Generating energy that produces no greenhouse gas emissions from fossil fuels and reduces some types of air pollution. To reduce our daily to daily increasing electricity bill cost. Creating economic development and jobs in manufacturing, installation, etc.

1. ENERGY
MANAGEMENT
AND COST
OPTIMIZATION
USING
SOLAR ENERGY

2. SUVOJIT DEY
SUJAY BISWAS
SUDIPTA AMBAL
SOURAV MAHATA
SOUGATA MANDAL
Prof. NABANITA CHANDRA CHAKRABORTY
MENTOR
FINAL YEAR PROJECT
PRESENTED BY

3. INDEX
OUR AIM
ABOUT OUR PROJECT
WHY SOLAR ENERGY
ON-GRID SYSTEM
CLASSIFICATION OF LOADS
PROFIT OF SYSTEM OPERATOR
PROFIT OF PROSUMER
ALGORITHM & GRAPH OF PROSUMER'S ROI
CONCLUSION
REFERENCES
PV PANEL & INSTALLMENT COSTS
MONTHLY LOAD CONSUMPTION AND MONTHLY COSTS
LOAD CONSUMPTION OF 6 PROSUMER THROUGHOUT A
DAY
ALGORITHM FOR PROFIT OF SYSTEM OPERATOR
PROFIT OF SYSTEM OPERATOR IN VARIOUS SEASONS

4. OUR AIM
Generating energy that produces no
greenhouse gas emissions from fossil
fuels and reduces some types of air
pollution.
To reduce our daily to daily increasing
electricity bill cost.
Creating economic development and
jobs in manufacturing, installation, etc.

5. ABOUT OUR PROJECT
In this project, we use self-produced solar energy
instead of conventional energy. Thereby we can manage
our daily energy consumption. And we can significantly
reduce the electricity cost so that we will return our
investment on PV panels installation, in a few years.
Here we use Matlab Software to calculate the profit of
the System operator and Prosumers.
A System operator is proposed which decides the
operation strategy of the grid as per the total energy
the demand of the end-users.
PV Prosumers are the end-users well equipped with
PV systems on the rooftop. The prosumers can act as
both load and supply of electricity to the grid.

6. WHY SOLAR ENERGY
COST
ADVANTAGE
AFFORDIBILITY
CLEAN
ENERGY
GOVT.
SUPPORT
10-30%
AVAILABILITY
30%

7. ON GRID SYSTEM

8. CLASSIFICATION OF LOAD
LOAD
ELECTRICAL
LOAD
HEAT
LOAD
FIXED
LOAD
VARIABLE
LOAD
COOLING
LOAD
TUBELIGHT
BULB
FAN
FRIDGE
IRON
GEYSER WATER CHILLER
TV
WATER PUMP
WASHING MACHINE
DESKTOP/LAPTOP
CHIMNEY

9. In 24 hours In 6am-5pm
Buildings
no.
1
2
3
4
5
6
291.14kw
322.64kw
303.12kw
315.23kw
337.32kw
277.48kw
153.62kw
149.42kw
130.56kw
164.44kw
117.62kw
115.26kw
Monthly Load
Consumption
Monthly Cost
According to
WBSEDCL
Buildings
no.
1
2
3
4
5
6
According to
CESC
1742
1965
1824
1911
2071
1652
1960
2227
2053
2161
2358
1863

10. 6
A
M
-
1
0
A
M
1
0
A
M
-
2
P
M
2
P
M
-
6
P
M
6
P
M
-
1
0
P
M
1
0
P
M
-
2
A
M
2
A
M
-
6
A
M
60
40
20
0
6
A
M
-
1
0
A
M
1
0
A
M
-
2
P
M
2
P
M
-
6
P
M
6
P
M
-
1
0
P
M
1
0
P
M
-
2
A
M
2
A
M
-
6
A
M
50
40
30
20
10
0
Fixed load consumption
throughout a day
1st Building
2nd Building
3rd Building
4thBuilding
5th Building
6th Building
Variable load consumption
throughout a day

11. PV Panel
PV Panel Installation Cost
A solar panel, or PV module, is an assembly of photovoltaic cells mounted in a
framework for installation. The most efficient mass-produced solar modules
have power density values of up to 175 W/m^2 (16.22 W/ft^2). A rooftop
photovoltaic power station, or rooftop PV system is a photovoltaic (PV) system
that has its electricity-generating solar panels mounted on the rooftop of a
residential or commercial building or structure. 1 kW of PV Panel produces
4kWh of energy in a day
Here we use 2 kW of PV panel to produce our own energy. We use 5 PV
panels of 375w each. The price of a 2kW PV panel is approx 1,36,800/- in
India.

