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Physically Based Stochastic Models of Power System Loads

机译：基于物理的电力系统负荷随机模型

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Power system load, being composed of a large number of individual devices and systems connected on the power system at various points, presents a very interesting and challenging modeling problem. In the past, load models have been developed for special purposes often using an empirical approach. Recently several new approaches to constructing physically-based models for power system loads have been proposed. This report examines one approach which attempts to construct dynamic models for both short-term demand prediction and long-term stability assessment. The basic idea is to start with a simple stochastic model for an individual load element, then develop a method for aggregation that yields tractable models for bulk-power substation loads. The intent of this approach is to include relevant weather effects and the response of the load to voltage variations. The material presented includes: a general methodology for constructing both demand and response models from stochastic point process theory; several examples of physically-based load element models; are detailed applications of this general approach; and some incomplete, or nonvalidated, information on identifiability of parameters and on aspects of implementation of parameter estimators. It is suggested that validation of these, and other models, in a wide variety of situations and applications is the next logical step in improving the state of the art in power system load modeling. (ERA citation 08:000536)

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