Electric Energy Distribution Company Research Articles

The Role of Preventive Major Maintenance in the Costs of Electric Energy Distribution Companies

Objectives: The unwanted and unplanned outages due to faults occurred in electrical energy distribution systems are one of the main concerns of distribution companies. This paper examines this concerning. Methods/Statistical Analysis: This paper examines about ninety outages in related to the medium pressure power lines in second region of Bushehr over twomonth period. Findings: It has identified faults caused by power outages, and the time of outage for each fault is extracted in all regions of the primary data obtained from the power events. Then, by determining the cost function with the purely economic factors, are obtained the costs of each fault individually. In the following, for each fault are provided a series of preventive overhauls or preventive recommendations. Until increasing the system’s trustworthiness, the operating costs of unwanted faults are completely eliminated or minimized. Application/Improvements: The application of this paper is that examines the roles of preventive major maintenance in the costs of electric energy distribution companies. Keywords: Cost Function, Electric Energy Distribution Companies, Energy Not Served (ENS), Preventive Maintenance, Unplanned Outage

Evaluation of technical efficiency of Brazilian distribution companies of electrical energy through Data Envelopment Analysis (DEA)

The Brazilian Provisional Act No. 579/2012 established a significant change in the rules applied to the electric energy sector, in particular in relation to the renewal of concessions of power generation, transmission and distribution of power from those who have contract termination between 2013 and 2017. Besides this measure, the electric energy distributors are going through the third Cycle of Periodic Tariff Review, a fact that also foresees the reduction of charges imposed on the electricity, thereby requiring a greater efficiency of its management. Thus, this research analyses the technical efficiency on the electric energy distribution companies. This is a study with a quantitative approach, based on data from 2012. With the application of Data Envelopment Analysis, we determined the relative technical efficiency of 18 companies of the population. The relative technical efficiency reached a score of 100% in seven of the 18 companies analyzed. Efficient firms are spread across Brazil, with a greater concentration in the Southeast. The Municipal Human Development Index, the size of the concession area and the extent of distribution network, as well as the population density are not explanatory to the attainment of efficiency factors.

Reducing the Electrical Consumption in the Humidity Control Process for Electric Cells using an Intelligent Fuzzy Logic Controller

The electrical energy distribution uses a huge network to cover the urbanized areas. The network distribution incorporates an important number of electrical cells that ensure the energy transformation. These cells play a fundamental role to ensure a permanent feeding. Thus, the performance of these cells must be optimized. The main problem that affects these cells is the inside humidity that should be controlled permanently to prevent serious damage and power failure. The presented work proposes the use of a powerful intelligent Fuzzy Logic Controller that can online adapt their internal parameters according to the actually state of the controlled plant and auto-learn from the behavior of the plant how the current humidity level can be decreased. The used controller can stabilize the humidity inside the cells within the recommended range by controlling a set of heating resistances installed inside these cells and in the same time ensuring valuable advantages for the electrical energy distribution company. Unlike the rest of the controllers that are used to stabilize moisture. The intelligent controller used in these papers ensures a very precise control with very low power consumption which trains a very significant energy savings in each electrical cell. Knowing that the distribution network incorporates a very large number of electrical cells, the final savings balance would be a very high amount of energy that can be presented economically with significant savings on the electricity bills.

On the impact of topological properties of smart grids in power losses optimization problems

Power losses reduction is one of the main targets for any electrical energy distribution company. In this paper, we face the problem of joint optimization of both topology and network parameters in a real smart grid. We consider a portion of the Italian electric distribution network managed by the ACEA Distribuzione S.p.A. located in Rome. We perform both the power factor correction (PFC) for tuning the generators and the distributed feeder reconfiguration (DFR) to set the state of the breakers. This joint optimization problem is faced considering a suitable objective function and by adopting genetic algorithms as global optimization strategy. We analyze admissible network configurations, showing that some of these violate constraints on current and voltage at branches and nodes. Such violations depend only on pure topological properties of the configurations. We perform tests by feeding the simulation environment with real data concerning hourly samples of dissipated and generated active and reactive power values of the ACEA smart grid. Results show that removing the configurations violating the electrical constraints from the solution space leads to interesting improvements in terms of power loss reduction. To conclude, we provide also an electrical interpretation of the phenomenon using graph-based pattern analysis techniques.

