Michael Joseph Krok

A coordinated optimization approach to Volt/VAr control for large power distribution networks

Electric distribution networks are operated under a number of constraints in order to deliver power at a certain quality and reliability level. A distributed management system (DMS) is a supervisory control layer in the distribution system used by the utilities for managing distribution assets in a coordinated fashion. For large distribution systems (those consisting of thousands of nodes and multiple tens of capacitor banks and voltage regulators), an integrated Volt/VAr Control (IVVC), which maximizes asset lifetime, is non-trivial due to the size of the search space for determining the optimal settings of these devices. This paper presents coordinated optimization approach to IVVC for large power distribution networks that will enable a more optimal operation of the distribution network while maximizing distribution control asset lifetime through the minimization of unnecessary device switching.

An integrated approach for controlling and optimizing the operation of a power distribution system

Electric distribution grid is operated under a number of constraints in order to deliver power at a certain quality and reliability level. Electrical devices, such as capacitor banks, voltage regulators, and load tap changers are employed by the utilities to facilitate and support the operation of the distribution grid, while respecting many constraints, such as maintaining an acceptable band of voltage magnitude and a certain level of power factor. Traditionally, these devices are operated under fixed schedules, based on time of day or some other local parameters, and their operations are disjointed from one another, resulting in a decreased overall effectiveness of operation. This paper presents an approach to realize an integrated control and operation of these devices that will enable a more optimal operation of the grid. Simulation studies are performed on the IEEE test feeder network and the results highlight increased efficiency of grid operation in terms of decreased line losses, increased power factor, and improved voltage profile.

Detection Of Surge Precursors In Locomotive Turbocharger

Locomotive engine performance depends among other factors on turbocharger efficiency and operating range. The turbocharger operating range can be constrained at high pressure ratio by flow induced instabilities, namely surge, in the centrifugal compressor. The resulting loss of flow results in degraded engine performance, higher exhaust emissions, high turbocharger vibration and can lead to mechanical damage on the compressor and adjoining air handling equipment. While surge avoidance methods are available to restrict the operating point to lie well within a static surge-avoid-line of the compressor, these methods can unnecessarily restrict the operating range, resulting in loss of overall performance and fuel efficiency. Surge detection and control is a closed loop strategy where a surge avoidance system starts acting if the onset of surge is detected. Use of such a strategy allows running at reduced surge margin to permit higher pressure ratio across the compressor, at potentially higher compressor efficiency, and yields increased power output from the engine at reduced emissions and improved fuel efficiency. This paper discusses a systematic approach adopted to detect precursors to the surge phenomenon, based on experiments on full-scale turbochargers and the use of a real-time wavelet algorithm to detect precursors.

Prognostics for advanced compressor health monitoring

Axial flow compressors are subjected to demands for ever-increasing levels of pressure ratio at a compression efficiency that augments the overall cycle efficiency. However, unstable flow may develop in the compressor, which can lead to a stall or surge and subsequently to gas turbine failure resulting in significant downtime and cost to repair. To protect against these potential aerodynamic instabilities, compressors are typically operated with a stall margin. This means operating the compressor at less than peak pressure rise which results in a reduction in operating efficiency and performance. Therefore, it is desirable to have a reliable method to determine the state of a compressor by detecting the onset of a damaging event prior to its occurrence. In this paper, we propose a health monitoring scheme that gathers and combines the results of different diagnostic tools to maximize the advantages of each one while at the same time minimizing their disadvantages. This fusion scheme produces results that are better than the best result by any one tool used. In part this is achieved because redundant information is available that when combined correctly improves the estimate of the better tool and compensates for the shortcomings of the less capable tool. We discuss the usage of diagnostic information fusion for a compressor event coupled with proactive control techniques to support improved compressor performance while at the same time avoid the increased damage risk due to stall margin reduction. Discretized time to failure windows provide event prediction in a prognostic sense.