Design and analysis of a grid-connected hybrid power system with constant supply for Patenga, Bangladesh

Abstract

A quickly growing nation like Bangladesh is experiencing scarcity of efficient electricity production system. Upgrade of the electricity production system is required to keep the progress of the nation uninterrupted. Keeping this motto into consideration, in this research, a grid-connected hybrid system model has been identified to overcome the shortage of electricity in Bangladesh with the combination of photovoltaic, wind turbines, diesel generator for remote and upgrade areas. Photovoltaic and wind turbines are used as a main primary source and the diesel generator is kept as a standby source to fulfil our target. The proposed system is mainly the renewable energy-based plant because it is environmentally friendly with less emission carbon as well as other greenhouse gases, as well as the system is controlled by the programmable logic controller for supplying constant electricity. For design, optimization and grid connection, Patenga beach, Chittagong, Bangladesh has selected where resources are generally usable. Finally, it has been found that the cost of electricity scheme becomes as low as $0.12/kWh compared to the quick rental plant (around $0.33/kWh) in Bangladesh.

Keywords:

• hybrid system
• photovoltaic
• wind energy
• diesel generator
• grid connection
• PLC

PUBLIC INTEREST STATEMENT

Referable to the shortage of conventional fuels, the rising quantity of fuel costs and environmental danger from fossil fuels, the conventional power generation is becoming unsustainable at this moment. Therefore, renewable energy such as sun, wind, geothermal, ocean, and biomass-based power generation is the best selection for Alternative power generation in the world-wide due to environmental matters and cost-effectiveness. On the other hand, Energy managements are the major concern for proper effectiveness. Control units are of the major elements of these journeys for the sustainable system. The main objective of this research is a cost-effective grid-connected hybrid power system which is proposed to meet the national electricity demand in Bangladesh, as well as a control system is optimized for supplying continuous power.

1. Introduction

Since the beginning of the twenty-first century, energy demand is rapidly increasing which is estimated to increase by 56% from 2010 to 2040. Even though, the nuclear power plants being capable of yielding a huge amount of power. However, due to the dangers associated with this plant makes electricity production risky. More than half of the power plants in Bangladesh which is estimated about are natural gas-based (Kabir et al., 2016). Current overuse will exhaust the natural gas within 6–7 years if we fail to discover any new natural gas field (Kabir et al., 2015). Under this severe circumstance, the Bangladesh Government is planning for various measures to meet the challenge. The oil-based quick rental project is one of the outcomes of such measures. Per-unit cost of this project is huge and it is about 26 BDT (Kabir et al., 2018). It creates a lot of bad effects on the economy and environment in Bangladesh. Currently, our generation is about 9500 MW (Bangladesh Power Development Board [BPDB], 2018). In 2030, the electricity demand will be 34,000 MW (Kabir, Matin, Amin et al., 2017). Bangladesh cannot sustain a quick rental power plant project for a long time. So, it has become inevitable for us to create a different scope of producing electricity to fulfil the demand. For instance, the government has taken to establish various power plants which are non-renewable; such as oil, gas, coal-based plants, and many more. In addition, the government has taken steps to establish a 1000 MW nuclear power plant at Ruppur. However, nuclear power needs a huge technological safety. If any kinds of disaster happen, it is very difficult for a country like Bangladesh to handle it because of lack of technical ability. Government has taken steps to establish 1320 MW thermal coal-fired plant in Rampal and 1200 MW plant in Moheshkhali; also, 1200 MW plant in Baskhali (Kabir & Matin Bhuiyan, 2017). It is also harmful to our nature. For this reason, to ensure energy security without any environmental impacts, it is important to create unconventional energy sources. Due to the shortage of fossil fuels and the limitations of using natural gas, Bangladesh has a vast potential for renewable energy because 72% are rural areas (Baky et al., 2017). A huge amount of sunlight during the day is a great blessing for Bangladesh as it contributes to a yearly average of about 4.5 kWh/m²/day (Billah et al., 2017).

