A HOME APPLIANCE CONTROL SYSTEM FOR ENERGY MANAGEMENT

Year 2020, Volume: 8 Issue: 3, 912 - 920, 24.09.2020

Hanife Apaydın Özkan

https://doi.org/10.21923/jesd.697845

Cited By: 1

Abstract

In this work, a Home Appliance Control System is proposed as a Home Energy Management System for preventing high peak demand and reducing electricity cost while keeping user comfort. The proposed Home Appliance Control System consists of a home equipped with smart appliances, grid, communication network and a Main Controller and it is based on appliance interference under certain conditions. Appliances are separated as controllable, semi-controllable and uncontrollable according to their effects on user comfort. Main Controller is not allowed to interfere with uncontrollable appliances, but with semi-controllable and controllable appliances as much as it is permitted. Appliance interference is done on real time in the order of appliance priority defined by the user due to expected power consumption and the grid limit. The corresponding control algorithm of Home Appliance Control System is also developed. Simulation results demonstrate the effectiveness of the proposed system on achieving the intended goals.

Keywords

Home energy management, home appliance, electricity cost, peak demand

EV ENERJİ YÖNETİMİ İÇİN EV CİHAZLARININ KONTROLÜ

Abstract

Bu çalışmada kullanıcı konforunu korurken elektrik maliyetini düşürmeyi ve anlık yüksek güç talebini önlemeyi hedefleyen bir Ev Enerji Yönetim sistemi olarak, bir Ev Cihazları Kontrol sistemi önerilmiştir. Önerilen Ev Cihazları Kontrol sistemi akıllı cihazlar, şebeke, haberleşme ünitesi ve bir ana kontrolcüden oluşmakta; ve cihazlara belirli koşullar altında müdahale etme esasına dayanmaktadır. Cihazlar kullanıcı konforuna etkilerine göre kontrol edilebilir, yarı-kontrol edilebilir ve kontrol edilemez olarak üçe ayrılmaktadır. Ana kontrolcünün kontrol edilemeyen cihazlara müdahale etmesine izin verilmezken, yarı kontrol edilebilir ve kontrol edilebilir cihazlara izin verilen ölçüde müdahale etmesine izin verilmektedir. Cihazlara kullanıcı tarafından belirlenen öncelik sırası ve belirlenen şebeke limitleri dikkate alınarak gerçek zamanlı müdahale edilmektedir. Önerilen Ev Cihazları Kontrol sistemine uygun kontrol algoritması da geliştirilmiştir. Simulasyon sonuçları sistemin amaçlanan sonuçlara ulaşmadaki başarısını göstermektedir.

Keywords

Ev enerji yönetimi, ev cihazları, elektrik maliyeti, yüksek talep, algoritma

References

• Apaydin Ozkan H. (2016). Appliance based control for home power management systems, Energy, vol. 114, pp. 693-707.
• Bui, K.-H., Jung, J. J., and Camacho, D. (2018). Consensual negotiation-based decision making for connected appliances in smart home management systems. Sensors, 18:2206
• Chauhan, R. K. and Chauhan, K. (2019). Building automation system for grid-connected home to optimize energy consumption and electricity bill. Journal of Building Engineering, 21:409 – 420.
• Conejo A., Morales J. and Baringo L., (2010). Real-time demand response model. IEEE Transactions on Smart Grid, vol.1, pp. 236-242.
• Daryanian R. and Bohn B., (1989) Optimal demand-side response to electricity spot prices for storage-type customers, IEEE Transactions on Power Systems, vol. 4 pp. 897-903.
• Du P. and Lu N., Appliance commitment for household load scheduling IEEE Trans. Smart Grid, 2 (2) (2011), pp. 411-419,
• Fernandes F. , Morais H, Vale Z and Ramos C. , Dynamic load management in a smart home to participate in demand response events, (2014). Energy and Buildings, vol 2. , pp. 592-606.
• Izmitligil H. and Apaydin Ozkan H.(2018). A Home energy management system. Transactions of the Institute of Measurement and Control, vol. 40, pp. 2498-2508.
• Kim T. and Poor H., Scheduling power consumption with price uncertainty,(2011). IEEE Transactions on Smart Grid, vol.2, pp. 519-527.
• Lee, E. and Bahn, H. (2013), ‘Electricity usage scheduling in smart building environments using smart devices’, The Scientific World Journal 2013(2), 134–143.
• Mohsenian-Rad A., Wong V., Jatskevich J. and Schober R., (2010). Optimal an autonomous incentive-based energy consumption scheduling algorithm for smart grid, Proceedings of Innovative Smart Grid Technologies, pp. 1-6.
• M. Pipattanasomporn, M. Kuzlu and S. Rahman, An algorithm for intelligent home energy management and demand response analysis,(2012). IEEE Transactions on Smart Grid, vol. 4, pp. 2166-2173.
• M. Erol-Kantarci and H. Mouftah, Wireless sensor networks for cost-effcient residential energy management in the smart grid, (2011). IEEE Transactions on Smart Grid, vol 2. , pp. 314-325.
• O’Neill, D., Levorato, M., Goldsmith, A. and Mitra, U. (2010), Residential demand response using reinforcement learning,in‘Smart Grid Communications (SmartGridComm), 2010 First IEEE International Conference on’, pp. 409–414.
• Rahimi F. and Ipakchi A., (2010). Demand response as a market resource under the smart grid paradigm , IEEE Transactions on Smart Grid, vol.1, pp. 82-88.
• Schweppe F., Daryanian B. And Tabors R., (1989). Algorithms for a spot price responding residential load controller, IEEE Transactions on Power Systems, vol. 2, pp.507-516.