12. Hardware
25%
Marketing & Sales
20%
Other cost & margin
20%
Overhead
20%
Labor
10%
Permits
5%

13. 1. Set System Operator selling & buying price to and from prosumer denoted as p_ms & p_mb respectively.
2. Take input the value of energy consumption hour slot-wise denoted as EC.
3. Set solar power generation output hour slot wise denoted as sg.
4. Calculation of total selling price and buying price
5(a). if(net load>0) then
profit= [(p_mb * EC) - (p_ms * (sg-EC))]
(b). else
profit= [(p_ms * (sg-EC)) -(p_mb * EC)]
(c). End if
6. Calculation of system operator's profit in each time slot.
7. Plot profit vs time slot
ALGORITHM FOR PROFIT OF SYSTEM OPERATOR

14. System operator's profit in summer

15. System operator profit in Monsoon

16. System operator profit in Winter

17. 1. Set electricity cost without PV
2. Set electricity cost with PV
3. Set PV panel installation cost
4. Increment electricity cost according to CHP
5. Calculate the next 10-year electricity cost
6(a). for(i=pv_cost,i--,i=0)
pv_cost=pv_cost-electricity cost
(b) End for
7. Calculate ROI=pv_cost/electricity cost
8. Plot electricity cost with PV and electricity cost without PV
9. Plot ROI
ALGORITHM FOR RETURN ON INVESTMENT

18. Return On Investment of Prosumer

19. Cost reduce of Prosumer after PV installation
Before PV installaion
17584 6601
After PV installaion
Buildings
no.
1
2
3
4
5
6
19912 8795
18466 8283
19342 7238
21038 10546
16696 7804

20. Profit of System operator
Before PV installaion
14794
After PV installaion
Buildings
no.
1
2
3
4
5
6
13785 23845
25102
12560 22423
13346 23372
14456 24057
11620 21556

21. CONCLUSION
In this project, We calculate how we can reduce our electricity costs
after installing PV panels. This is a very good approach for reducing the
daily electricity cost. Switching to solar energy in the forms of solar
heaters and solar cookers are some ways to reduce the usage of
conventional loads, Besides by using solar energy we can come out
from conventional power supply. In this way, we can save our thermal
energy or coal. Profit of System operator it is depicted that the
proposed methodology generates more profit with respect to the
existing models. The Prosumer earns savings during the daytime when
they are connected with PV sources on the rooftop whereas at night
with PV not generating energy there is no saving.

22. REFERENCES
[1] N. Chakraborty, A. Naskar, A. Ghosh, S. Chandra, A. Banerji, and S. K. Biswas,
"Multi-Party Energy Management of Microgrid with Heat and Electricity
Coupled Demand Response," 2018 IEEE International Conference on Power
Electronics, Drives and Energy Systems (PEDES), 2018, pp. 1-6, DOI:
10.1109/PEDES.2018.8707689.
[2] J. Li, L. Wu et al., “Optimal operation for community-based multiparty
microgrid in grid-connected and islanded modes,” IEEE Transactions on Smart
Grid, vol. PP, no. 99, pp. 1–9, 2016.
[3] M. H. Cintuglu, H. Martin, and O. A. Mohammed, “Real-time implementation
of multiagent-based game theory reverse auction model for microgrid market
operation,” IEEE Transactions on Smart Grid, vol. 6, no. 2, pp. 1064–1072, 2015.
[4] https://en.wikipedia.org/wiki/Solar_panel
[5] https://en.wikipedia.org/wiki/Grid-connected_photovoltaic_power_system

23. THANK YOU