Actual Load Demand Research Articles

Utilization of time varying event-based customer interruption cost load shedding schemes

Load curtailments occurring under emergency conditions can have significant monetary impacts on the system customers. Customer satisfaction is becoming increasingly important in the new deregulated electric utility environment, and the customers in some jurisdictions are beginning to receive monetary compensation for power supply failures. Minimizing the customer interruption costs associated with a load curtailment event is an important factor in maintaining customer satisfaction. Customer interruption costs depend on many factors such as the customer types interrupted, the actual load demand at the time of the outage, the duration of the outage, the time of day and the day in which the outage occurs. This paper focuses on incorporating these interruption cost factors in a load shedding strategy. The load shedding algorithm was developed using an approximate event-based customer interruption cost evaluation technique to identify and determine the priority of the distribution feeders on a given bus during an emergency. The developed algorithm incorporates a time dependent feeder cost priority index (FCP). The optimum load shedding set determined using the FCP is a feeder or group of feeders that meet a capacity deficiency, and result in the lowest customer interruption cost for the specified emergency situation. This paper illustrates the algorithm development for a load shedding scheme and demonstrates the utilization of the technique on a sample load bus.

Approximate Methods for Event-Based Customer Interruption Cost Evaluation

There is increasing interest in the new deregulated electric utility environment in assessing the customer costs associated with failures in electric power supply and the responsibilities associated with these failures. The customer interruption cost when an electric supply failure occurs depends on many factors, such as the customer types interrupted, the actual load demand at the time of the outage, the duration of the outage, the time of day and the day in which the outage occurs. The absence of many of the data sets required in a detailed evaluation of the customer costs makes it difficult to estimate precise individual customer outage costs due to a specific failure event. This paper illustrates the development of approximate methods for event-based customer interruption cost evaluation on a distribution feeder subjected to a specific outage event. A series of approximate methods are presented and the outage cost estimates are compared with a set of base method results. The approximate methods are based on the use of customer sector data sets, i.e., commercial, industrial, residential data, which are generally available to most utilities. The paper also illustrates further simplifications of the approximate techniques which reduce the effort required to estimate the outage costs. The approximate techniques provide a practical approach to evaluating a specific outage event.

Maximal load demand allocation

The authors address the problem of determining the maximum amount of active and reactive unserved load demand that can be connected to each bus in an electric power system without violation of its operating constraints. This maximal load demand allocation problem, which is associated with each electrical island of a power system operating in a restorative state, is formulated as a mixed nonlinear-integer programming problem. A decoupling procedure partitions the overall allocation problem into a maximal active load demand allocation subproblem and a minimal reactive load demand deallocation subproblem. The approach has been implemented in the form of a computer program and tested using power system models of up to 118 buses. Details of the implementation procedure and some illustrative test results are presented. >

Further studies on the problem of load modelling of an interconnected power system for short-term prediction

The paper presents farther results on the problem of identification of a minimal order dynamic model for the behaviour of the active load demand at a number of nodes of an interconnected power system. An earlier paper contains the results of application of the vector time series techniques. In the present paper a stochastic state variable model is identified using the recently proposed algorithm of Tse and Weinert (1976). Real data pertaining to a segment of the northern India power grid have been processed using this algorithm, and short-term load forecasts obtained through the state variable model are compared with those based on the time series model.