P3. Smart Load Control and Grid-Friendly Appliances > Outcomes

Technical Outcomes:

• Two load controller prototypes, based on detecting under-frequency events and based on spectral analysis, were developed, built, and tested. The first load controller prototype responded to under-frequency events and rapid decay in the grid frequency. The controller was based on a personal computer (PC) platform with a Microsoft DOS operating system. The second load controller prototype was used for the statistical and spectral analysis of historic frequency data of known grid events. It was based on a PC with a Linux operating system that provided real-time controller capability as well as processing historic data read from a data file. To test the hypotheses postulated, historic data representing two distinct grid events were analyzed. The first data set represented the WECC breakup of August 10, 1996 that caused wide-spread outages in the western region. The other data set (dated October 8, 2002) represented a transmission line trip followed by some remedial action and scattered load loss.

• The results of the data analysis did not support the hypotheses. The randomness and magnitude of constantly changing loads, adjustments by generators to meet the demand, and the randomness of the unplanned outages, cause changes in the topology of the network making it very difficult, if not impossible, to definitively declare a state of the power system as low stress. Even during periods at night, when the load tends to be lower than during the day, it is not obvious that the system attains a low or lower-stress state. Transmission outages, planned or unplanned, may pose a difficult burden on transmission engineers to keep the system in stable and safe condition. Because of the inherent inability to establish a state of low stress as a reference case, it became difficult during this analysis of historic data to detect the transition from a safe condition to that of an impending problem.

Market Outcomes:

As a result of this data analysis, it appears questionable whether the chosen approach will be successful in the long-run. The major obstacle for this approach is the necessity to establish a reference scenario that would represent safe grid operating conditions. To establish this, a large series of the conditions needs to be analyzed to become familiar with the spectrum of variability for each indicator to establish signatures or patterns for impending problems.

An alternative approach to detecting grid instability focuses on determining the transfer function that describes the dynamic behavior of the entire power system, from which the standard stability analysis methods can be applied. So far, no one has successfully established a power system transfer function of sufficient accuracy with which to perform a meaningful stability analysis.

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