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An agent-based modelling approach for domestic load simulation

Panel: 6. Appliances, product policy and ICT

This is a peer-reviewed paper.

Authors:
Ana Soares, Universidade de Coimbra, Portugal
Carlos Henggeler Antunes, INESC Coimbra / University of Coimbra, Portugal
Alvaro Gomes, INESC Coimbra / University of Coimbra, Portugal

Abstract

The evolution of power systems towards smart grids will expectedly foster the implementation of dynamic tariffs and provide the technological basis for a broader dissemination of local generation and electricity storage. These trends will require a more proactive attitude from typical domestic end-users, namely determining the best demand response strategies: when using, storing or selling electricity back to the grid in face of dynamic variables such as electricity prices, weather conditions, comfort requirements, and local generation availability. This is a very challenging decision process that requires some form of automated support to achieve optimal decisions. This process may be simplified using a decision support tool in the form of energy management systems (EMS) endowed with algorithms with the capability of simulating consumption and able to manage different loads, generation and storage resources. The objective of the EMS is to minimize domestic end-user’s electricity bill without degrading the quality of the energy service provided. The design of adequate management algorithms requires a robust simulation tool able to compute the electricity consumption within a home and the impact of the management algorithms on the end-users’ electricity bill and quality of service. This simulation tool must consider the uncertainty associated with the use of certain appliances, end-users’ habits and preferences besides having also some forecasting capability.

Agent-based models (ABM) can be used in this context to build a simulation environment where the behaviour of loads without interference of any management system and the behaviour of loads managed by an EMS is replicated. The aim of this paper is to present an ABM simulation tool able to reproduce end-user’s electricity consumption profiles. This tool is an essential step to develop and test the robustness and acceptance of management algorithms to optimize the use of multiple endogenous energy resources.

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