In Patenga, annual average solar radiation is 4.63 kWh/m²/day, and annual average wind speed is 3.10 m/s (Bangladesh Meteorological Department, 2016; NASA surface meteorology and solar energy, 2018). Therefore, the hybrid system is one of the best choices to provide continuous power demand. Grid-Connected hybrid system with photovoltaic, wind, battery, and diesel generator seems to be most suitable and efficient. This proposed hybrid model ensures improved efficiency which consequently reduces per-unit cost of energy production. For design and optimization, Patenga, Chittagong has chosen because solar radiation is reasonable as well as the availability of wind speed. The main target of the system is to produce the electricity of 50 kW per hour every day. Thus, the projected demand is 1.2 MW/days which will elaborately discuss in section 4.

2. Energy sources and data analysis

Solar panels convert light energy into electrical energy. Sun radiation is absorbed with the panel materials and electrons that are emitted from the atoms that they are bounded. This released current creates solar power and converted into electrical power by the solar cell (Chowdhury et al., 2012). When PV cells are joined physically and electrically, it is called a solar panel or PV module. Panels join together and form a solar array. The sunlight impinging on panels, i.e. irradiance or isolation (incoming solar radiation), is measured in units of watts per square meter (W/m²). Generally, only 40% of sunlight radiation can be used by PV module (Bala & Siddique, 2009). The PV system gives the output as a direct current power. Wind power involves converting wind energy into electricity by using wind turbines. It converts kinetic energy into mechanical energy (Sebzali et al., 2013). A wind turbine is composed of a number of propeller-like blades called a rotor. The wind comes from the change of the air that moves around the surface of the earth. The power output of a turbine is a function of the cube of the wind speed. If wind speed increases, output power also increases. It can convert only 59% wind energy into electricity according to the Betz limit (Mathew, 2006). The Nonrenewable source diesel generator which operates at a low load is inefficient and fuel cost low, diesel generator consumes 30% of full-load fuel consumption (Shaahid & Elhadidy, 2005). The autonomous diesel generator has high operation cost, constant maintenance, and the transportation of fuel to remote locations is difficult and costly, mainly in the rainy season in Bangladesh (Zubair et al., 2012). Diesel generator uses to help fulfil the target demand. To analysis the price of diesel, this can vary considerably based on region, transportation costs, and current market price. In Bangladesh, the Diesel price of diesel is 0.7 USD/L, with the lower heating value of 42.3 MJ/kg, an emission density of 820 kg/m³, a sulphur content of 0.33%, and carbon content of 88%.

2.1. Resources data analysis

Chittagong is the commercial capital of Bangladesh. There are 20 Thana and Upazilla in Chittagong (Bangladesh National Portal, 2018). Patenga Thana in Chittagong city is the chosen area for the collection of resources data for software simulations. Patenga is located at 22 degrees 14.73 minutes North latitude and 91 degrees 47.24 minutes East longitude. One-year climate data and wind data are collected from Bangladesh Meteorological Department, Patenga airport branch and the average real-time solar radiation is 5.85 kWh/m²/day also collected one-year solar radiation data from NASA and average solar radiation is 4.76 kWh/m²/day (Bangladesh Meteorological Department, 2016; NASA surface meteorology and solar energy, 2018). The highest solar radiation is in April and the lower radiation is in October and the average clearness index is 0.51. Table 1 shows the resources data for Patenga, Chittagong, Bangladesh.

Table 1. Global horizontal irradiance (GHI) data and wind speed for Patenga, Chittagong

Month	Clearness index	NASA solar radiation (kWh/m^2/d)	BMD solar radiation (kWh/m^2/d)	NASA wind speed (m/s)	BMD-Patenga wind speed (m/s)
January	0.643	4.597	4.240	3.100	2.22
February	0.625	5.634	6.350	3.300	2.22
March	0.595	5.126	7.800	3.500	2.50
April	0.550	5.760	8.110	5.000	4.20
May	0.527	5.786	7.750	3.800	3.05
June	0.391	4.335	5.040	4.900	3.78
July	0.368	4.048	5.590	4.200	3.05
August	0.398	4.224	4.320	3.600	3.78
September	0.418	4.083	4.670	3.700	3.50
October	0.553	4.725	4.180	3.500	3.30
November	0.559	4.409	6.910	3.200	2.90
December	0.646	4.391	5.250	2.800	2.60
Average	0.512	4.758	5.850	3.710	3.10

