322 resultados para 660304 Energy systems analysis
Resumo:
A set of basic reliability indices at the generation and composite generation and transmission levels for a small reliability test system are presented. The test system and the results presented have evolved from reliability research and teaching programs. The indices presented are for fundamental reliability applications which should be covered in a power system reliability teaching program. The RBTS test system and the basic indices provide a valuable reference for faculty and students engaged in reliability teaching and research
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This paper presents a new approach for network upgrading to improve the penetration level of Small Scale Generators in residential feeders. In this paper, it is proposed that a common DC link can be added to LV network to alleviate the negative impact of increased export power on AC lines, allowing customers to inject their surplus power with no restrictions to the common DC link. In addition, it is shown that the proposed approach can be a pathway from current AC network to future DC network.
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Capacity probability models of generating units are commonly used in many power system reliability studies, at hierarchical level one (HLI). Analytical modelling of a generating system with many units or generating units with many derated states in a system, can result in an extensive number of states in the capacity model. Limitations on available memory and computational time of present computer facilities can pose difficulties for assessment of such systems in many studies. A cluster procedure using the nearest centroid sorting method was used for IEEE-RTS load model. The application proved to be very effective in producing a highly similar model with substantially fewer states. This paper presents an extended application of the clustering method to include capacity probability representation. A series of sensitivity studies are illustrated using IEEE-RTS generating system and load models. The loss of load and energy expectations (LOLE, LOEE), are used as indicators to evaluate the application
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The majority of distribution utilities do not have accurate information on the constituents of their loads. This information is very useful in managing and planning the network, adequately and economically. Customer loads are normally categorized in three main sectors: 1) residential; 2) industrial; and 3) commercial. In this paper, penalized least-squares regression and Euclidean distance methods are developed for this application to identify and quantify the makeup of a feeder load with unknown sectors/subsectors. This process is done on a monthly basis to account for seasonal and other load changes. The error between the actual and estimated load profiles are used as a benchmark of accuracy. This approach has shown to be accurate in identifying customer types in unknown load profiles, and is used in cross-validation of the results and initial assumptions.
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This paper presents a reliability assessment of a substation, part of the Queensland transmission network in Australia. As part of a maintenance considerations, this study utilises the substation reliability assessment package STAREL to quantitatively compare the reliability improvement achieved by two circuit breaker reinforcement alternatives for Swanbank circuit breaker replacement or refurbishment. Substation reliability is interpreted on the basis of outage frequency and outage duration indices for each individual transmission line terminated in Swanbank 'B' substation. By considering the reliability indices in this paper with the cost associated conducted by POWERLINK Queensland, a Swanbank 'B' reinforcement alternative can be selected that optimises both transmission line security and the costs incurred in achieving it.
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Reliability is an integral component of modern power system design, planning and management. This paper uses the Markov approach to substation reliability evaluation using dedicated reliability software. This technique was applied to yield reliability indices for an existing and important substation in the POWERLINK QUEENSLAND 275 kV transmission network. Reliability indices were also determined for several reinforcement alternatives for this substation with the aim of improving substation reliability. The economic feasibility of achieving higher levels of reliability was also taken into account.
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This paper describes a new approach to establish the probabilistic cable rating based on cable thermal environment studies. Knowledge of cable parameters has been well established. However the environment in which the cables are buried is not so well understood. Research in Queensland University of Technology has been aimed at obtaining and analysing actual daily field values of thermal resistivity and diffusivity of the soil around power cables. On-line monitoring systems have been developed and installed with a data logger system and buried spheres that use an improved technique to measure thermal resistivity and diffusivity over a short period. Based on the long-term continuous field data for more than 4 years, a probabilistic approach is developed to establish the correlation between the measured field thermal resistivity values and rainfall data from weather bureau records. Hence, a probabilistic cable rating can be established based on monthly probabilistic distribution of thermal resistivity
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Power system restoration after a large area outage involves many factors, and the procedure is usually very complicated. A decision-making support system could then be developed so as to find the optimal black-start strategy. In order to evaluate candidate black-start strategies, some indices, usually both qualitative and quantitative, are employed. However, it may not be possible to directly synthesize these indices, and different extents of interactions may exist among these indices. In the existing black-start decision-making methods, qualitative and quantitative indices cannot be well synthesized, and the interactions among different indices are not taken into account. The vague set, an extended version of the well-developed fuzzy set, could be employed to deal with decision-making problems with interacting attributes. Given this background, the vague set is first employed in this work to represent the indices for facilitating the comparisons among them. Then, a concept of the vague-valued fuzzy measure is presented, and on that basis a mathematical model for black-start decision-making developed. Compared with the existing methods, the proposed method could deal with the interactions among indices and more reasonably represent the fuzzy information. Finally, an actual power system is served for demonstrating the basic features of the developed model and method.
