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This study aims to investigate the water spray uniformity and collection ratio of sprinkler in an evaporative condenser of a water chiller. Experiments of water droplet distribution are conducted with 50 water collectors during the tests. Three different combinations of nozzle opening length and width were tested with the flow rates varied at 135 LPM and 176.4 LPM. Measured results show that the cross-sectional area of nozzle opening and flow rate significantly affect the water spray uniformity. In this work, at high flow rate, the Nozzle 2 with opening of 4 cm in length and 1 cm in width has better water spray uniformity compared to the nozzle 1 with opening of 4 cm in length and 0.7 cm in width. On the other hand, at low flow rate, the Nozzle 1 provides better impacting effect with the nozzle spacing of 17 cm, yet the Nozzle 2 performed better with the nozzle spacing of 15 cm. The latter case, with the smaller nozzle spacing and bigger nozzle opening size, led to a shorter impact distance of the spraying flow from two facing nozzles. Subsequently the spattering of water droplets was more pronounced, and distributed more uniformly. Keywords: Water spray uniformity, Collection ratio of sprinkler, Evaporative condenser, Nozzle opening

This paper presents several advances for the PMU placement problem (PPP). Existing approaches have difficulty scaling to full-scale systems, and are not guaranteed to be resilient to multiple component failures. This paper expands PPP to a more general k-resilient PPP, where any k PMUs and/or lines can fail without jeopardizing the problem's full supervision criterion. Our PPP model — a novel formulation based on maximum-flow network design — is unique in that it is amenable to efficient decomposition, which significantly improves tractability and scalability. We present two cutting plane algorithms to support this decomposition — the first such algorithms for the PPP to our knowledge. The improvements in computational efficiency afforded by the network decomposition suggest that our approach can solve the PPP for large-scale systems.

Fouling behavior under reburn conditions was investigated with cattle wastes (termed as feedlot biomass [FB]) and coal as reburn fuels under a transient condition and short-time operation. A small-scale (30 kW or 100,000 Btu/hr) boiler burner research facility was used for the reburn experiments. The fuels considered for these experiments were natural gas (NG) for the ashless case, pure coal, pure FB, and blends of coal and FB. Two parameters that were used to characterize the ash "fouling" were (1) the overall heat-transfer coefficient (OHTC) when burning NG and solid fuels as reburn fuels, and (2) the combustible loss through ash deposited on the surfaces of heat exchanger tubes and the bottom ash in the ash port. A new methodology is presented for determining ash-fouling behavior under transient conditions. Results on the OHTCs for solid reburn fuels are compared with the OHTCs for NG. It was found that the growth of the layer of ash depositions over longer periods typically lowers OHTC, and the increased concentration of ash in gas phase promotes radiation in high-temperature zones during initial periods while decreasing the heat transfer in low-temperature zones. The ash analyses indicated that the bottom ash in the ash port contained a smaller percentage of combustibles with a higher FB percentage in the fuels, indicating better performance compared with coal because small particles in FB burn faster and the FB has higher volatile matter on a dry ash-free basis promoting more burn out.

Abstract Most work in dynamic heat exchanger modeling for control design can be classified as either a finite volume or a moving boundary formulation. These approaches represent fundamentally different discretization approaches and are often characterized as contrasting accuracy with simulation speed. This work challenges that characterization by validating finite volume and moving boundary heat exchanger models with experimental data from a vapor compression system in order to demonstrate that these approaches are capable of achieving similar levels of accuracy. However, there are differences. The moving boundary model is found to have faster simulation speed, while the finite volume model is more flexible for adaptation to heat exchangers of different physical configuration. The formulation of each modeling approach used in this work is described in detail and techniques to increase simulation speed and avoid numerical issues in implementation are discussed.

In recent years, Smart Grid was introduced to achieve an environmentally-friendly, adequate, secure and fossil fuel-independent power system. The large scale smart grid studies require accurate state estimation to obtain an acceptable adequacy level. There exist some challenges regarding anomalous power flow studies which motivate grid operators to utilize robust and accurate estimation methods. Therefore, power system state estimators play a pivotal role in real-time grid management. In this paper, a sequential linear minimum mean square error (LMMSE) estimator is utilized to solve the DC power flow problem. First, we introduce the classic linear estimator model which assumes that to-be-estimated parameter values are unknown but deterministic. The LMMSE estimator will be discussed which treats the to-be-estimated parameter as a random variable with a known prior probability density function (pdf). We evaluate the accuracy of the LMMSE estimator by comparing it with maximum likelihood estimator (MLE). Finally, the effect of covariance matrix topology will be studied by defining three scenarios with different noise covariance matrices.

Abstract Pyrolysis of corncob particles was conducted in nitrogen in an externally heated benchscale fluidized bed reactor. Test results are presented with a demonstration of their application in gasification modeling.

This paper presents an approach for intelligent distributed control of power plants using the concept of multi-agent systems (MAS). Solving the problem of optimally controlling a power plant based on multiple objectives, such as minimizing pollution, maximizing equipment life, etc., and coordinating each of the involved tasks that must be performed in distributed environments is a challenge, which involves many individual computationally intensive tasks. These tasks include calculating feasible control valve operating ranges based on unit load demand, multi-objective optimization, training neural networks, monitoring and managing real-time input/output data, and task delegation, among others. Since each of these tasks requires such computational overhead and these systems need to be coordinated among distributed environments, it is necessary to divide them up into multiple agents. The presented method of design of the multi-agent system is a continuation of research to develop a multi-agent system to implement a technique for computing optimal multi-objective power plant controls.

This paper presents the development of a novel digital relay model and its validation by a digital relay data analysis application. The model is developed as a SIMULINK S-function block. MATLAB file I/O functions are employed to generate an oscillography file and an event report. The expert system based digital relay data analysis application validates the relay model and generates diagnosis information for refining the model. An example is used to demonstrate the procedure of simulation, validation, and refining