SARMA Time Series for Microscopic Electrical Load Modeling

Abstract

In the current context of profound changes in the planning and operations of electrical systems, many Distribution System Operators (DSOs) are deploying Smart Meters at a large scale. The latter should participate in the effort of making the grid smarter through active management strategies such as storage or demand response. These considerations involve to model electrical quantities as locally as possible and on a sequential basis. This paper explores the possibility to model microscopic loads (individual loads) using Seasonal Auto-Regressive Moving Average (SARMA) time series based solely on Smart Meters data. A systematic definition of models for 18 customers has been applied using their consumption data. The main novelty is the qualitative analysis of complete SARMA models on different types of customers and an evaluation of their general performance in an LV network application. We find that residential loads are easily captured using a single SARMA model whereas other profiles of clients require segmentation due to strong additional seasonalities.