Power Calculations for a Single House Complex

Introduction

This project focuses on a single house complex comprising 96 houses, predominantly used as summer residences. However, with an increasing trend of families deciding to stay all year round, an analysis of the power consumption throughout the year was necessitated.

Power Calculations

In this project, a single house complex which contains 96 houses has selected. Most of the owners use their house in this complex as a summer house but every year 2 or 3 family decide to stay in the complex for 12 months.

Due to this event, calculations were made through the power analysis of a house which has the family stays there for 12 months.

Table 1. Monthly energy usage of a house in kWh

Month	2015	2016	2017	Maximum
January	168	165	128	168
February	110	131	116	131
March	76	143	118	143
April	139	108	159	159
May	114	115	130	130
June	148	178	130	178
July	129	124	137	137
August	142	143	142	143
September	118	123	158	158
October	133	121	97	133
November	125	111	109	125
December	100	126	119	126

As we can see in the table above, these are the energy usages of a house by months. The maximum energy usage of this complex calculated by months:

E_complex= E_house x 96

E_complex : Monthly energy usage of complex (only house based)

E_house : Monthly energy usage of a house

Table 2. Monthly maximum energy usage of single house complex in kWh

Month	2015	2016	2017	Maximum	total_max
January	168	165	128	168	16128
February	110	131	116	131	12576
March	76	143	118	143	13728
April	139	108	159	159	15264
May	114	115	130	130	12480
June	148	178	130	178	17088
July	129	124	137	137	13152
August	142	143	142	143	13728
September	118	123	158	158	15168
October	133	121	97	133	12768
November	125	111	109	125	12000
December	100	126	119	126	12096

The daily average energy usage of the complex calculated as:

E_((daily)_complex ) =E_complex/30

E_((daily)_complex ) : Daily energy usage of the complex (only house based)

E_complex : Monthly energy usage of complex (only house based)

Month 2015 2016 2017 Maximum total_max daily_tot_max

Table 3. Daily maximum energy usage of single house complex in kWh

Month	2015	2016	2017	Maximum	total_max	daily_tot_max
January	168	165	128	168	16128	537.6
February	110	131	116	131	12576	419.2
March	76	143	118	143	13728	457.6
April	139	108	159	159	15264	508.8
May	114	115	130	130	12480	416
June	148	178	130	178	17088	569.6
July	129	124	137	137	13152	438.4
August	142	143	142	143	13728	457.6
September	118	123	158	158	15168	505.6
October	133	121	97	133	12768	425.6
November	125	111	109	125	12000	400
December	100	126	119	126	12096	403.2

These values show the daily maximum energy usage of the complex only for the houses. But there are some other elements in the complex use energy aswell. For example; there are a small waste water treatment system, an irrigation motor, a pool and street lights. These are cathegorized with “other”.

Table 4. Daily energy usage of other elements by months in kWh

Month	2015	2016	2017
January	159.0488	175.8065	79.37788
February	32.21043	129.7619	81.8555
March	92.06782	126.0292	65.22504
April	98.04274	89.6381	59.25317
May	75.38462	99.91551	41.48233
June	123.0171	34.48889	37.88889
July	222.0347	210.1075	205.53
August	261.0008	165.384	374.8464
September	204.34188	142.06349	114.14286
October	179.4872	121.3441	163.3871
November	166.39316	56.230159	95.468254
December	137.6923	114.9155	127.4424

The energy usage of other elements in the system by months shown in the table above. As we can see it in the table above; the peak of the power is mostly seen in the summer times because of the irrigation motor and pool. Motor for irrigation is used from second half of may to end of the first half of the september. Pool is open from start of june to second half of september.

