901 resultados para Distribution network reconfiguration


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In the first part some information and characterisation about an AC distribution network that feeds traction substations and their possible influences on the DC traction load flow are presented. Those influences are investigated and mathematically modelled. To corroborate the mathematical model, an example is presented and their results are confronted with real measurements.

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Large-scale renewable energy (RE) integration into the distribution network (DN) causes uncertainties due to its intermittent nature and is a challenging task today. In general RE sources are mostly connected near the end user level, i.e., in the low voltage distribution network. RE integration introduces bi-directional power flows across distribution transformer (DT) and hence DN experiences with several potential problems that includes voltage fluctuations, reactive power compensation and poor power factor in the DN. This study identifies the potential effects causes due to large-scale integration of RE into the Berserker Street Feeder, Frenchville Substation under Rockhampton DN. From the model analyses, it has clearly evident that voltage of the Berserker Street Feeder fluctuates with the increased integration of RE and causes uncertainties in the feeder as well as the DN.

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Wind energy is one of the most promising renewable energy sources due to its availability and climate-friendly attributes. Large-scale integration of wind energy sources creates potential technical challenges due to the intermittent nature that needs to be investigated and mitigated as part of developing a sustainable power system for the future. Therefore, this study developed simulation models to investigate the potential challenges, in particular voltage fluctuations, zone substation, and distribution transformer loading, power flow characteristics, and harmonic emissions with the integration of wind energy into both the high voltage (HV) and low voltage (LV) distribution network (DN). From model analysis, it has been clearly indicated that influences of these problems increase with the increased integration of wind energy into both the high voltage and low voltage distribution network, however, the level of adverse impacts is higher in the LV DN compared to the HV DN.

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The advancement in solar photovoltaic (PV) technology, the cost and efficiency of PVs have encouraged users worldwide to adopt more and more PVs as it is free from greenhouse gas emissions and unlimited in nature. Integration of roof-top solar PV systems is currently emerging rapidly in Australia as the governments are giving attractive incentives and encouraging households to build a sustainable climate-friendly society for the future. The key major barriers to the integration of roof-top solar PV systems are the uncertainties in the performance of the low voltage distribution network due to the intermittent nature of solar PV sources. In this paper, a model was developed to investigate the potential technical impacts of integrating roof-top solar PV systems into the low voltage distribution network in a subtropical climate. The results show that integration of roof-top solar PV in the customer premises causes uncertainties such as voltage fluctuations, phase unbalance, distribution transformer overloading, reactive power compensation, and harmonic injections that detract the overall power quality of the typical distribution network. © 2014 AIP Publishing LLC.

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This paper describes the formulation of a Multi-objective Pipe Smoothing Genetic Algorithm (MOPSGA) and its application to the least cost water distribution network design problem. Evolutionary Algorithms have been widely utilised for the optimisation of both theoretical and real-world non-linear optimisation problems, including water system design and maintenance problems. In this work we present a pipe smoothing based approach to the creation and mutation of chromosomes which utilises engineering expertise with the view to increasing the performance of the algorithm whilst promoting engineering feasibility within the population of solutions. MOPSGA is based upon the standard Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and incorporates a modified population initialiser and mutation operator which directly targets elements of a network with the aim to increase network smoothness (in terms of progression from one diameter to the next) using network element awareness and an elementary heuristic. The pipe smoothing heuristic used in this algorithm is based upon a fundamental principle employed by water system engineers when designing water distribution pipe networks where the diameter of any pipe is never greater than the sum of the diameters of the pipes directly upstream resulting in the transition from large to small diameters from source to the extremities of the network. MOPSGA is assessed on a number of water distribution network benchmarks from the literature including some real-world based, large scale systems. The performance of MOPSGA is directly compared to that of NSGA-II with regard to solution quality, engineering feasibility (network smoothness) and computational efficiency. MOPSGA is shown to promote both engineering and hydraulic feasibility whilst attaining good infrastructure costs compared to NSGA-II.

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An optimization technique to solve distribution network planning (DNP) problem is presented. This is a very complex mixed binary nonlinear programming problem. A constructive heuristic algorithm (CHA) aimed at obtaining an excellent quality solution for this problem is presented. In each step of the CHA, a sensitivity index is used to add a circuit or a substation to the distribution network. This sensitivity index is obtained solving the DNP problem considering the numbers of circuits and substations to be added as continuous variables (relaxed problem). The relaxed problem is a large and complex nonlinear programming and was solved through an efficient nonlinear optimization solver. A local improvement phase and a branching technique were implemented in the CHA. Results of two tests using a distribution network are presented in the paper in order to show the ability of the proposed algorithm. ©2009 IEEE.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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The objective of this report is to study distributed (decentralized) three phase optimal power flow (OPF) problem in unbalanced power distribution networks. A full three phase representation of the distribution networks is considered to account for the highly unbalance state of the distribution networks. All distribution network’s series/shunt components, and load types/combinations had been modeled on commercial version of General Algebraic Modeling System (GAMS), the high-level modeling system for mathematical programming and optimization. The OPF problem has been successfully implemented and solved in a centralized approach and distributed approach, where the objective is to minimize the active power losses in the entire system. The study was implemented on the IEEE-37 Node Test Feeder. A detailed discussion of all problem sides and aspects starting from the basics has been provided in this study. Full simulation results have been provided at the end of the report.

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An asymmetric stripline is proposed in this paper. The main aim of this line is to distribute the power among subarrays in an array with minimum losses. Several vertical transitions to subarrays are shown besides some network designs at X band for a square array for satellite communications.