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EE5900: Advanced Embedded System For Smart Infrastructure Single User Smart Home. Smart Grid. Classical Power System v.s. Smart Grid. 3. The Classical Power System. 4. Smart Grid: Making Every Component Intelligent. Clean Reliable Secure Energy Efficient Money Efficient.
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EE5900: Advanced Embedded System For Smart Infrastructure Single User Smart Home
Smart Grid: Making Every Component Intelligent Clean Reliable Secure Energy Efficient Money Efficient
Smart Power Transmission and Distribution • More devices integrated such as IED, PMU, FRTU, FDR • Improved monitoring and control • Improved cybersecurity • Energy efficiency • Expense efficiency
Smart Community http://www.meti.go.jp 10
Smart Home • Smart home technologies are viewed as users end of the Smart Grid. • A smart home or building is equipped with special structured wiring to enable occupants to remotely control or program an array of automated home electronic devices. • Smart home is combined with energy resources at either their lowest prices or highest availability, e.g. taking advantage of high solar panel output. http://www.yousharez.com/2010/11/20/house-of-dreams-a-smart-house-concept/ 11
Smart Appliances • Smart Appliances Characterized by • Compact OS installed • Remotely controllable • Multiple operating modes 13
ZigBee Home Area Network (HAN) http://www.zigbee.org/ 15
Property 1: Dynamic Pricing from Utility Company Illinois Power Company’s price data Price ($/kwh) Pricing for one-day ahead time period 19
Property 2: Renewable Energy Resource • Marcelo Gradella Villalva, Jonas Rafael Gazoli, and Ernesto Ruppert Filho. Comprehensive Approach to Modeling and Simulation of Photovoltaic Arrays. IEEE Transactions on Power Electronics, Vol. 24, No. 5, May 2009 20
Benefit of Smart Home • Reduce monetary expense • Reduce peak load • Maximize renewable energy usage 21
Smart Home System Flow Power flow Internet Control flow 22
Smart Home Scheduling • Smart Home Scheduling • when to launch a home appliance • at what frequency or power level • The variable frequency drive (VFD) is to control the rotational speed of an alternating current (AC) electric motor through controlling the frequency of the electrical power supplied to the motor • for how long • use grid energy or renewable energy • use battery or not • Closely related to Demand Side Management • Demand Side Management is a top down approach • Smart Home Scheduling is a bottom up approach 23
End Start Dish washer 13:00 18:00 Landry machine 09:00 18:00 PHEV 18:00 08:00 AC 17:00 N/A …… 24
Electric Vehicles (EV) Powered by one or more Electric Motors 25
Plug-in Hybrid Electric Vehicles (PHEV) Powered by an Electric Motor and Engine • Internal combustion engine uses alternative or conventional fuel • Battery charged by outside electric power source, engine, or regenerative breaking • During urban driving, most power comes from stored electricity. Long trips require the engine 26
Charging of PHEV at Home • 2014 Honda Accord PHEV 120-volt: less than 3 hours 240-volt: one hour • 2013 Toyota Prius PHEV 120-volt: less than 3 hours 240-volt: 1.5 hours • 2014 Chevrolet Volt PHEV 120-volt: 10 – 16 hours 240-volt: 4 hours Using mobile connector 29 miles of range per hour charge The fastest way to charge at home 58 miles of range per hour charge 27
VFD Impact Powerr Power 3 cents / kwh 5 cents/kwh 3 cents / kwh 5 cents/kwh 10 kwh 5 kwh 1 2 3 1 2 Time Time (b) (a) cost = 5 kwh * 5 cents/kwh + 5 kwh * 3 cents/kwh = 40 cents cost = 10 kwh * 5 cents/kwh = 50 cents 28
Uncertainty of Appliance Execution Time and Energy Consumption • In advanced laundry machine, time to do the laundry depends on the load. How to model it? 29
Problem Formulation • Given n home appliances, to schedule them for monetary expense minimization considering multiple power level considering variations • Solutions for continuous VFD/power level • Solutions for discrete VFD/power level • Solutions for continuous VFD • Solutions for discrete VFD 1 2 3 4 30
The Procedure of the Our Proposed Scheme • Offline Schedule • A deterministic scheduling with continuous power level • A deterministic scheduling with discrete power level • Stochastic Programming for Appliance Variations • Online Schedule for Renewable Energy Variations 31
Linear Programming for Deterministic Scheduling with Continuous Power Level minimize: subject to: 33
Max Load Constraint To avoid tripping out, in every time window we have load constraint 34
Appliance Load Constraint Sum up in each time window appliance power consumption is equal to its input total power 35
Appliance Speed Limit and Execution Period Constraint The power is upper bounded Appliance cannot be executed before its starting time or after its deadline 36
Power Resource Power resource can be various 37
Solar Energy Distribution Constraint Solar Energy can be directly used by home appliances or stored in the battery 38
Battery Energy Storage Constraint and Charging Cost Solar Energy Storage Battery Charging Cost 39
Greedy based Deterministic Scheduling for Task i Task i Power 0 Time t1 t2 t3 t4 Price Time Cannot handle noninterruptible home appliances 41
Greedy based Deterministic Scheduling For Multiple Home Appliances • Appliances • Determine Scheduling Appliances Order An appliance • Schedule Current Home Appliance by Greedy Algorithm Not all the appliance(s) processed • Update Upper Bound of Each Time Interval All appliances are processed • Schedule 42
Dynamic Programming • Given a home appliance, one processes time interval one by one for all possibilities until the last time interval and choose the best solution 0 0 0 Choose the solution with total energy equal to E and minimal monetary cost 44
Characterizing • For a solution in time interval i, energy consumption e and cost c uniquely characterize its state 45
Pruning • For one time interval, (e1, c1) will dominate solution (e2, c2), if e1>= e2 and c1<= c2 46
Dynamic Programming based Appliance Optimization Power level: {1, 2, 3} Dynamic Programming returns optimal solution (6, 9) (5, 8) (4, 7) (4, 5) (3, 4) (2, 3) (3, 3) (2, 2) (1, 1) (5, 7) (4, 6) (3, 5) (3,6) (3,3) Price (2,4) (2,2) (1,2) (1,1) Time t2 (0,0) t1 (0,0) 0 47
Handling Multiple Tasks • According an order of tasks • Perform the dynamic programming algorithm on each task 48
DP based Deterministic Scheduling For Multiple Home Appliances • Appliances • Determine Scheduling Appliances Order An appliance • Schedule Current Home Appliance by DP Not all the appliance(s) processed • Update Upper Bound of Each Time Interval All appliances are processed • Schedule 49