Table 5. Daily maximum energy usage of other elements by months in kWh

Month	2015	2016	2017	Max
January	159.0488	175.8065	79.37788	175.8065
February	32.21043	129.7619	81.8555	129.7619
March	92.06782	126.0292	65.22504	126.0292
April	98.04274	89.6381	59.25317	98.04274
May	75.38462	99.91551	41.48233	99.91551
June	123.0171	34.48889	37.88889	123.0171
July	222.0347	210.1075	205.53	222.0347
August	261.0008	165.384	374.8464	374.8464
September	204.34188	142.06349	114.14286	204.34188
October	179.4872	121.3441	163.3871	179.4872
November	166.39316	56.230159	95.468254	166.39316
December	137.6923	114.9155	127.4424	137.6923

The rest of the calculations are made with highest values from the table. Daily total energy usage of the complex is calculated by ;

E_((complex)_total )= E_(((daily〗_total)_max )+ E_((other)_daily )

E_((complex)_total ) : Total energy usage of single house complex

E_(((daily)_total)_max ) : Daily total maximum energy usage of complex (only house based)

E_((other)_monthly ) : Daily energy usage of other elements of complex

Table 6. Daily energy usage of single house complex by months in kWh

Month	Others	Houses	Total
January	175.8065	537.6	713.4065
February	129.7619	419.2	548.9619
March	126.0292	457.6	583.6292
April	98.04274	508.8	606.8427
May	99.91551	416	515.9155
June	123.0171	569.6	692.6171
July	222.0347	438.4	660.4347
August	374.8464	457.6	832.4464
September	204.3419	505.6	709.9419
October	179.4872	425.6	605.0872
November	166.3932	400	566.3932
December	137.6923	403.2	540.8923

These values shows the daily total energy usage of the complex by months.

Calculation of Photovoltaic Panel Size

Photovoltaic panel size can be calculated with these values:

C_pv= E_consumed/(t_solar x P_pv )

C_pv : Size of photovoltaic panels

E_consumed : Consumed energy of the system

t_solar : Sunshine duration

P_pv : Maximum power output of photovoltaic panel

But this formula can be calculated if the efficiency of the panel is 100%. In reality, photovoltaic panels affected by soiling of panels, wiring losses, shading, etc. to indicate to what photovoltaic panel may be stressed/ used in such conditions, a factor, known as derating factor, is specified. Derating factor is between 95% - 80% for photovoltaic panels. In this project, derating factor of photovoltaic panel selected as 85%.

Table 7. Daily required energy from PV panels by months in kWh

Month	E_total	E_pv
January	713.4065	839.3018
February	548.9619	645.8375
March	583.6292	686.6226
April	606.8427	713.9326
May	515.9155	606.9594
June	692.6171	814.8436
July	660.4347	776.982
August	832.4464	979.3487
September	709.9419	835.2258
October	605.0872	711.8673
November	566.3932	666.3449
December	540.8923	636.3439

Formula for calculating the size of photovoltaic panel is:

C_pv= E_required/(t_solar x P_pv x derating factor)

C_pv= E_required/(t_solar x P_pv x 0,85)

PLM-250M-60 photovoltaic panel from Perlight Company has been chosen in this project. It is a monocrystaline photovoltaic panel and maximum power of the photovoltaic panel is 250 watts.

Table 8. Technical specifications for PerlghtPLM-250M-60 PV Panel

Technical Specification	Value
Model	PLM-250M-60
P_max (Maximum Power)	250 W
V_mp (Voltage at Maximum Power)	30.5 V
I_mp (Current at Maximum Power)	8.2 A
V_oc (Open Circuit Voltage)	38 V
I_sc (Short Circuit Current)	8.78 A
Maximum System Voltage	1000 V dc
NOTC (Nominal Operating Cell Temperature)	45℃ ± 2℃
Temperature coefficient of I_sc	0.06 %/℃
Temperature coefficient of V_oc	-0.34 %/℃
Temperature coefficient of P_max	-0.45 %/℃
Power tolerance	0 / +3%
Working temperature	-40 ℃ to 85℃

This project is planned to be photovoltaic heavy hybrid system. Thus; most of the power will be generated by photovoltaic panels and the rest of the power will be generated by bio generator.

Calculation results by months are below:

Table 9. Size of PV Panels by months

Month	Size of PV Panels
January	668
February	428
March	388
April	351
May	244
June	398
July	293
August	382
September	344
October	367
November	434
December	530

The photovoltaic panel size has been chosen 350. In table 9 in may, it can be seen only 244 panel should be enough for whole complex. The datas from last 3 years show, energy usage of complex had the lowest value in may every year. According to the old head of that community, in may, electricity provider company making some maintenance on the transmission lines. Because of that, they cut off the electricity. Sometimes this complex didn’t get electricity for 48 hours in this process.

Biogas System

Two renewable energy resources selected in hybrid energy system part of this project. Photovoltaic system and small biogas power plant.

