A home energy management algorithm in demand response events for household peak load reduction

• Autorzy: Ahmed M. S. , Mohamed A. , Homod R. Z. , Shreef H.

Identyfikatory

DOI

10.15199/48.2017.03.46

Warianty tytułu

PL

Algorytm zarządzania konsumpcj a enegii w gospodarstwach domowych

• Języki publikacji: EN

Abstrakty

EN

In the last decades, home energy consumption has increased significantly due to increasing load demand in the residential sector. This paper presents a home energy management (HEM) algorithm to manage the home appliances in a house during a demand response (DR) event. The developed algorithm considers load appliances according to customer preference setting, priority of appliance, and comfortable lifestyle that can be changed at any given time and performs DR at appliance level. The load models are developed based on the operational and physical characteristics for the purpose of DR strategies. Appropriate residential load models are required to support the DR strategies and therefore air conditioner, water heater, electric vehicle and washing machine are chosen as the loads. The proposed HEM algorithm is shown to be effective in managing power consumption at appliances level and can maintain the total household power consumption below its demand limit (DL) without affecting the comfort level.

PL

W artykule predstawiono algorytm do zarządzania konsumpcja energii w gospodarstwach domowych. Algorytm zarządza enegią przy założonym poziomie dopuszczalnego limitu I bazuje na charakterystykach urządzeń podłączonych do sieci.

Słowa kluczowe

EN

home energy management; demand response; smart appliance; energy efficiency; peak load reduction

PL

konsumpcja energii; gospodarstwo domowe; algorytm HEM

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2017
• Tom: R. 93, nr 3
• Strony: 197--200
• Opis fizyczny: Bibliogr. 18 poz., rys., tab.

Twórcy

autor

Ahmed M. S.

• Department of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia (UKM)
• General Directorate of Electrical Energy Production- Basrah, Ministry of electricity, Iraq

autor

Mohamed A.

• Department of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia (UKM)

autor

Homod R. Z.

• Dept. of Petroleum and Gas Engineering, Basrah University, Iraq

autor

Shreef H.

• Department of Electrical Engineering, United Arab Emirates University

Bibliografia

• [1] Zhang X., Shahidehpour M., Alabdulwahab A., Abusorrah A., Hourly Electricity Demand Response in the Stochastic Day- Ahead Scheduling of Coordinated Electricity and Natural Gas Networks, IEEE Trans on Power Syst. 31 (2016) 592-601.
• [2] Maharjan S., Zhu Q., Zhang Y., Gjessing S., Basar T., Demand Response Management in the Smart Grid in a Large Population Regime, IEEE Trans on SG. 7 (2016) 189-199.
• [3] Moreno-Munoz A., Bellido-Outeirino F.J., Siano P., Gomez- Nieto M.A., Mobile social media for smart grids customer engagement: Emerging trends and challenges, Renewable and Sustainable Energy Reviews. 53 ( 2016)1611-1616.
• [4] Ahmed M.S., Mohamed A., Homod R. Z., Shareef H., Real time optimal schedule controller for home energy management system using new binary backtracking search algorithm, Energy and Buildings. 138 (2017) 215-227.
• [5] Kushiro N., A Basic Study for Realizing Life Event Sensor for Home Energy Management System, Knowledge-Based information systems in Practice. Springer International Publishing, (2015) 21-38.
• [6] Patel K., Khosla A., Home energy management systems in future Smart Grid networks: A systematic review, IEEE NGCT. (2015) 479-483.
• [7] Gudi N., Wang L., Devabhaktuni V., A demand side management based simulation platform incorporating heuristic optimization for management of household appliances, Int. J. Electr. Power Energy Syst. 43 (2012) 185–193.
• [8] Hong Y. Y., Chen C. R., Yang H W., Implementation of demand response in home energy management system using immune clonal selection algorithm, IEEE CEC conf. (2015) 3377-3382.
• [9] Zhang Y., Zeng P., Zang C., Optimization algorithm for home energy management system based on artificial bee colony in smart grid, IEEE CYBER conf. (2015) 734-740.
• [10] Mohsenian-Rad A H., Leon-Garcia A., Optimal residential load control with price prediction in real-time electricity pricing environments, IEEE Trans on SG. 2 (2010)120-133.
• [11] Ahmed M. S., Shareef H., Mohamed A., Ali J. A., Mutlag AH. Rule Base Home Energy Management System Considering Residential Demand Response Application, Appl Mechanics & Materials. 785 (2015) 526-531.
• [12] Li X. H., Hong S. H., User-expected price-based demand response algorithm for a home-to-grid system, Energy. 64(2014) 437-49.
• [13] Ahmed M.S., Mohamed A., Homod R. Z., Shareef H., Sabry A. H., Khalid K.B., Smart plug prototype for monitoring electrical appliances in Home Energy Management System, IEEE SCOReD conf. (2015) 32-36.
• [14] Wehierek P., Konarski M., Electricity measurement accuracy in the smart metering system, Electrical review, R. 91 NR 3 / 2015.
• [15] Ahmed M.S., Mohamed A., Homod R. Z., Shareef H., Khalid K., Modeling of Electric Water Heater and Air Conditioner for Residential Demand Response Strategy. International Journal of Applied Engineering Research. 11 (2016) 9037-9046.
• [16] Fiori C., Ahn K., Rakha H. A., Power-based electric vehicle energy consumption model: Model development and validation, Applied Energy. 168 (2016) 257-268.
• [17] Chi S., Zhang Z., Xu L., Sliding-mode sensorless control of direct-drive PM synchronous motors for washing machine applications, IEEE Trans on IA. 45 (2009) 582-90.
• [18] Ahmed M.S., Mohamed A., Homod R. Z., Shareef H., Hybrid LSA-ANN Based Home Energy Management Scheduling Controller for Residential Demand Response Strategy, energies. 9 (2016) 716.

Uwagi

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).