3. Proposed hybrid system

A hybrid energy system has been proposed and thus have used two renewable energy (solar and wind) and a conventional energy diesel. When solar radiation falls on the PV cell, it will produce Direct current. After that, we used DC to DC regulator for the requirement of battery charging and the process will be controlled by the DC controller then store the PV power in the battery. Furthermore, an inverter to convert DC power into AC power. When wind flows rotates the wind turbine, it will produce AC Current. If the wind turbines produce less than 50 kW power, the power will go to the AC bar. If Wind turbine produces greater than 50 kW, the extra power will go to AC to DC converter then storage system battery. The combined power will supply the electrical load and national grid. If the primary combined power resources do not fulfil the targeted demand, then a diesel generator would be used as standby power to fulfil the targeted demand. The system controlled by a programmable logic controller. In addition, HOMER is used to optimize the most cost-effective configurations among a set of the hybrid system for electricity and MicroWin use for PLC Simulation (MicroWin Software, 2016).

Figure 1. Proposed Ssystem Ggeographical Llocation at Patenga

Figure 2. Hybrid Ssystem Mmodel

The main target of the grid-connected hybrid system is to produce 1.2 MW/day. Therefore, the average electrical power is 50 kW/h and the project lifetime is 25 years. Table 2 presents the proposed hybrid system component specification. Figures 1 and 2 represent the hybrid system model and geographical location which is situated at 22 degrees 14.73 minutes North latitude and 91 degrees 47.24 minutes East longitude at Patenga besides the Shah Amanat International Airport and Bay of Bengal, Chittagong, Bangladesh.

Table 2. Proposed system components specification

Component	Model name	Capacity	Unit
PV	Generic flat plate PV	100	kWP
Wind turbine	Norvento nED	10 × 8 = 80	kW
Generator	50 kW Genset	50	kW
Battery	CELLCUBE® FB 200-1600	1600	kWh
Converter & inverter	EnerSection® ZBB	50	kW
PLC	Siemens S7-200	1	Pcs
Grid extension	————	2	Km

4. Simulation and results

To optimize and cost analysis of the system used HOMER Pro software. Entering all the data of solar radiation, wind speed and load based on HOMER software requirement for optimized the system (HOMER Energy, 2018; Kabir, Matin, Chowdhury et al., 2017).

4.1. System component specifications for simulation

The proposed solar panel capacity is (200 W_p × 500) = 100 kW. The wind turbine capacity is (10 kW × 8) = 80 kW, and alternate source diesel generator capacity is 50 kW. The battery capacity is 1600 kWh. There, source data are collected from Bangladesh Meteorological Department Patenga airport branch in January to December 2015. Figure 3 shows the real-time solar radiation curve by HOMER and Table 3 Shows the PV system specification.

Figure 3. Monthly Aaverage Ssolar Rradiation Ddata

Table 3. PV system specification

Generic flat plate PV panel
PV panel	500Pcs
Rated capacity	(200WP × 500) = 100 kWP
Lifetime	25 yr
De-rating factor	80%
Tracking system	No Tracking
Slope	23.000 deg
Ground reflectance	20.0%
Capital cost	$72,500
Replacement cost	$000
Operation & maintenance (O&M) cost	$100/yr

Figure 4 represents the real-time wind speed curve by HOMER and Table 4 shows the wind system specification. Table 5 provides the diesel energy specification, and Table 6 presents the battery specification of the system.

