Multi-Agent Simulation of Urban Social Dynamics for Spatial Load Forecasting

Abstract

A multi-agent system for spatial electric load forecasting, especially suited to simulating the different social dynamics involved in distribution systems, is presented. This approach improves the spatial forecasting techniques that usually consider the service zone as a static entity to model or simulate the spatial electric load forecasting in a city. This paper aims to determine how the electric load will be distributed among the sub-zones in the city. For this, the service zone is divided into several subzones, each subzone considered as an independent agent identified with a corresponding load level, and their relationships with the neighbor zones are represented through development probabilities. These probabilities are considered as input data for the simulation. Given this setting, different kinds of agents can be developed to simulate the growth pattern of the loads in distribution systems in parallel. The approach is tested with data from a real distribution system in a mid-size city; the results show a low spatial error when compared to real data. Less than 6% of the load growth was identified 0.71 km outside of its correct location on the test system.