Biogas produced from biological waste in the digester.Biological process named anaerobic digestion heppens in the digestor then produced gas send it to the Desulphurization unit. Desulphurizedbiogas send to the gas engine to create electricity.The rest of the waste left in the digester contains rich elements such as potassium, nitrogen, iron, phosphorous, etc. Because of this, treated waste send to transition pond to create fertilizer.

Table 10. Biogas kits and their costs in Clever-Ferm-Kit

Kit	Power (kW)	Diameter of digester (m)	Volume of Digester (m3)	Total Cost (Euro)
BO K30	30	9.45	320	230,000
BO K50	50	12.89	600	305,000
BO K75	75	12.89	800	350,000
BO K100	100	16.33	1000	380,000

Maximum Power Point Tracker Charger for Batteries

Output of the photovoltaic system can be different time to time because it depends on weather conditions. Therefore maximum power point tracker must be used if maximum power is required from the system. MPPT charger is a must for this kind of systems. For battery charger unit; the maximum power point tracker charger unit and string calculator tool from Morningstar Company used in this project. First of all; manufacturer and model of photovoltaic panel has been selected in the PV Module. Then the mppt charger of morningstar selected. After that; the rest of the information of system entered in the required areas.

Calculation of Battery Sizing and Inverter

For this system; deep-cycle batteries recommended because deep-cycle batteries are specifically designed for to be discharged to low energy level and rapid recharged or cycle charged/discharged day after day. The battery should be large enough to store sufficient energy to operate the appliences at night and cloudy days.

The battery size of the system depends on ;

• daily energy usage
• depth of discharge
• battery loss
• nominal battery voltage
• days of autonomy

Battery system capacity (Ah)= (daily energy usage x days of autonomy)/(battery loss x depth of discharge x nominal battery voltage)

Depth of discharge is defined as capacity in ampere hours that is discharged from a fully charged battery, divided by battery nominal capacity. Depth of discharge is a method to indicate battery’s state of charge. In this method; %100 means empty and %0 means full. There is a correlation between depth of discharge and cycle life of battery in some battery technologies such as lead acid type of batteries. The recommended depth of charge is 70%.

Days of autonomy is chosen 1 day because of the maintenance or other problems in system.

Nominal battery voltage is 12 voltage.

Battery loss depends on many factors related to battery. It is between 80% - 90% for lead acid type of batteries. In this system it is chosen 85%.

Three different capacity of batteries (100 Ah, 150 Ah and 200 Ah) compared for economical analysis by months.

Table 11. Size of battery system for 100 Ah, 150 Ah and 200 Ah

Month	100 Ah	150 Ah	200 Ah
January	799,335	532,89	399,675
February	615,0814	410,0556	307,5417
March	653,9263	435,9508	326,9631
April	679,93584	453,29056	339,96792
May	578,0566	385,3711	289,0283
June	776,04156	517,36104	388,02078
July	739,9829	493,3219	369,9915
August	932,713	621,8087	466,3565
September	795,45309	530,30206	397,72654
October	677,9688	451,9792	338,9844
November	634,6142	423,0761	317,3071
December	606,0418	404,02787	303,0209

8 batteries from 4 different producers in Turkey has been compared.

Table 12. Batteries and their costs

Producer	Capacity (Ah)	Price (Euro)
YIGITAKU	100	274,7663551
ORBUS	150	208,5669782
SOYTURK	150	225,8411215
ORBUS	100	144,2352025
SOYTURK	100	151,8535826
Ttec	100	230,3582555
SOYTURK	200	249,0654206
ORBUS	200	294,2367601

If the calculation for price per ampere-hour, than it has been clearly seen which battery has low price.

