Journal
APPLIED SCIENCES-BASEL
Volume 10, Issue 5, Pages -Publisher
MDPI
DOI: 10.3390/app10051627
Keywords
model predictive control; mixed integer programming; smart appliance scheduling; demand-side-management
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Funding
- INDICATE project under the European Unions 7th Framework Programme for research [608775]
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In this work, an algorithm for the scheduling of household appliances to reduce the energy cost and the peak-power consumption is proposed. The system architecture of a home energy management system (HEMS) is presented to operate the appliances. The dynamics of thermal and non-thermal appliances is represented into state-space model to formulate the scheduling task into a mixed-integer-linear-programming (MILP) optimization problem. Model predictive control (MPC) strategy is used to operate the appliances in real-time. The HEMS schedules the appliances in dynamic manner without any a priori knowledge of the load-consumption pattern. At the same time, the HEMS responds to the real-time electricity market and the external environmental conditions (solar radiation, ambient temperature, etc.). Simulation results exhibit the benefits of the proposed HEMS by showing the reduction of up to 70% in electricity cost and up to 57% in peak power consumption.
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