Bottom-up Modelling Approach for Residential Loads

Abstract

Considering that residential sector is responsible for 52% of peak demand, it must be evaluated for demand response potential. In New Zealand, demand response strategies are already implemented in industrial sector, potential of commercial and residential sector has not been evaluated. The prime reason is lack of understanding of the customer behaviour and a detailed model of the household appliances. These constraints tend to make the analysis of demand response potential of domestic sector di cult. In this thesis, an e ort is made to create a comprehensive model of house using Matlab Simulink platform, which can simulate the behaviour of several appliances and their interaction with the environment. The bottom-up approach is physically based which takes into account external factors like size of house, thermal insulation properties based on location of the house and outdoor temperature to model individual appliances. Hence separate models of heat-pump, hot water cylinder and refrigerator are simulated in a single environment to form a household model. The study also makes an attempt to analyse customer behaviour by statistical analysis of existing load curves, and represent the electrical power consumption in terms of customer priority. The physically based models are then operated according to the customer priorities so obtained from the statistical analysis to recreate the load curves and a detailed time of use is obtained from the analysis. Time of use is utilized to estimate hourly load variation factor, which is useful tool for determining aggregate load. A stochastic process is explained for simulating several houses, based on hourly variation factor so obtained from time of use extraction. Thus, a complete bottom-up residential load model is created for determining aggregated load. Top-down approach is successfully integrated in the method by considering variation factors as the basis of creating random process. The similarity between aggregated and measured load form the basis of validation.