Wyniki 1-3 spośród 3 dla zapytania: authorDesc:"Edmarcio A. BELATI"

First-Order Sensitivity Applied in Power Distribution System DOI:10.12915/pe.2014.07.018

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This paper presents a study of the power distribution system via sensitivity analysis. This study is based on first-order sensitivity analysis applied in the power flow (PF) solution. Unlike the PF algorithm, this technique does not require an iterative process, which results in a faster methodology with high accuracy and greatly reduced computational work. Starting from a known PF solution, considered as the base case, the new operating point is calculated directly after making a perturbation in the loads. The methodology analysis is applied to 34, 70 and 476-bus distribution power systems. Test results demonstrate the efficiency of the approach. Streszczenie. W artykule przedstawiono metodę kontroli dystrybucji mocy za pośrednictwem analizy czułości (analiza czułości pierwszego rzędu). Dzięki tej metodzie uzyskuje się szybsze rezultaty unikając procesu iteracji. Startując ze znanego rozwiązania rozpływu mocy PF nowy punkt pracy jest obliczany po zmianie obciążeń. (Zastosowanie metody analizy czułości pierwszego rzędu w systemach energetycznych) Keywords: Sensitivity analysis; power flow; distribution power systems. Słowa kluczowe: in the case of foreign Authors in this line the Editor inserts Polish translation of keywords. doi:10.12915/pe.2014.07.18 1. Introduction In the scenario of electric power, great changes happened in the last few years. New technologies are emerging allied to the concept of smart grids that will lead to deep changes and advances in the direction of new technologies enabling better system management with efficiency gains. The technologies that are currently under investigation for the smart grids will provide system control in real time enabling better control about variations of the demand and supply energy [1]. The power demand in distribution system varies during the day (load curve) as well as power generated by intermittent energy sources. Allied to these changes the electrical power systems have expe[...]

Optimal Capacity Planning of Renewable Distributed Generation in Active Distribution Networks to Reduce Greenhouse Gas Emissions DOI:10.15199/48.2017.04.33

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This work presents an evaluation of the maximum capacity of renewable distributed generation that can be connected to active distribution networks to minimize the greenhouse gas emissions of the electric network. The study aimed at obtaining a methodology applicable to active distribution networks with characteristics of variable generation and demand in order to reduce greenhouse gas emissions from electric power generation activities. The formulation of the methodology is based on an optimal power flow model incorporating special system controls. Streszczenie. W artykule rozważa się maksymalna pojemność odnwialnych źródeł energii rozproszonej która może być dołączona do aktywnej sieci rozdzielczej dla zminimalizowania emisji gazów cieplarnianych. Metoda polega na modelu optymalnego przepływu mocy uwzględniającym sterowanie systemem. Planowanie optymalnej pojemności odnawialnych źródeł energii w aktywnej sieci rozdzielczej w celu redukcji emisji gazów cieplarnianych Keywords: greenhouse gas emissions; distributed generation; active distribution networks; wind energy. Słowa kluczowe: gazy cieplarniane, energia rozproszpona, źródła odnawialne Introduction In the last decade, the phenomenon called global warming has been associated with the increase of greenhouse gases emitted during the combustion of fossil fuels like oil, coal and gas. The current conventional generation systems that use fossil fuels emit large amounts of greenhouse gases to the environment. Renewable energy sources are those whose origin lies in natural phenomena, processes or materials that can be converted to usable energy to mankind and is naturally regenerated. Thus, are available continually and periodically. Distributed generation (DG) is an electric energy generator connected to the electric distribution network or directly to the load consuming electric power. Distributed generation that uses renewable energy sources to generate electricity are called rene[...]

Distributed Generation Allocation Using the Genetic Algorithm of Chu-Beasley and Sensitivity DOI:10.15199/48.2016.08.53

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This paper presents a methodology for the allocation of distributed generation (DG) units to minimize active power losses in distribution networks. This methodology is based on the genetic algorithm of Chu-Beasley (GACB) and first-order sensitivity (FOS). To evaluate the different proposals of solution, instead of using Load Flow (LF), a FOS technique was used in order to directly estimate the solution of the LF. The proposed methodology was applied to three distribution systems, containing 34, 70 and 126 buses, respectively. Results obtained for the 34 bus system using GACB and FOS technique were compared with that obtained using GACB but solving the LF via Newton-Raphson (NR) method, showing the computational time gain when the FOS technique is used. For the three systems, the best locations for allocation two DG units are shown and the technical impacts in the network, i.e., active power losses and voltage profiles, are verified. Streszczenie. W artykule opisano metodologię lokalizacji rozproszonych źródeł energii przy kryterium minimalizacji strat mocy czynnej. Metoda bazuje na algorytmie genetycznym Chu-Beasley i czułości pierwszego rzędu. Metodę sprawdzono na przykładzie trzech różnych sieci dystrybucyjnych. Analiza lokalizacji rozproszonych generatorów przy wykorzystaniu algorytmu generycznego Chu-Beasley Keywords: Distributed generation; Sensitivity analysis; Genetic algorithm of Chu-Beasley. Słowa kluczowe: generacja rozproszona, algorytm genmetyczny Chu-Beasley. 1. Introduction The efforts towards the expansion of the participation of alternative energy in the electricity generation are growing in the world. Diversifying the energy matrix by implementing new sources of electric generation is the object and desire of many countries. These new forms of power generation may be connected to distribution and transmission networks. The renewable resources [1], e.g., wind, solar, biomass, among others, are classified as environmental[...]

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