This document describes the work done by the grad student Leonardo Carlassare during the six months mobility program 'Erasmus+ for Studies' at University of Coimbra, Portugal. Two professors followed me during the researches, Prof. Carlos Henggeler Antunes for the modelling and methodological part and Prof. Domenico Salvagnin for the implementation of the code. In this work first has been developed a software able to produce an appliances scheduling that reduces the electricity consumption costs of a user. This program is based on the mathematical models that describe the consumer appliances physical behavior and it should be able to run in a home-management device. Then exact and metaheuristic approaches have been used to solve a bilevel optimization (\acrshort{blo}) problem. The outcome is a pricing schedule able to maximize the profit for the electricity retailer. Lastly, a multi follower version of the BLO problem (\acrshort{blmf}) has been analyzed and a new version of the algorithm that performed the best in the second part has been used to solve it. Test results, a performance overview and optimal parameters are presented for each of these.

This document describes the work done by the grad student Leonardo Carlassare during the six months mobility program 'Erasmus+ for Studies' at University of Coimbra, Portugal. Two professors followed me during the researches, Prof. Carlos Henggeler Antunes for the modelling and methodological part and Prof. Domenico Salvagnin for the implementation of the code. In this work first has been developed a software able to produce an appliances scheduling that reduces the electricity consumption costs of a user. This program is based on the mathematical models that describe the consumer appliances physical behavior and it should be able to run in a home-management device. Then exact and metaheuristic approaches have been used to solve a bilevel optimization (\acrshort{blo}) problem. The outcome is a pricing schedule able to maximize the profit for the electricity retailer. Lastly, a multi follower version of the BLO problem (\acrshort{blmf}) has been analyzed and a new version of the algorithm that performed the best in the second part has been used to solve it. Test results, a performance overview and optimal parameters are presented for each of these.

### Price-based demand response for residential consumers using bilevel optimization

#### Abstract

This document describes the work done by the grad student Leonardo Carlassare during the six months mobility program 'Erasmus+ for Studies' at University of Coimbra, Portugal. Two professors followed me during the researches, Prof. Carlos Henggeler Antunes for the modelling and methodological part and Prof. Domenico Salvagnin for the implementation of the code. In this work first has been developed a software able to produce an appliances scheduling that reduces the electricity consumption costs of a user. This program is based on the mathematical models that describe the consumer appliances physical behavior and it should be able to run in a home-management device. Then exact and metaheuristic approaches have been used to solve a bilevel optimization (\acrshort{blo}) problem. The outcome is a pricing schedule able to maximize the profit for the electricity retailer. Lastly, a multi follower version of the BLO problem (\acrshort{blmf}) has been analyzed and a new version of the algorithm that performed the best in the second part has been used to solve it. Test results, a performance overview and optimal parameters are presented for each of these.
##### Scheda Scheda DC
2021
Price-based demand response for residential consumers using bilevel optimization
This document describes the work done by the grad student Leonardo Carlassare during the six months mobility program 'Erasmus+ for Studies' at University of Coimbra, Portugal. Two professors followed me during the researches, Prof. Carlos Henggeler Antunes for the modelling and methodological part and Prof. Domenico Salvagnin for the implementation of the code. In this work first has been developed a software able to produce an appliances scheduling that reduces the electricity consumption costs of a user. This program is based on the mathematical models that describe the consumer appliances physical behavior and it should be able to run in a home-management device. Then exact and metaheuristic approaches have been used to solve a bilevel optimization (\acrshort{blo}) problem. The outcome is a pricing schedule able to maximize the profit for the electricity retailer. Lastly, a multi follower version of the BLO problem (\acrshort{blmf}) has been analyzed and a new version of the algorithm that performed the best in the second part has been used to solve it. Test results, a performance overview and optimal parameters are presented for each of these.
Demand Response
Bilevel Optimization
Electricity
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Utilizza questo identificativo per citare o creare un link a questo documento: `https://hdl.handle.net/20.500.12608/11552`