1. Development of a Smart Advisor
for the optimized energy usage
in a Smart Grid Node at Fortiss
Cheng Zhang
Supervisor: PD Dr. rer. nat. habil. Bernhard Schätz

2. Outline
• Motivation
• Problem Statement
• Approach
• Result
• Conclusion & Future Work
2
* Smart Grid node (fortiss smart energy living lab)

3. Motivation
1. Inefficient usage of storage
2. Storage usage in different price models (static/dynamic)
3. Maximize the financial benefits of storage
Implement the advisor for storage usage in the fortiss smart
energy living lab.
3

4. Problem Statement
• Reduces Cost
• Increases Revenue
• Advises to charge/ discharge battery
based on prices, node connection and energy generation
and consumption data
Scenarios
• Non-Export Scenario
• Sell Renewable Scenario
• Sell Storage Scenario
• Sell Energy Scenario
4
Schema of the smart energy living lab

5. Problem Statement
• Reduces Cost
• Increases Revenue
• Advises to charge/ discharge battery
based on prices, node connection and energy generation
and consumption data
Scenarios
• Non-Export Scenario
• Sell Renewable Scenario
• Sell Storage Scenario
• Sell Energy Scenario
4
Schema of the smart energy living lab
Power flow in sell energy scenario

6. Problem Statement
4
Power flow in sell energy scenario

7. Approach
Purpose: Match energy demand at intervals with high energy
price to energy supply at intervals with low energy price.
Restrictions
• Chronological order (of intervals)
• Limited capacity of battery
Greedy Algorithm
• Candidate Set(Remaining unused intervals)
• Selection function(Choose the locally optimal choice at each
stage)
5

8. Preparation based on Price Periods
6
* Price Period is a period that prices at all consecutive intervals in this period are
the same.

9. EnergyWh
-6000
-30000
3000
6000
2014-09-04 00:00:00 2014-09-04 07:45:00 2014-09-04 15:30:00 2014-09-04 23:15:00
Max Demand (Wh) Least Supply (Wh) Max Supply (Wh)
Price€ct/kWh
0.00
7.50
15.00
22.50
30.00
Energy Demand/Supply at intervals
Preparation based on Price Periods
6
* Price Period is a period that prices at all consecutive intervals in this period are
the same.
Time

10. EnergyWh
-6000
-30000
3000
6000
2014-09-04 00:00:00 2014-09-04 07:45:00 2014-09-04 15:30:00 2014-09-04 23:15:00
Max Demand (Wh) Least Supply (Wh) Max Supply (Wh)
Price€ct/kWh
0.00
7.50
15.00
22.50
30.00
Energy Demand/Supply at intervals
Preparation based on Price Periods
6
* Price Period is a period that prices at all consecutive intervals in this period are
the same.
Time

11. EnergyWh
-6000
-30000
3000
6000
2014-09-04 00:00:00 2014-09-04 07:45:00 2014-09-04 15:30:00 2014-09-04 23:15:00
Max Demand (Wh) Least Supply (Wh) Max Supply (Wh)
Price€ct/kWh
0.00
7.50
15.00
22.50
30.00
Energy Demand/Supply at intervals
Preparation based on Price Periods
6
* Price Period is a period that prices at all consecutive intervals in this period are
the same.
Time

12. EnergyWh
-10000
-50000
5000
10000
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Max Demand (Wh) Least Supply (Wh) Max Supply (Wh)
Price€ct/kWh
0.00
7.50
15.00
22.50
30.00
Energy Demand/Supply in Price Periods
Preparation based on Price Periods
6
* Price Period is a period that prices at all consecutive intervals in this period are
the same.

13. Selection function
The selection of next locally optimal choice based on the
candidate set and the current situation reflected by the pool.
7
*The pool at each stage stores the current capacity of battery at the beginning and
the end of each price period based on previous choices.
CapacityWh
0
2500
5000
7500
10000
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Max Capacity Final Pool
Pool at the final stage

14. Solution
The final solution of the greedy algorithm used in the advisor
consists of battery exchanges in each price period.
8
EnergyWh
-10000
-50000
5000
10000
Price€ct/kWh
0.00
7.50
15.00
22.50
30.00
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
RTP Price Final Exchange
Battery exchange in price periods

15. Result
9
PowerWatt
-30000
-20000
-100000
10000
20000
30000
40000
2014-09-04 00:00:00 2014-09-04 07:45:00 2014-09-04 15:30:00 2014-09-04 23:15:00
Consumption Generation From Grid To Grid
Charging Discharging Wastage
Price€ct/kWh
0.00
7.50
15.00
22.50
30.00
Optimized Schedule in a day
* The optimized schedule depends on input intervals
Time

