A Real-Time Dynamic Optimization Based Heuristic Algorithm for Home Energy Management System
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Abstract
Modern buildings are being designed with increasingly sophisticated energy management and control systems that have the capabilities for monitoring and controlling the conditions in buildings. Reducing and scheduling energy usage is the key for any home energy management system. To better match demand and supply, many utilities offer residential demand response program to change the pattern of power consumption of a residential customer by curtailing or shifting their energy use during the peak time period. In the present study, real time optimal schedule controller for home energy management system is proposed using a heuristic algorithm to manage the energy consumption. The proposed method gives optimal schedule for home devices in order to limit the demand of total load and schedule the operation of home appliances at specific times during the day. A set of the most common home appliances, namely, air conditioner, water heater, refrigerator, and washing machine has been considered to be controlled.
Keywords
Energy Smart-Home, Residential demand response, Energy efficiency, Schedule controller
Article Details
References
[1] Z. Zhao, W.C. Lee, Y. Shin, K.-B. Song. "An optimal power scheduling method for demand response in home energy management system", IEEE Trans. Smart Grid 4 (3) (2013):1391-1400
[2] B. Yuce, Y. Rezgui, M. Mourshed. "ANN-GA smart appliance scheduling for optimized energy management in the domestic sector", Energy Build. 111, (2016):311-325
[3] M. Ahmed, A. Mohamed, R. Homod, H. Shareef. "Hybrid LSA-ANN based home energy management scheduling controller for residential demand response strategy". Energies 9(9) (2016) 716.
[4] N. Yaagoubi, H.T. Mouftah. "User-aware game theoretic approach for demand management", IEEE Trans. Smart Grid 6(2) (2015) 716-725.
[5] Z. Chen, L. Wu, Y. Fu, "Real-time price-based demand response management for residential appliances via stochastic optimization and robust optimization", IEEE Trans. Smart Grid 3(4) (2012): 1822-1831.
[6] Ahmed. M. S., Mohamed, A., Khatib, T., Shareef, H., Homod, R. Z., & Ali, J. A. "Real time optimal schedule controller for home energy management system using new binary backtracking search algorithm". Energy and Buildings, 138, (2017): 215-227.
[7] Ghiaus C. "Causality issue in the heat balance method for calculating the design heating and cooling load". Energy Build; 50(0) (2013):292-301.
[8] Ha, D. L., Ploix, S., Jacomino, M., & Le, M. Η. (2010). "Home energy management problem: towards an optimal and robust solution". In Energy Management. InTech.
[9] AFNOR. "Ergonomie des ambiances thermiques, détermination analytique et interprétation du confort thermique par le calcul des indices PMV et PDD et par des critères de confort thermique local". Norme européenne. (2006).
[2] B. Yuce, Y. Rezgui, M. Mourshed. "ANN-GA smart appliance scheduling for optimized energy management in the domestic sector", Energy Build. 111, (2016):311-325
[3] M. Ahmed, A. Mohamed, R. Homod, H. Shareef. "Hybrid LSA-ANN based home energy management scheduling controller for residential demand response strategy". Energies 9(9) (2016) 716.
[4] N. Yaagoubi, H.T. Mouftah. "User-aware game theoretic approach for demand management", IEEE Trans. Smart Grid 6(2) (2015) 716-725.
[5] Z. Chen, L. Wu, Y. Fu, "Real-time price-based demand response management for residential appliances via stochastic optimization and robust optimization", IEEE Trans. Smart Grid 3(4) (2012): 1822-1831.
[6] Ahmed. M. S., Mohamed, A., Khatib, T., Shareef, H., Homod, R. Z., & Ali, J. A. "Real time optimal schedule controller for home energy management system using new binary backtracking search algorithm". Energy and Buildings, 138, (2017): 215-227.
[7] Ghiaus C. "Causality issue in the heat balance method for calculating the design heating and cooling load". Energy Build; 50(0) (2013):292-301.
[8] Ha, D. L., Ploix, S., Jacomino, M., & Le, M. Η. (2010). "Home energy management problem: towards an optimal and robust solution". In Energy Management. InTech.
[9] AFNOR. "Ergonomie des ambiances thermiques, détermination analytique et interprétation du confort thermique par le calcul des indices PMV et PDD et par des critères de confort thermique local". Norme européenne. (2006).