Multi-objective demand response to real-time prices (RTP) using a task scheduling methodology

• Published in: Energy (Oxford) Vol. 138; pp. 19 - 31
• Main Authors: Cortés-Arcos, Tomás, Bernal-Agustín, José L., Dufo-López, Rodolfo, Lujano-Rojas, Juan M., Contreras, Javier
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.11.2017; Elsevier BV
• Subjects: Algorithms; Cost engineering; Cost reduction; Demand response; Electricity; Electricity consumption; Electricity pricing; Energy consumption; Energy management; Evolutionary algorithm; Evolutionary algorithms; Habits; Methodology; Multi-objective problem; Multiple objective analysis; Pareto optimum; Real time; Risk management; Task scheduling; Task scheduling methodology; Demand response; Multi-objective problem; Evolutionary algorithm; Task scheduling methodology
• ISSN: 0360-5442; 1873-6785
• DOI: 10.1016/j.energy.2017.07.056

This paper presents a multi-objective problem, whose resolution is carried out using a task management methodology and an evolutionary algorithm. The multi-objective problem includes demand response to real-time prices (RTP). Two objectives have been considered: the daily cost of electricity and consumer dissatisfaction, minimizing both. Hourly prices corresponding to a tariff currently existing in Spain have been used to evaluate the daily cost of the consumed electricity. The degree of compliance with the daily task programming required by the user has been used to evaluate the dissatisfaction of the consumer. Using a multi-objective evolutionary algorithm (NSGA-II), it has been possible to use the concept of Pareto optimality in order to determine the best solutions for the problem. The results show that the applied methodology can lead to cost savings between 6% and 12% without substantially changing the consumption habits of the consumer. If the consumer is willing to change his/her consumption habits, then the cost savings can reach 50%. In addition to cost savings, this methodology can reduce energy losses in the electric grid because the shift of consumption from peak to off-peak hours. •This work presents a multi-objective problem solved using a task management methodology.•The objectives are the daily cost of electricity and consumer dissatisfaction, minimizing both.•The NSGA-II and the concept of Pareto optimality have been used.•The applied methodology can lead to cost savings between 6% and 12%.•The cost saving can reach 50% if the consumer changes his/her consumption habits.