1. EE5900: Cyber-Physical Systems
Renewable Energy

2. Community-level Solar Energy
All the customers in the building belong to the community and share the energy generated by the PV panel as a public resource. 2

3. Microgrid
A microgrid is a localized grouping of electricity generation, energy storage, and loads that normally operates connected to a traditional centralized grid. Microgrid generation resources can include fuel cells, wind, solar, or other energy sources. 3

4. Benefit of Renewable Energy Integration?
Mitigate the pressure of the peak generation.
Avoid pollution due to excessive generation.
Reduce the power flow of transmission and distribution system, ensure the security.

5. Challenges
Utility designs the predictive pricing. However, it only considers the electricity availability from utility.
Smart home scheduling (e.g., dynamic programming) only schedules the energy according to the predictive pricing. When renewable energy is available, how do smart home customers use it in smart home scheduling?
Suppose that the total available renewable energy is 100kWh, while the total energy demand is 200 kWh. How do we distribute the renewable energy resources?
After merging, cannot physically distinguish utility energy and renewable energy.
We can only virtually distribute them to reward customers, but how much energy/reward should be assigned to a customer? 5

6. New Idea
Design an effective and efficient smart home scheduling method to virtually distribute energy and the associated reward to each customer.
If an aggregator decides the energy distribution, it intends to minimize the community-wide monetary cost, while expecting the monetary cost of each customer is also reduced. 6

7. Model of Community-level Renewable Energy
𝑛∈𝑁 𝑤 𝑛,ℎ = 𝑊 ℎ
𝑤 𝑛,ℎ
Power Line
Data Line 7

8. Energy Consumption & Monetary Cost
Consume 𝐿 ℎ − 𝑊 ℎ
Pay 𝑎 ℎ 𝐿 ℎ − 𝑊 ℎ 2
Consume 𝑙 𝑛,ℎ − 𝑤 𝑛,ℎ
Pay 𝑎 ℎ 𝐿 ℎ − 𝑊 ℎ 𝑙 𝑛,ℎ − 𝑤 𝑛,ℎ 𝐿 ℎ − 𝑊 ℎ = 𝑎 ℎ 𝐿 ℎ − 𝑊 ℎ 𝑙 𝑛,ℎ − 𝑤 𝑛,ℎ
Power Line
Data Line 8

9. Problem Formulation Centralized min ℎ=1 𝐻 𝑎 ℎ 𝐿 ℎ − 𝑊 ℎ 2
Decentralized
For each customer 𝑛:
min ℎ=1 𝐻 𝑎 ℎ 𝐿 ℎ − 𝑊 ℎ 𝑙 𝑛,ℎ − 𝑤 𝑛,ℎ ⇓
min ℎ=1 𝐻 𝑎 ℎ 𝑙 𝑛,ℎ + 𝑙 −𝑛,ℎ − 𝑊 ℎ 𝑙 𝑛,ℎ − 𝑤 𝑛,ℎ
Constraint conditions for energy consumption are the same as before. 9

10. Constraints 𝑙 𝑛,ℎ = 𝑚∈ 𝐴 𝑛 𝑦 𝑚,ℎ 𝑦 𝑚,ℎ = 𝑥 𝑚,ℎ 𝑡 𝑚,ℎ 𝑥 𝑚,ℎ ∈ 𝑋 𝑚
𝑙 𝑛,ℎ = 𝑚∈ 𝐴 𝑛 𝑦 𝑚,ℎ
𝑦 𝑚,ℎ = 𝑥 𝑚,ℎ 𝑡 𝑚,ℎ
𝑥 𝑚,ℎ ∈ 𝑋 𝑚
ℎ= 𝛼 𝑚 𝛽 𝑚 𝑦 𝑚,ℎ = 𝐸 𝑚
𝑛: index of the customer
ℎ: index of the time slot
𝑚∈ 𝐴 𝑛 : index of the home appliances for customer 𝑛
𝑥 𝑚,ℎ ∈ 𝑋 𝑚 : power level of home appliance 𝑚 at time slot ℎ, which is the energy consumption per time slot
𝑙 𝑛,ℎ : total energy consumption of customer 𝑛 at time slot ℎ
𝐸 𝑚 : total energy consumption of home appliance 𝑚 for a given task
𝐶 𝑛,ℎ 𝑙 𝑛,ℎ : Total monetary cost in time slot ℎ for energy consumption 𝑙 𝑛,ℎ
𝛼 𝑚 and 𝛽 𝑚 : earliest start time and latest end time of home appliance 𝑚
𝑡 𝑚,ℎ : The actual working time of home appliance 𝑚 at time slot ℎ such that 𝑡 𝑚,ℎ =1 except for the last time slot. 10

11. Algorithmic Flow
Aggregator tentatively decides 𝑤 𝑛,ℎ for each customer 𝑛 No
Yes
Converge?
All customers solve the multi-customer smart home scheduling problem
End 11

12. How to decide 𝑤 𝑛,ℎ ?
Problem: Renewable energy is merged with conventional energy in the feeder such that it is impossible to know how much renewable energy is distributed to each one. However, we virtually distribute it through telling the customers how much energy they can use for free.
Solution: We seek for the 𝑤 𝑛,ℎ that could promote smart home scheduling. Since the relationship between renewable energy distribution and total monetary cost is not explicit, a cross entropy optimization based algorithm is proposed to solve this problem. 12

13. Experimental Setup Community: 500 customers
Time Horizon: 24 hours from this moment, divided into time 15-minutes slots.
𝑎 ℎ =0.0064$/ 𝑘𝑊ℎ 2 at any time slot.
Setup of home appliances is the same as last work
Belgian wind farm data is used to model renewable energy generation. 13

14. Wind Farm Data
Wind Power from 01/01/2014 to 01/05/2014, every 15 minutes, Forecast Error 9%
Scaled for 20% penetration 14

15. Background Energy 15

16. No Smart Home Scheduling16

17. Centralized Solution
$ over all the customers 17

18. Decentralized Solution
$ over all the customers 18

19. Energy Consumption During Cross Entropy Iteration19

20. Sell Energy Back to Grid
Home level renewable energy generation unit is encouraged such that customers could sell residual renewable energy back to the utilities.
Standard: Clarify how to connect renewable generation unit into the power grid.
Net Metering: Measure the power flow in both directions.
Selling Price: Partial the retail price or generation cost (varies in different locations).
Already applied in 27 states of U.S. 20

21. Net Metering
Net Meter
The power flow injected into the distribution network is measured by net meter as the selling back amount. 21

22. Making Smart Home Scheduling More Complex
PV panel
Power Line
Data Line 22