16. Evaluation
10
Cost€
0471114
Price€ct/kWh
0.00
7.50
15.00
22.50
30.00
2014-09-04 00:00:00 2014-09-04 07:15:00 2014-09-04 14:30:00 2014-09-04 21:45:00
Price Non-optimized Cost Optimized Cost
Comparison with non-optimized cost
* The cost curve increases at 6:00 and 14:00 for charging energy
* The cost curve declines at 12:00 and 17:00 for consuming stored energy
Time

17. Evaluation
10
Cost€
0471114
Price€ct/kWh
0.00
7.50
15.00
22.50
30.00
2014-09-04 00:00:00 2014-09-04 07:15:00 2014-09-04 14:30:00 2014-09-04 21:45:00
Price Non-optimized Cost Optimized Cost
Comparison with non-optimized cost
* The cost curve increases at 6:00 and 14:00 for charging energy
* The cost curve declines at 12:00 and 17:00 for consuming stored energy
Time
Charging Discharging

18. Conclusion & Future Work
The smart advisor generates an optimized schedule based on
consumption, generation and energy price in a short term
future (24 hours currently) through a greedy algorithm.
Future Work
• Optimize the greedy algorithm
• Involve more connection modes
• Enhance load-shifting optimization for unused power
(Profiles of Electrical Devices)
11

19. Q & A
Thanks!
12

20. Background

21. Demand Power
• Consumption
(Reduce Cost)
• Power to the grid
(Increase Revenue)
14
Supply Power
• Generation
(Free/Energy Price)

22. Maximum Demand Power
PDemand
Max = PLine
Max + PConsumption - PGeneration
Scenarios
• PDemand
Max = PConsumption - PGeneration
• PDemand
Max = PConsumption - Max(0, PGeneration - PLine
Max)
• PDemand
Max = PLine
Max + PConsumption - PGeneration
• PDemand
Max = PConsumption - PGeneration < 0 ?
PConsumption - PGeneration :
PLine
Max + PConsumption - PGeneration
* If PDemand
Max < 0, there is no power demand.
15

23. Maximum Supply Power
PSupply
Max = PLine
Max - PConsumption
PSupply
Least = -Min(0, PDemand
Max)
* PSupply
Least is the unused power.
16

24. Demand Energy from the Battery
PDemand
Max = Min(PDemand
Max, PBat_dch
Max)
EDemand
Max × ηdch = PDemand
Max × TDuration
* EDemand
Max is the energy actually be used in the battery.
17

25. Supply Energy to the Battery
PSupply
Max = Min(PSupply
Max, PBat_ch
Max)
ESupply
Max = PSupply
Max × TDuration × ηch
* ESupply
Max is the energy actually be stored in the battery.
18

26. Financial Benefit
Benefit = (PriceHigher ÷ PriceLower) × ηch × ηdch
If Benefit > 1, there is financial benefit by using energy, which
is supplied in the price period (PriceLower), in the price
period (PriceHigher).
* ηch is the charge efficiency of battery.
* ηdch is the discharge efficiency of battery.
19

27. Circuit Diagram
20
Circuit Diagram in the fortiss smart energy living lab

28. Decision Path
21
* Depth represents the depth level of the recursion in the algorithm.
* Number above the arrows represents the stage number.
* Red nodes represent demand price period and the number represents the sequence.
* Orange nodes represent supply price period.
* Red horizontal arrow represents the final solution.

29. Decision Path
21
* Depth represents the depth level of the recursion in the algorithm.
* Number above the arrows represents the stage number.
* Red nodes represent demand price period and the number represents the sequence.
* Orange nodes represent supply price period.
* Red horizontal arrow represents the final solution.

30. Performance
22
Effect = (CostNop - CostOp) / CostNop
0.00%
27.50%
55.00%
82.50%
110.00%
10000 20000 30000 50000 60000 150000
17.77%
32.53%
45.80%
91.14%
106.79% 106.79%
26.27%
39.41%
44.84%
48.74% 48.74%
Senario 1 Senario 3

31. Energy Demand / Energy Supply in Price Period
23
EnergyWh
-10000
-50000
5000
10000
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Max Demand Least Supply Max Supply
Price€ct/kWh
0.00
7.50
15.00
22.50
30.00
Energy Demand/Supply in Price Periods in non-export scenario