Figure 4. Monthly Aaverage Wwind Sspeed Ddata

Table 4. Wind turbine generator specification

Wind turbine—Norvento nED 10
Wind turbine	8Pcs
Rated capacity	(10 kW × 8) = 80 kW
Rotor diameter	22 m
Hub height	35 m
Start up speed	2.5 m/s
Cut in speed	3 m/s
Cut off speed	20 m/s
Life time	20 years
Capital cost	$120,000
Replacement cost	$80,000
Operation & maintenance (O&M) cost	$1000/yr

Table 5. Diesel generator specification

Diesel generator—50 kW Genset
Rated capacity	50 kW
Lifetime	20,000 h
Capital cost	$6100
Replacement cost	$5000
Operation & maintenance (O&M) cost	$1000/h

Table 6. Battery specification

CELLCUBE battery
Nominal voltage	700 V
Nominal capacity	2285.71 Ah
Nominal capacity	16000 kWh
Round trip efficiency	65%
Approximate life	20 year
Maximum capacity	3297.384Ah
Suggest life throughout	17,520,000 kWh
Max. charge rate	1 A/Ah
Max. charge current	230.35 A
Max. discharge current	354.385 A
Capital cost	$100,000
Replacement cost	$60,000
Operation & maintenance (O&M) cost	$100/yr

The aimed of the system is to produce the electricity of 50 kW per hour on 365 days, but here it is shown only a household load demand collected from energy monthly bill. The uses of the household are tube light, energy bulbs, fans, laptop, TV, refrigerator, water pump, mobile charger, microwave, and many more.

2 km grid extension will be needed for the system to connect the National Grid. The rated capacity of grid purchase is 100 kW and the selling capacity is 1000 kW and the electricity price is 0.14 USD/kWh. Table 7 provides the monthly load demand in a household. Table 8 represents the grid connection and other system components specification.

Table 7. Monthly energy load demand

Month	kWh
January	120
February	90
March	145
April	185
May	210
June	180
July	190
August	235
September	185
October	220
November	200
December	120
Total consumed (year)	1890

Table 8. Other components capacity and cost specification

Name	Size ($)	Capital ($)	Replacement ($)	O&M ($)
Converter	80 kw	6000	300	None
Inverter	50 kw	12,000	800	None
Grid extension	2 km	10,000	000	100
PLC	1pcs	2000	000	None

4.2. Simulation results

The simulation results are discussed in the following subsection.

4.2.1. Photovoltaic energy analysis

The rated capacity of the PV panel is 100 kW and total electricity production is 186,035 kWh/yr. The mean output of the PV system is 21 kW.

Figure 5. PV power curve

Figure 6. PV monthly power production

Total hours of operation of the PV system are 4372 h/yr and per-unit cost of the PV system is 0.041$/kWh. Table 9 represents the PV system output power also Figures 5 and 6 show the PV system daily and monthly electricity Production.

Table 9. PVsystem output power

Quantity	Value	Units
Rated capacity	100	kW
Mean output	21	kW
Mean output	509.69	kWh/d
Total production	186035	kWh/yr
Hours of operation	4372	h/yr

4.2.2. Wind energy analysis

The rated capacity of the wind turbine generator is 80 kW; total electricity production is 225807 kWh/yr. The mean output of wind power is 26 kW.

Figure 7. Wind power output

Figure 8. Wind turbine monthly production

Total hours of operation of the wind system are 5758 h/yr and per unit cost of the wind system is 0.059 $/kWh. Table 10 presents the wind turbine output power also Figures 7 and 8 show the wind turbine daily and monthly electricity production.

Table 10. Wind turbine generator output power

Quantity	Value	Units
Rated capacity	80	kW
Mean output	26	kW
Total production	225807	kWh/yr
Hours of operation	5758	h/yr

4.2.3. Diesel energy analysis

The rated capacity of the diesel generator is 50 kW. The total electricity production of the diesel generator is 85,480 kWh/yr.

Figure 9. Diesel generator output

Total hours of operation of the diesel system are 2137 h/yr. Total fuel consumption is 26,862 L/yr. Table 11 represents the Generator output power also Figure 9 shows the generator yearly output curve.

