An integrated price- and incentive-based demand response program for smart residential buildings: A robust multi-objective model

•DSM in smart residential buildings is taken into account.•A robust multi-objective mixed integer linear programming model is developed.•TOU and EDRP are applied simultaneously.•Scheduling the use of appliances and power exchange planning are considered.•Simultaneous use of price- and incentive-base...

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Veröffentlicht in:Sustainable cities and society Jg. 113; S. 105664
Hauptverfasser: Talebi, Hossein, Kazemi, Aliyeh, Shakouri G․, Hamed, Kocaman, Ayse Selin, Caldwell, Nigel
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 15.10.2024
Schlagworte:
Demand side management
Incentive-based programs
Multi-objective robust optimization
Price-based programs
Smart buildings
Incentive-based programs
Smart buildings
Demand side management
Price-based programs
Multi-objective robust optimization
ISSN:2210-6707
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Zusammenfassung:•DSM in smart residential buildings is taken into account.•A robust multi-objective mixed integer linear programming model is developed.•TOU and EDRP are applied simultaneously.•Scheduling the use of appliances and power exchange planning are considered.•Simultaneous use of price- and incentive-based programs can strengthen DSM. Residential buildings consume a significant amount of energy, emphasizing the importance of optimizing energy usage. Demand-side management (DSM) helps consumers and producers manage energy consumption through incentives and pricing. This study develops a new mathematical model to manage DSM in smart residential buildings. Extant literature commonly considers only a single objective function, ignores uncertainties, and applies only one price- or incentive-based program to load management in smart residential buildings. This study develops a multi-objective mixed-integer linear programming (MILP) model that applies both price- and incentive-based programs and considers uncertainties. The objectives are cost reduction, peak load minimization, user comfort improvement, and load factor maximization. This model can manage optimal schedules for household appliances and power exchange within buildings. The study shows that participating in the incentive-based program in a four-household residential complex yielded a 2 % decrease in electricity costs and a 1 % reduction in peak load while upholding comfort and load factor levels compared to non-participation. When extended to an eight-household complex, potential benefits include an 8.3 % decrease in electricity cost and a 2.6 % reduction in peak load, highlighting the program’s effectiveness in residential energy management strategies.
ISSN:2210-6707
DOI:10.1016/j.scs.2024.105664