depends on the volume of energy delivered. We believe these results could be considered by the regulator when setting incentives and considering factors to adjust tariffs. [ABSTRACT FROM AUTHOR]

We report the development of a measurement system capable of monitoring and characterizing the main features of the leakage current flowing on a polluted insulator string of a high-voltage transmission line. The system comprises a fiber-optic sensor, directly connected to one insulator of the string, that emits a sample of the leakage current waveform to a processing module via an optical link. A capacitive sensor connected to the processing module allows recording the relative humidity of the outer environment. At the present stage, six measurement units have been deployed on CHESF's electrical transmission system in the Northeast of Brazil, and studies are underway to further correlate the degree of environmental pollution with humidity and leakage current activities on high-voltage insulator strings. [ABSTRACT FROM AUTHOR]

This work presents a methodology that combines the use of artificial neural networks and fuzzy logic for alarm processing and identification of faulted components in electrical power systems. Fuzzy relations are established and form a database employed to train artificial neural networks. The artificial neural networks inputs are alarm patterns, while each output neuron is responsible for estimating the degree of membership of a specific system component into the class of faulted components. The proposed method allows good interpretation of the results, even in the presence of difficult corrupted alarm patterns. Tests are performed with a test system and with part of a real Brazilian system. [ABSTRACT FROM AUTHOR]

Presents the results of a study carried out to determine the residential, commercial and industrial consumers daily load curves based on field measurements performed by the Utilities of Electric Energy of Sao Paulo State, Brazil. Representative load curves; Aggregation of curves.

Proposes to introduce an additional procedure for dealing with the geographic distribution of water power resources, an approach tentatively named the Participation Ratio. Procedure that may be used for analogous distributional studies; Area and estimated water power resources of Brazil by hydrographic basins.