Barriers to Strategic Planning Implementation; Case of: Mashhad Electricity Distribution Company

Organizations have learned to evaluate their performance from the viewpoint of their customers to achieve competitive advantage. However, environmental turbulence remains the main challenge for organizations to succeed, requiring more attention to emerging opportunities and threats under strategically thinking and planning. The aim of this study was to explore the barriers in implementing strategic plan at Mashhad Electric Energy Distribution Company (MEEDC). To achieve research goal, a qualitative research method was sought to collect data from a panel of experts consisting of eleven top managers of MEEDC. A semi-structured interview was utilized and performed based on snowball technique. Collected data was deliberately classified and analyzed using NVIVO software. The result ended with eight distinct groups of barriers including cultural, Structural, managerial, environmental, human resource management, and lack of effective performance measures, insufficient resources, and inadequate strategy formulation. Finally, suggestions to ease or eliminate implementation barriers were provided to MEEDC managers and decision makers.

Comparison between time-constrained and time-unconstrained optimization for power losses minimization in Smart Grids using genetic algorithms

The power losses reduction is one of the main targets for any electrical energy distribution company. This paper studies the applicability of a control system based on a Genetic Algorithm (GA) on a portion of the actual Italian electric distribution network located in Rome and surroundings, managed by the ACEA Distribuzione S.p.A. The joint optimization of both power factor correction (PFC) and distributed feeder reconfiguration (DFR) is faced. The PFC is performed tuning the phases of the distributed generators (DGs) and the output voltage of the Thyristor Voltage Regulator (TVR). The DFR is performed by opening and closing the available breakers according to a graph based algorithm that is able to find all the possible radial configurations of the network. The joint PFC and the DFR optimization problem are faced by solving a suitable optimization problem, defining the fitness function that drives the GA. In order to have the opportunity to study a realistic future scenario, the actual network has been modified by introducing a few extra distributed generators. Aiming to validate the applicability of the proposed algorithm to an operative scenario, two different tests have been performed. The first one, referred to as time-unconstrained optimization, represents an ideal scenario where there are no constraints on time available for optimization. The second one, referred to as time-constrained optimization, represents a real scenario where the optimization must be completed within a time slot of one hour. Both tests have been performed by feeding the developed simulation tool with real data concerning dissipated and generated active and reactive power values. The comparison between results obtained in the two tests campaigns furnishes the opportunity to evaluate the effectiveness of the proposed control algorithm in real time, relying on the computational performances of an entry-level workstation. The obtained results encourage the use of derivative free methods in a real-time control scenario, showing that the performances achieved by the time-constrained optimization procedures are very close in terms of objective function values to the ones obtained by the time-unconstrained procedure.

Development of transient fault management methodology

This paper presents the results of development studies to diagnostic and support to locate faults in distribution systems with recognition patterns using neural networks. It presents the developed methodology for input data processing for neural networks, as well as for fault type identification. In this methodology is necessary to get input data and were designed equipment prototypes to measure and transmit data's and voltage transducers. These equipments were installed in two feeders in the concession area of an electrical energy distribution company. The paper conclusion is that all results obtained indicate the suitability of neural networks to support transient fault management.

The Role of Social Capital on Improving the Talent Management at the Southern Khorasan Electric Energy Distribution Company (SKEDC)

The Role of Social Capital on Improving the Talent Management at the Southern Khorasan Electric Energy Distribution Company (SKEDC)

Electrical Energy Losses Determination In Low Voltage – A Case Study

Along the last years, electrical energy distribution companies have already done many investments in order to identify and calculate energy losses along a distribution network. Although these big efforts, most approaches for clearly identifying and solving the related problems still remain rather inefficient. The accurate identification and the precise calculation of electricity losses enables the clear specification of the critical points and segments in the networks and, consequently, the effective prioritization of actions and interventions in order to reduce those electricity losses and problems. Moreover, the work already performed on this issue, the existing approaches focus mainly on empirical and probabilistic data. Hence, there is still a clear gap between real information and the considered one, which tends to be poor and imprecise. Due to this reality and the lack of appropriate software applications, in this paper we propose a web platform for the management of the whole network of electrical energy distribution, from medium voltage (MV) down to low voltage (LV), including billing on the transformation centers (TCs), electricity losses calculation and proposals for solving actions, by means of a fuzzy decision-making model.

Frontier methodology to fix quality goals in electrical energy distribution companies

Frontier methodology to fix quality goals in electrical energy distribution companies

A Data Mining Approach For Medium-term Demand Forecasting

The Brazilian government, in the past, monopolized the generation, transmission and distribution of electric energy. Following world-wide tendencies, nowadays the government assumes the regulation function in a competitive and horizontal market. The variable load, fundamental in the planning of the electrical and energy operation, in the studies of magnifying and reinforcement of the basic network, assumes strategic importance in the commercial area, improving the data storage and knowledge extraction process using computational techniques. In the present work, data mining techniques are used to produce monthly load forecasts in intervals of high, medium and low consumption, according to the needs of electrical energy distribution companies. The results of neural network models, when compared to statistical results, show improved performance, presenting an Average Relative Error about 0.5% lower.