1. BY: A. Mahmood, I. Khan, S. Razzaq, N. Javaid, Z. Najam, N. A. Khan, M. A. Rehman COMSATS Institute of Information Technology, Islamabad, Pakistan

2. Introduction (1/3) Global Energy demand has increased. Excessive Generation is not a solution because of the economic and environmental constraints. Smart grid is one of the solutions proposed for smart use of energy resources.

3. Introduction (2/3) Smart Grid Applications: Transmission and distribution automation Optimized utilization Commodity trading of electricity in competitive markets etc.

4. Introduction (3/3) Demand Side Management (DSM): DSM includes the measures and procedures to influence the customers regarding their electricity consumption. There are many tools of DSM like Direct Load Control (DLC), Home Energy Management Systems (HEMS), Load Limiters etc. Our focus is HEMS which can be optimized by appliances co-ordination.

5. Related Work (1/2) Scheme proposed in [1] is aimed at shifting the peak loads to off peak hours using Pricing scheme used: ToU pricing In-home Wireless Sensor Networks are used for delivery of consumer requests to Energy Management Unit. [1]Erol-Kantarci, M., Mouftah, H.T.. Using wireless sensor networks for energy-aware homes in smart grids. In: Computers and Communications (ISCC), 2010 IEEE Symposium on. IEEE; 2010, pp. 456–458

6. Related Work (2/2) In [2] a Linear Programming (LP) model has been presented that aims at minimizing the cost of electricity consumption at home. In this scheme, a day is divided in consecutive time slots of equal lengths with varying prices of electricity consumption similar to Time of Use (ToU) tariff. [2] Samadi, P., Mohsenian-Rad, H., Wong, V.W., Schober, R.. Tackling the load uncertainty challenges for energy consumption scheduling in smart grid. Smart Grid, IEEE Transactions on 2013;4(2):1007–1016.

7. Proposed Scheme (HACS4EM) (1/6) The scheme involves communications among smart appliances, a central EMU and WSHAN. Conceptual interaction of different entities of this scheme is elaborated in Fig. 1 and 2. The aim of this scheme is to decrease the electricity bill of the consumer by shifting the appliances operation from peak demand hours to off-peak.

8. Proposed Scheme (2/6) Interaction of different Modules

9. Proposed Scheme (3/6)

10. Proposed Scheme (4/6) A central processing unit is the decision making centre and we call it energy management unit (EMU). The consumer may turn on any appliance at any moment irrespective of the peak hours concern and then HACS4EM suggests a convenient start time to the consumer.

11. Proposed Scheme (5/6) On switching the appliance on, a START-REQ packet is sent by the appliance to the EMU. Upon receiving the START-REQ packet, EMU corresponds with the storage system to inquire about the available stored energy by sending AVAIL REQ packet. EMU also communicates with smart meter to know about the updated prices.

12. Proposed Scheme (6/6) Proposed Algorithm

13. Simulation Results (1/9) We have used a scenario of five loads: a washer, a dryer, a dishwasher and a coffeemaker with energy consumption ratings of 0.89 kWh, 2.46 kWh, 1.19 kWh, 0.4 kWh respectively. An extra load has been supposed whose electricity consumption value varies randomly between 0 kWh and 4 kWh. 80% of the extra load is the miscellaneous load and the remaining 20% is of standby appliances.

14. Simulation Results (2/9) Time of Use pricing Peak Load Reduction Monetary Cost Reduction Performance of Wireless Sensor Home Area Network

15. Simulation Results (3/9) Peak load has been reduced because of the load shifting to the off peak hours.

16. Simulation Results (4/9) Monetary Cost Reduction: Time of Use (ToU) tariff. In ToU tariff, pricing rates are different for different hours. Water and Power Development Authority (WAPDA) charges 8.5 Rs/kWh in off peak hours and 13.2 Rs/kWh in peak hours. We have supposed peak hours from 8 AM to 2 PM and used the same rates as charged by WAPDA

17. Simulation Results (5/9)

18. Simulation Results (6/9) Performance of Wireless Sensor Home Area Network

19. Simulation Results (7/9) The overall performance of the network is affected by the packet size. The packet size of this application is varied between 32B and 128B. We assume here that the packets are generated at node at 10 min intervals

20. Simulation Results (8/9) Performance of Wireless Sensor Home Area Network

21. Simulation Results (9/9) Performance of Wireless Sensor Home Area Network