855 resultados para Distributed Array
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Problems as voltage increase at the end of a feeder, demand supply unbalance in a fault condition, power quality decline, increase of power losses, and reduction of reliability levels may occur if Distributed Generators (DGs) are not properly allocated. For this reason, researchers have been employed several solution techniques to solve the problem of optimal allocation of DGs. This work is focused on the ancillary service of reactive power support provided by DGs. The main objective is to price this service by determining the costs in which a DG incurs when it loses sales opportunity of active power, i.e, by determining the Loss of Opportunity Costs (LOC). The LOC will be determined for different allocation alternatives of DGs as a result of a multi-objective optimization process, aiming the minimization of losses in the lines of the system and costs of active power generation from DGs, and the maximization of the static voltage stability margin of the system. The effectiveness of the proposed methodology in improving the goals outlined was demonstrated using the IEEE 34 bus distribution test feeder with two DGs cosidered to be allocated. © 2011 IEEE.
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Distributed Generation, microgrid technologies, two-way communication systems, and demand response programs are issues that are being studied in recent years within the concept of smart grids. At some level of enough penetration, the Distributed Generators (DGs) can provide benefits for sub-transmission and transmission systems through the so-called ancillary services. This work is focused on the ancillary service of reactive power support provided by DGs, specifically Wind Turbine Generators (WTGs), with high level of impact on transmission systems. The main objective of this work is to propose an optimization methodology to price this service by determining the costs in which a DG incurs when it loses sales opportunity of active power, i.e, by determining the Loss of Opportunity Costs (LOC). LOC occur when more reactive power is required than available, and the active power generation has to be reduced in order to increase the reactive power capacity. In the optimization process, three objectives are considered: active power generation costs of DGs, voltage stability margin of the system, and losses in the lines of the network. Uncertainties of WTGs are reduced solving multi-objective optimal power flows in multiple probabilistic scenarios constructed by Monte Carlo simulations, and modeling the time series associated with the active power generation of each WTG via Fuzzy Logic and Markov Chains. The proposed methodology was tested using the IEEE 14 bus test system with two WTGs installed. © 2011 IEEE.
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This paper proposes a methodology to consider the effects of the integration of DG on planning. Since DG has potential to defer investments in networks, the impact of DG on grid capacity is evaluated. A multi-objective optimization tool based on the meta-heuristic MEPSO is used, supporting an alternative approach to exploiting the Pareto front features. Tests were performed in distinct conditions with two well-known distribution networks: IEEE-34 and IEEE-123. The results combined minimization and maximization in order to produce different Pareto fronts and determine the extent of the impact caused by DG. The analysis provides useful information, such as the identification of futures that should be considered in planning. A future means a set of realizations of all uncertainties. MEPSO also presented a satisfactory performance in obtaining the Pareto fronts. © 2011 IEEE.
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This paper presents a mixed-integer linear programming approach to solving the optimal fixed/switched capacitors allocation (OCA) problem in radial distribution systems with distributed generation. The use of a mixed-integer linear formulation guarantees convergence to optimality using existing optimization software. The results of one test system and one real distribution system are presented in order to show the accuracy as well as the efficiency of the proposed solution technique. © 2011 IEEE.
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Simulation of large and complex systems, such as computing grids, is a difficult task. Current simulators, despite providing accurate results, are significantly hard to use. They usually demand a strong knowledge of programming, what is not a standard pattern in today's users of grids and high performance computing. The need for computer expertise prevents these users from simulating how the environment will respond to their applications, what may imply in large loss of efficiency, wasting precious computational resources. In this paper we introduce iSPD, iconic Simulator of Parallel and Distributed Systems, which is a simulator where grid models are produced through an iconic interface. We describe the simulator and its intermediate model languages. Results presented here provide an insight in its easy-of-use and accuracy.
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The problem of reconfiguration of distribution systems considering the presence of distributed generation is modeled as a mixed-integer linear programming (MILP) problem in this paper. The demands of the electric distribution system are modeled through linear approximations in terms of real and imaginary parts of the voltage, taking into account typical operating conditions of the electric distribution system. The use of an MILP formulation has the following benefits: (a) a robust mathematical model that is equivalent to the mixed-integer non-linear programming model; (b) an efficient computational behavior with exiting MILP solvers; and (c) guarantees convergence to optimality using classical optimization techniques. Results from one test system and two real systems show the excellent performance of the proposed methodology compared with conventional methods. © 2012 Published by Elsevier B.V. All rights reserved.