Producer Capacity (Ah) Price (Euro) Price per Ampere-hour

Table 13. Batteries and their price per ampere-hour

Producer	Capacity (Ah)	Price (Euro)	Price per Ampere-hour
YIGITAKU	100	274,7663551	2,7476636
ORBUS	150	208,5669782	1,3904465
SOYTURK	150	225,8411215	1,5056075
ORBUS	100	144,2352025	1,442352
SOYTURK	100	151,8535826	1,5185358
Ttec	100	230,3582555	2,3035826
SOYTURK	200	249,0654206	1,2453271
ORBUS	200	294,2367601	1,4711838

200 Ah battery from SOYTURK company.

Battery size of the system calculated by:

Battery size= (Battery energy storage system capacity)/(Capacity of a single battery)

Table 14. Battery Size by month

Month	Battery Size
January	400
February	308
March	327
April	340
May	290
June	389
July	370
August	467
September	398
October	339
November	318
December	304

The maximum power from photovoltaic panels is 87,5 kW. Inverter should be withstand 1,2 - 1,3 times of the total power of the panels. That means; inverter should be withstand 113,7 kW power for this system. Two 80 kW inverters has been chosen for this project. The rated DC voltage input of this inverter is 384 volts. That means 32 batteries should be lined to get the rated input voltage for inverter to convert it to 380 (phase to phase) volts AC. The total battery size has been chosen 352 for this project.

Table 15. Total cost of the system

Components	Quantity	Price per Component	Total Cost
PV Panels	350	€305.4	€106,890
Batteries	352	€250	€88,000
Inverter	2	€26,700	€53,400
Biogen System	1	€305,000	€305,000
MPPT Chargers	39	€533.11	€20,791.29
Area	5	€100,031.5	€500,157.5
Additional costs	-	-	€100,000
Total	-	-	€1,174,239

Procedures for Producing Energy From Hybrid System in Turkey

Procedures for getting licence:

1. Establishment of a company for electricity generation according to the Turkish Commercial Code
2. Obtain the right of use by the company for the location of the wind or solar measurement stations according to the type of facility in the field where the project will be developed.
3. Installation of wind or solar measuring stations
4. Approval of the red Measurement Station Installation Report Mete prepared by the General Directorate of Meteorology or the accredited bodies prepared for the measurement stations established
5. Submission of at least one year measurement data to the General Directorate of Meteorology or Accredited organizations
6. Approval of Measurement Result Report by the General Directorate of Meteorology or Accredited Institutions after 1 year
7. Preparation of the application information and documents announced by the Electricity Market Licensing Regulation and EMRA Board Decisions
8. Application of an associate degree on the dates announced by EMRA Board Decisions
9. Preliminary examination of the application for associate degree by EMRA
10. Technical evaluation by YEGM of the applicants whose preliminary examination is approved
11. Submission of the Technical Evaluation Final Report prepared by YEGM to EMRA for those whose technical evaluation is deemed appropriate
12. Completion of the competition process by TEIAS for technical evaluation and applications in the same region
13. Submission of the application by TEIAS to EMRA by paying the maximum fee for the unit MW installed power
14. Awarded by the EMRA to the Company that won the competition
15. In the process of associate degree, the company obtains all administrative permissions for the establishment of the facility and processing of the facility to the development plans.
16. Licensing of the Company by MENR
17. Approval of the projects by the organizations authorized by the MENR or the MENR
18. Completion of construction and installation
19. Acceptance of the facility by organizations authorized by MENR or MENR
20. Commercial company

Summary and Conclusions

In this thesis, I tried to solve some problems for a single house complex. This complex had some energy shortages in time and each year more families deciding to stay in the complex. This creates more demand in the future and if energy shortages keeps going with that; then this complex will face a huge energy problem when all of the houses filled with families.

Nowadays; renewable energy sources and energy production from these sources are popular. The conventional power plants damage the environment badly and these power plants depend on the resources which is limited. Thus we need to use the renewable energy sources to produce energy to lower the damage to environment. But renewable energy sources are depends on the weather conditions. That means electricity production is unstable for these kind of technologies. But scientists are finding new solutions these problems, such as maximum power point tracker is used for getting maximum power from the photovoltaic panels or wind turbines. It will be better if these systems supported by storage systems as well. These kind of hybrid systems will be the solution for the future.

There are some villages which they have farmlands and diaries close to the complex. That brings easy access to the biological wastes and because of the location of this complex, it can get so much solar radiation from the sun and location has long sun durations. Solution for this complex is off-grid hybrid energy system.

All of the components are chosen from commercial equipments on the internet. It is possible to get better equipment when contacted with better producers. It can be make the system more efficient. Contact with the universities for better results for optimum photovoltaic panel angle, exact solar radiation and biomass analysis for Iskenderun District. That makes better analysis for photovoltaic system and biogas power plant.