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In this paper, a new comprehensive planning methodology is proposed for implementing distribution network reinforcement. The load growth, voltage profile, distribution line loss, and reliability are considered in this procedure. A time-segmentation technique is employed to reduce the computational load. Options considered range from supporting the load growth using the traditional approach of upgrading the conventional equipment in the distribution network, through to the use of dispatchable distributed generators (DDG). The objective function is composed of the construction cost, loss cost and reliability cost. As constraints, the bus voltages and the feeder currents should be maintained within the standard level. The DDG output power should not be less than a ratio of its rated power because of efficiency. A hybrid optimization method, called modified discrete particle swarm optimization, is employed to solve this nonlinear and discrete optimization problem. A comparison is performed between the optimized solution based on planning of capacitors along with tap-changing transformer and line upgrading and when DDGs are included in the optimization.
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A new control method for battery storage to maintain acceptable voltage profile in autonomous microgrids is proposed in this article. The proposed battery control ensures that the bus voltages in the microgrid are maintained during disturbances such as load change, loss of micro-sources, or distributed generations hitting power limit. Unlike the conventional storage control based on local measurements, the proposed method is based on an advanced control technique, where the reference power is determined based on the voltage drop profile at the battery bus. An artificial neural network based controller is used to determine the reference power needed for the battery to hold the microgrid voltage within regulation limits. The pattern of drop in the local bus voltage during power imbalance is used to train the controller off-line. During normal operation, the battery floats with the local bus voltage without any power injection. The battery is charged or discharged during the transients with a high gain feedback loop. Depending on the rate of voltage fall, it is switched to power control mode to inject the reference power determined by the proposed controller. After a defined time period, the battery power injection is reduced to zero using slow reverse-droop characteristics, ensuring a slow rate of increase in power demand from the other distributed generations. The proposed control method is simulated for various operating conditions in a microgrid with both inertial and converter interfaced sources. The proposed battery control provides a quick load pick up and smooth load sharing with the other micro-sources in a disturbance. With various disturbances, maximum voltage drop over 8% with conventional energy storage is reduced within 2.5% with the proposed control method.
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The well-established under-frequency load shedding (UFLS) is deemed to be the last of effective remedial measures against a severe frequency decline of a power system. With the ever-increasing size of power systems and the extensive penetration of distributed generators (DGs) in power systems, the problem of developing an optimal UFLS strategy is facing some new challenges. Given this background, an optimal UFLS strategy for a distribution system with DGs and load static characteristics taken into consideration is developed. Based on the frequency and the rate of change of frequency, the presented strategy consists of several basic rounds and a special round. In the basic round, the frequency emergency can be alleviated by quickly shedding some loads. In the special round, the frequency security can be maintained, and the operating parameters of the distribution system can be optimized by adjusting the output powers of DGs and some loads. The modified IEEE 37-node test feeder is employed to demonstrate the essential features of the developed optimal UFLS strategy in the MATLAB/SIMULINK environment.
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A novel intelligent online demand side management system is proposed for peak load management in low-voltage distribution networks. This method uses low-cost controllers with low-bandwidth two-way communication installed in custumers’ premises and at distribution transformers to manage the peak load while maximising customer satisfaction. A multi-objective decision making process is proposed to select the load(s) to be delayed or controlled. The efficacy of the proposed control system is verified by simulation of three different feeder types.
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Multilevel converters, because of the benefits they attract in generating high quality output voltage, are used in several applications. Various modulation and control techniques are introduced by several researchers to control the output voltage of the multilevel converters like space vector modulation and harmonic elimination (HE) methods. Multilevel converters may have a DC link with equal or unequal DC voltages. In this study a new HE technique based on the HE method is proposed for multilevel converters with unequal DC link voltage. The DC link voltage levels are considered as additional variables for the HE method and the voltage levels are defined based on the HE results. Increasing the number of voltage levels can reduce lower order harmonic content because of the fact that more variables are created. In comparison to previous methods, this new technique has a positive effect on the output voltage quality by reducing its total harmonic distortion, which must take into consideration for some applications such as uninterruptable power supply, motor drive systems and piezoelectric transducer excitation. In order to verify the proposed modulation technique, MATLAB simulations and experimental tests are carried out for a single-phase four-level diode-clamped converter.
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A general electrical model of a piezoelectric transducer for ultrasound applications consists of a capacitor in parallel with RLC legs. A high power voltage source converter can however generate significant voltage stress across the transducer that creates high leakage currents. One solution is to reduce the voltage stress across the piezoelectric transducer by using an LC filter, however a main drawback is changing the piezoelectric resonant frequency and its characteristics. Thereby it reduces the efficiency of energy conversion through the transducer. This paper proposes that a high frequency current source converter is a suitable topology to drive high power piezoelectric transducers efficiently.