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Traditionally, ancillary services are supplied by large conventional generators. However, with the huge penetration of distributed generators (DGs) as a result of the growing interest in satisfying energy requirements, and considering the benefits that they can bring along to the electrical system and to the environment, it appears reasonable to assume that ancillary services could also be provided by DGs in an economical and efficient way. In this paper, a settlement procedure for a reactive power market for DGs in distribution systems is proposed. Attention is directed to wind turbines connected to the network through synchronous generators with permanent magnets and doubly-fed induction generators. The generation uncertainty of this kind of DG is reduced by running a multi-objective optimization algorithm in multiple probabilistic scenarios through the Monte Carlo method and by representing the active power generated by the DGs through Markov models. The objectives to be minimized are the payments of the distribution system operator to the DGs for reactive power, the curtailment of transactions committed in an active power market previously settled, the losses in the lines of the network, and a voltage profile index. The proposed methodology was tested using a modified IEEE 37-bus distribution test system. © 1969-2012 IEEE.
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This paper presents a mixed-integer linear programming approach to solving the problem of optimal type, size and allocation of distributed generators (DGs) in radial distribution systems. In the proposed formulation, (a) the steady-state operation of the radial distribution system, considering different load levels, is modeled through linear expressions; (b) different types of DGs are represented by their capability curves; (c) the short-circuit current capacity of the circuits is modeled through linear expressions; and (d) different topologies of the radial distribution system are considered. The objective function minimizes the annualized investment and operation costs. The use of a mixed-integer linear formulation guarantees convergence to optimality using existing optimization software. The results of one test system are presented in order to show the accuracy as well as the efficiency of the proposed solution technique.© 2012 Elsevier B.V. All rights reserved.
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In this study, a novel approach for the optimal location and contract pricing of distributed generation (DG) is presented. Such an approach is designed for a market environment in which the distribution company (DisCo) can buy energy either from the wholesale energy market or from the DG units within its network. The location and contract pricing of DG is determined by the interaction between the DisCo and the owner of the distributed generators. The DisCo intends to minimise the payments incurred in meeting the expected demand, whereas the owner of the DG intends to maximise the profits obtained from the energy sold to the DisCo. This two-agent relationship is modelled in a bilevel scheme. The upper-level optimisation is for determining the allocation and contract prices of the DG units, whereas the lower-level optimisation is for modelling the reaction of the DisCo. The bilevel programming problem is turned into an equivalent single-level mixed-integer linear optimisation problem using duality properties, which is then solved using commercially available software. Results show the robustness and efficiency of the proposed model compared with other existing models. As regards to contract pricing, the proposed approach allowed to find better solutions than those reported in previous works. © The Institution of Engineering and Technology 2013.
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This article shows a transmission line model developed directly in the phase domain. The proposed model is based on the relationships between the phase currents and voltages at both the sending and receiving ends of a single-phase line. These relationships, established using an ABCD matrix, were extended to multi-phase lines. The proposed model was validated by using it to represent a transmission line during short-and open-circuit tests. The results obtained with the proposed model were compared with results obtained with a classical model based on modal decomposition. These comparisons show that proposed model was correctly developed. © 2013 Taylor and Francis Group, LLC.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The objective of the present article is to assess and compare the performance of electricity generation systems integrated with downdraft biomass gasifiers for distributed power generation. A model for estimating the electric power generation of internal combustion engines and gas turbines powered by syngas was developed. First, the model determines the syngas composition and the lower heating value; and second, these data are used to evaluate power generation in Otto, Diesel, and Brayton cycles. Four synthesis gas compositions were tested for gasification with: air; pure oxygen; 60% oxygen with 40% steam; and 60% air with 40% steam. The results show a maximum power ratio of 0.567 kWh/Nm(3) for the gas turbine system, 0.647 kWh/Nm(3) for the compression ignition engine, and 0.775 kWh/Nm(3) for the spark-ignition engine while running on synthesis gas which was produced using pure oxygen as gasification agent. When these three systems run on synthesis gas produced using atmospheric air as gasification agent, the maximum power ratios were 0.274 kWh/Nm(3) for the gas turbine system, 0.302 kWh/Nm(3) for CIE, and 0.282 kWh/Nm(3) for SIE. The relationship between power output and synthesis gas flow variations is presented as is the dependence of efficiency on compression ratios. Since the maximum attainable power ratio of CIE is higher than that of SIE for gasification with air, more research should be performed on utilization of synthesis gas in CIE. (C) 2014 Elsevier Ltd. All rights reserved.
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Usually, ancillary services are provided by large conventional generators; however, with the growing interest in distributed generation to satisfy energy and environmental requirements, it seems reasonable to assume that these services could also be provided by distributed generators in an economical and efficient way. In this paper, a proposal for enhancement of the capacity of active power reserve for frequency control using distributed generators is presented. The goal is to minimize the payments done by the transmission system operator to conventional and distributed generators for this ancillary service and for the energy needed to satisfy loads and system losses, subject to a set of constraints. In order to perform analysis, the proposal was implemented using data of the IEEE 30-bus transmission test system. Comparisons were performed considering conventional generators without and with distributed generators installed in the system.