Table 11. Diesel generator output power

Quantity	Value	Units
Hours of operation	2137	h/yr
Number of starts	365	starts/yr
Operational life	14	yr
Fixed generation cost	1.76	$/h
Electrical production	85480	kWh/yr
Mean electrical output	40	kW
Fuel consumption	26862	L/yr
Specific fuel consumption	0.031	L/kWh
Fuel energy input	264323	kWh/yr
Mean electrical efficiency	32	%

4.2.4. Load and grid analysis

The main purpose of this work is to meet the national power demand. The aimed of the system is to contribute 1200 kW/day. The annual contribution is 438000 kWh/yr. The following results of the hybrid system are obtained in Table 12.

Figure 10. Total hybrid system electricity production

Figure 11. Energy sell into grid

Table 12. Total hybrid electricity production and consumption

Component/Load	Production/Consumption (kWh/yr)	Friction (%)
PV	186,036	38
Wind turbine	225,807	46
Diesel generator	85,480	16
Total hybrid system	497,323	100
Cost of energy (COE) of the system		$0.12
AC	1,890	0.38
Grid sell	478,498	96.21
System loss	16,935	3.41

In this system, the production of electricity is 497323 kWh/yr. Figure 10 shows total hybrid electricity production of the system. The system connected to the National grid for commercial purpose. The energy sell price is 0.149 USD/kWh. The annual grid sold 478,498 kWh/yr and the energy sold price is 71,725 USD/yr. Table 13 shows an analysis of grid selling price and Figure 11 represents the curve of energy sell into the grid.

Table 13. Analysis of grid selling price

Monthly	Energy sold (kWh)	Unit price ($)	Energy charge ($)
January	37,857	0.149	5,675
February	32,600		4,888
March	40,099		6,011
April	37,269		5,586
May	56,885		8,529
June	38,795		5,816
July	52,353		7,850
August	39,014		5,847
September	36,302		5,442
October	36,309		5,442
November	35,279		5,285
December	35,731		5,354
Annual	478,498		71,725

5. Hybrid control system

The main target is to supply 50 kW electricity per hour, but Homer does not show the curve constantly 50 kW per hour. Therefore, we controlled the system using the programmable logic controller like SiemensS7-200. Two energy meter are used as a sensor, it’s count then PLC device will control the system. Solar, wind ON/OF switch are used for maintenance. Diesel generator on/off switch uses automatic control which is controlled by PLC controller. There is an interlock system (W_Meter) which controls wind power. If electricity generation is less than equal to 50 KWh, it directly goes to E_Meter. If electricity generation greater than 50 kWh, extra energy will be stored in the battery. If E_Meter provide less than 50 kWh hour, diesel generator starts and controls valve control the flow of diesel. The control system provides a constant of 50 units per hour.

Figure 12. Proposed control system diagram

There are many months that would not need to use a diesel generator but in those months minimum, 1 hour will operate diesel generator in peak demand time in a day for running the diesel generator. Figure 12 represents the proposed control system diagram, and Figure 13 presents the total electricity production curve after using a Programmable logic controller.

Figure 13. Total electricity production controlled by plc

Figure 14. Generator output curve controlled by plc

The highest use of the diesel generator is in October and the lowest uses are in March to August. Figure 14 represents the generator yearly output controlled by the Programmable logic controller. Furthermore, May is the highest electricity production of the hybrid system and the lowest production is in October. On the other side, the cost of electricity is about 0.16 USD/kWh initially without using a PLC controller. After that using the PLC controller, the cost of energy is reducing 0.12 USD/kWh as well as reducing the rate of conventional fuel (diesel) consumption which helps to reach the environment-friendly system.

6. Cost analysis of the system

The components, installation, and transportation cost of the system initially are very high at about 328,600 USD. About 15 years, battery converter and inverter need to be replaced, and wind turbine needs to be replaced about 20 years. After 14 years, the diesel generator needs to be replaced. The real interest rate is 6.3. The cost of energy (COE) is the average cost/kWh of the electrical energy produced by the system.

