Work

Aggregated Demand Flexibility Prediction of Residential Thermostatically Controlled Loads and Participation in Electricity Balance Markets

Year: 2025

Type: article

Abstract: The aggregate demand flexibility of a set of residential thermostatically controlled loads (TCLs) can be represented by a virtual battery (VB) in order to manage their participation in the electricity markets. For this purpose, it is necessary to know in advance and with a high level of reliability the maximum power that can be supplied by the aggregation of TCLs. A probability function of the power that can be supplied by a VB is introduced in this paper. This probability function is used to predict the demand flexibility using a rigorous experimental probabilistic method based on a combination of Monte Carlo simulation and extremum search by bisection (MC&ESB) algorithm. As a result, the maximum flexibility power that a VB can provide is obtained. MC&ESB performs the demand flexibility prediction with a given confidence level and taking into account TCLs and users’ real‐time constraints, which is a novel contribution. The performance and validity of the proposed method are demonstrated and discussed in three different case studies where a VB bids its aggregate power in the Spanish electricity balancing markets (SEBMs).

Source: International Journal of Energy Research

DOI: 10.1155/er/8819201

Authors: Alejandro Martín-Crespo, Enrique Baeyens, Sergio Saludes-Rodil, Fernando Frechoso-Escudero

Institutions: CARTIF, Universidad de Valladolid

Language: English

Topic: Smart Grid Energy Management

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $2,700