A Practical Probabilistic Design Procedure for LV Residential Distribution Systems

Abstract

Two basic types of low voltage (LV) distribution exist in practice. The systems based on the European approach have long LV feeders whose sizing requires more careful design consideration than systems based on North American practice with shorter LV feeders. The most important criterion in conductor sizing is the correct estimation of the design loads. This paper describes the development and application of a probabilistic design method based on the Beta probability density function (pdf). The paper investigates an approximate approach for estimating load parameters in countries where a large load database is not available. This approach estimates the Beta parameters from the group after-diversity-maximum-demand (ADMD) for the customers.

Energy efficient reconfiguration for practical load combinations in distribution systems

“…Table 1 lists voltage exponents for static load models. The voltage exponents of load classes differ from each other because of aggregated load patterns [4][5][6][7][8][9][10].…”

“…In this scenario, multi-objective approach of reconfiguration provides more flexibility to the utility to operate the system to actively participate in a competitive deregulated environment. Loads, in distribution systems, are modelled as composite loads for power flow and stability studies in [4][5][6][7][8][9][10]. The effect of these load models on EEDPs, that is, active and reactive load demands [5,6], loadability limit [7] and the load demand at the substation with distribution resource placement [11,12], are studied and it was observed that these EEDPs respond differently to these loads.…”

“…Loads, in distribution systems, are modelled as composite loads for power flow and stability studies in [4][5][6][7][8][9][10]. The effect of these load models on EEDPs, that is, active and reactive load demands [5,6], loadability limit [7] and the load demand at the substation with distribution resource placement [11,12], are studied and it was observed that these EEDPs respond differently to these loads. Moreover, load models also affect load flow solutions and their convergence [13].…”

Investigating a probabilistic customer interruption costs and energy not supplied assessment for electric power distribution residential customers

“…Load parameters can be estimates from the group after diversity maximum demand (ADMD) for the customers in countries where a large load database is not available, and but this study uses available load data in South Africa. Using the mean and standard deviation of the outage duration distribution, the α and β parameters are calculated as shown in equations 1 and 2 [13]. A typical interruption duration distribution is shown in Figure 6.…”

“…Where µ is mean of the outage duration, σ is the standard deviation and C is the limiting factor [13]. The beta PDF model is used for this study for the following reasons [13]:…”