Figure 15. Components wise cost of the hybrid system

Figure 16. Hybrid system cash flows yearly

The total cost of the system is 750,804 USD. The fuel cost is 0.85 USD/litre. Total fuel cost of the system is 277,808 USD. Figures 15 and 16 show the system cost analysis. Grid sell price is 0.149 USD/kWh. The net grid sell price is 917,228 USD. It is represented in the operation and maintenance cost in Tables 14 and 15. The net profit of the system is 220,424 USD. The annual cost is 53,901 USD. As a result, the annual profit of the system is 17,051 USD. The overall electricity cost of the hybrid system is 0.12 USD/kWh (or 10.4BDT/kWh) that is also cost-effective than quick rental power (HFO) plants (around 0.33 USD/kWh or 26.57 BDT/kWh) wind power plant (around 70 BDT/kWh or 0.88 USD/kWh) and Diesel power plants (around 0.39 USD/kWh or 31.03 BDT/kWh) in Bangladesh according to the latest Bangladesh power development board annual reports in 2016–17 (Bangladesh Power Development Board, 2018).

Table 14. Net present costs of the hybrid system

Component	Capital($)	Replacement($)	O&M($)	Fuel($)	Salvage($)	Total($)
Generic flat plate PV	72,500	0	1,293	0	0	73,793
Norvento nED 10	120,000	33,942	25,855	0	−6,388	173,409
50 kW Genset	6,100	8,649	829	277,808	−641	292,745
Grid	774	0	−71,725	0	0	70,952
PLC	2,000	0	0	0	0	2,000
CELLCUBE battery	100,000	33,942	1,293	0	−6,388	128,846
Converter & inverter	18,000	5,091	3,878	0	−958	26,011
System	328,600	81,62	−894,081	277,808	−14,37	−220,424

Table 15. Annualized costs of the hybrid system

Component	Capital($)	Replacement($)	O&M($)	Fuel($)	Salvage($)	Total($)
Generic flat plate PV	5,608	0	100	0	0	5,708
Norvento nED 10	9,283	2,626	2,000	0	−494	13,414
50 kW Genset	472	669	64	21,490	−50	22,645
Grid	774	0	−71,725	0	0	70,952
PLC	15	0	0	0	0	154
CELLCUBE battery	7,735	2,626	100	0	−494	9,967
Converter & inverter	1,392	394	300	0	−74	2,012
System	25,418	6,314	−69,161	21,490	−1,112	−17,051

7. Conclusions

The per-unit cost of electricity of the proposed hybrid power system is 0.16 USD initially that is better than conventional quick rental power plant in an economic point of view which per-unit cost of electricity is 0.33 USD/kWh. Finally, utilizing the programmable logic controller the proposed system cost of electricity is reached 0.12 USD/kWh which is the optimized cost of the system. The proposed system is suitable for any kind of areas in Bangladesh except wind system. The system creates negligible noise and pollution. Diesel generator creates some emissions, but the percentage of the usage of a diesel generator is low which about 16%. Figure 17 shows the system electricity contribution.

Figure 17. The system electricity contribution

The collected wind speed data are at 30 feet height, but the proposed wind turbine height was 25 m. However, the production of wind power will increase with an increase in height. Therefore, it may not necessitate using diesel power. The electricity sale price of the system is 0.149 USD which is better than conventional power plants (Such as HFO, Diesel) electricity rates in Bangladesh. After 25 years, the overall profit of the system is about 220,424 USD. The system also helps to connect urban and rural areas power plant. As a result, it helps to decrease the gap between the urban and rural areas.

Cover Image

Source: Author.

Acknowledgements

The authors are grateful to the Renewable Energy Research Lab, Department of Electrical & Electronic Engineering (EEE) and Institute of Energy Technology (IET), at Chittagong University of Engineering & Technology (CUET), Chittagong, Bangladesh for the support to carry out the research work reported in this paper.

Additional information

Funding

The authors received no direct funding for this research.

Notes on contributors

K. M. Kabir

K. M. Kabir has received his B.Sc. in EEE from University of Science & Technology Chittagong (USTC) and awarded his M.Sc. in Energy Technology from Chittagong University of Engineering and Technology (CUET), Chittagong-4349, Bangladesh. He is a member of the Institute of Electrical and Electronics Engineers (IEEE) since 2013, His research area includes Renewable energy, Power Generation, Micro Grid & Smart Grid, Desalination, Control & Automation. Email: [email protected]