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HEMS

Sawsan Al Zahr

[Invited paper] Proc. of the IEEE MENACOMM Confrence, Jounieh, Lebanon, Apr. 2018
DOI: 10.1109/MENACOMM.2018.8371044

Abstract: Along with the growing penetration of renewable energy sources, demand side management (DSM) is becoming a key component of future energy systems such as smart grids. DSM aims at balancing the demand for power with intermittent renewable energy sources such as wind and solar units. DSM deploys various mechanisms to influence customer’s capability and willingness to modify their power consumption according to the utility’s energy production and the distribution capacity. DSM aims at either saving energy in sustainable manner (i.e. energy response) or/and shifting the time of energy use to off-peak hours (i.e. demand response). Indeed, DSM does not necessarily reduce the total customer’s power consumption but reshapes consumption patterns. Hence, DSM is expected to reduce the need for investments in networks and power plants in order to meet peak demands. In this paper, we propose an advanced demand response (DR) solution for individual households. Considering a household equipped with various domestic loads, we aim at optimally scheduling the day-ahead power consumption under timevariable rates while taking advantage of modular and deferrable loads, e.g. electric vehicle. Our proposal is numerically illustrated through real-life scenarios, elaborated using an existing simulator of human behavior regarding power consumption.

Sawsan Al Zahr, Elias A. Doumith, Philippe Forestier

Proc. of the IEEE Globecom Confrence, Singapore, Singapore, Dec. 2017
DOI: 10.1109/GLOCOM.2017.8255068

Abstract: As the global energy policy is changing from a demand-driven to a supply-driven approach, demand side management (DSM) is becoming a key component of future energy systems. Indeed, it helps power grids’ operators to balance the demand for power with intermittent renewable energy sources such as wind and solar units. DSM consists in optimizing/adapting the power consumption to meet the production through various methods such as improving the energy efficiency by using better equipment and materials, implementing demand response (DR) solutions, etc. DSM mechanisms do not necessarily reduce the total power consumption, but reshape the consumption pattern. Hence, DSM is expected to reduce the need for investments in networks and power plants in order to meet peak demands. In this paper, we propose an advanced DR solution for individual households. Considering a household equipped with various domestic loads, we aim at optimally scheduling the day-ahead power consumption under time-variable rates while taking advantage of modular and deferrable loads, e.g., electric vehicle. For this purpose, we propose an exact approach to solve the problem of energy management within a household under both system’s and user’s constraints. Our proposal is numerically validated through real- life scenarios, elaborated using an existing simulator of human behavior regarding power consumption.