Please wait a minute...
Frontiers in Energy

ISSN 2095-1701

ISSN 2095-1698(Online)

CN 11-6017/TK

邮发代号 80-972

2019 Impact Factor: 2.657

Frontiers in Energy  2019, Vol. 13 Issue (2): 269-283   https://doi.org/10.1007/s11708-018-0573-z
  本期目录
基于光伏-风力-电池纳米电网系统的优化设计与开发:一个实验室现场演示
TUDU B.(), MANDAL K. K., CHAKRABORTY N.
贾达夫布尔大学动力工程系,加尔各答 700098, 印度
Optimal design and development of PV-wind-battery based nano-grid system: A field-on-laboratory demonstration
B. TUDU(), K. K. MANDAL, N. CHAKRABORTY
Department of Power Engineering, Jadavpur University, Kolkata 700098, India
 全文: PDF(6665 KB)   HTML
摘要:

本文介绍了纳米网格系统的设计方法、项目实施和经济性。该系统的开发旨在通过实验室现场演示(FOLD)和“架通研究、开发和实施之间的鸿沟”,以使可再生技术适应印度社会。该系统由太阳能光伏(PV)(2.4 kWp)、风力发电机(3.2 kWp)和电池组(400 Ah)组成。首先,利用美国国家可再生能源实验室(NREL)开发的成熟的HOMER(电力可再生混合优化模型)软件进行了前期可行性研究。可行性研究表明,纳米电网系统的最佳容量由一台2.16 kWp太阳能光伏、一台3kWp风力发电机、一台1.44kw逆变器和一个24kWh电池组组成。系统的总净现值(TNPC)和能源成本(COE)分别为20789.85美元和0.673美元/kWh。然而,由于没有所需规格的系统组件,并且为了提高系统的可靠性,安装了由2.4 kWp太阳能光伏、3.2 kWp风力发电机、3 kVA逆变器和400 Ah电池组组成的混合系统。安装系统的TNPC和COE分别为20073.63美元和0.635美元/kWh,这两个成本在很大程度上受电池成本的影响。此外,本文还对各部件和系统的的安装细节进行了说明。另外,还讨论了系统的详细成本分解。进一步地,还对系统的性能进行了研究,并用仿真结果进行了验证。发现了在一年中来自光伏发电系统的发电量相当大,而且几乎是均匀的。与此相反,除4月、5月和6月外,一年中的风速很小,发电量也很小。本研究演示为在印度地区或类似地形地区,未来规划大规模混合能源系统或微电网提供了一条路径。

Abstract

The present paper has disseminated the design approach, project implementation, and economics of a nano-grid system. The deployment of the system is envisioned to acculturate the renewable technology into Indian society by field-on-laboratory demonstration (FOLD) and “bridge the gaps between research, development, and implementation.” The system consists of a solar photovoltaic (PV) (2.4 kWp), a wind turbine (3.2 kWp), and a battery bank (400 Ah). Initially, a prefeasibility study is conducted using the well-established HOMER (hybrid optimization model for electric renewable) software developed by the National Renewable Energy Laboratory (NREL), USA. The feasibility study indicates that the optimal capacity for the nano-grid system consists of a 2.16 kWp solar PV, a 3 kWp wind turbine, a 1.44 kW inverter, and a 24 kWh battery bank. The total net present cost (TNPC) and cost of energy (COE) of the system are US$20789.85 and US$0.673/kWh, respectively. However, the hybrid system consisting of a 2.4 kWp of solar PV, a 3.2 kWp of wind turbine, a 3 kVA of inverter, and a 400 Ah of battery bank has been installed due to unavailability of system components of desired values and to enhance the reliability of the system. The TNPC and COE of the system installed are found to be US$20073.63 and US$0.635/kWh, respectively and both costs are largely influenced by battery cost. Besides, this paper has illustrated the installation details of each component as well as of the system. Moreover, it has discussed the detailed cost breakup of the system. Furthermore, the performance of the system has been investigated and validated with the simulation results. It is observed that the power generated from the PV system is quite significant and is almost uniform over the year. Contrary to this, a trivial wind velocity prevails over the year apart from the month of April, May, and June, so does the power yield. This research demonstration provides a pathway for future planning of scaled-up hybrid energy systems or microgrid in this region of India or regions of similar topography.

Key wordsphotovoltaic (PV)    wind    battery    nano-grid    hybrid optimization model for electric renewable (HOMER)    field-on-lab demonstration (FOLD)
收稿日期: 2017-10-10      出版日期: 2019-07-04
通讯作者: TUDU B.     E-mail: bhimsen.tudu@jadavpuruniversity.in
Corresponding Author(s): B. TUDU   
 引用本文:   
TUDU B., MANDAL K. K., CHAKRABORTY N.. 基于光伏-风力-电池纳米电网系统的优化设计与开发:一个实验室现场演示[J]. Frontiers in Energy, 2019, 13(2): 269-283.
B. TUDU, K. K. MANDAL, N. CHAKRABORTY. Optimal design and development of PV-wind-battery based nano-grid system: A field-on-laboratory demonstration. Front. Energy, 2019, 13(2): 269-283.
 链接本文:  
https://academic.hep.com.cn/fie/CN/10.1007/s11708-018-0573-z
https://academic.hep.com.cn/fie/CN/Y2019/V13/I2/269
Sl. No. Load type Rating/kW Units Total/kW
1 Fan 0.074 15 1.11
2 Light 0.030 40 1.2
3 Computer 0.150 3 0.45
4 Test benches 0.050 4 0.2
Total load 2.96
Total energy required (2 h per day)/(kWh?d–1) 5.92
Tab.1  
Fig.1  
Fig.2  
Fig.3  
Fig.4  
Components Capacity
Solar PV/kW 2.16
Wind turbine/kW 3
Battery/kWh 24
Converter/kW 1.44
Tab.2  
Fig.5  
Fig.6  
Fig.7  
Fig.8  
Parameters Values
Make WEBSOL Energy System Ltd.
Module type H300-300WP
Rated peak power (PMAX)/Wp 300
Voltage at maximum power (VMP)/V 36.2
Current at maximum power (IMP)/A 8.3
Open circuit voltage (VOC)/V 44.9
Short circuit current (ISC)/A 8.9
Temperature/°C –40 – 90
Wind load/(km?h–1) Up to 200
Humidity 0%–100%
Type of cell Crystalline silicon
Efficiency of cell 13%–15%
Lamination type Vacuum laminated glass to EVA and tedler
Tab.3  
Fig.9  
Parameters Specification
General configuration Rotation axis Horizontal
Orientation Up wind
Rotation direction Clockwise facing upwind
Number of blades 2
Rotor diameter/m 4.50
Weight/kg Approx. 70±10%
Performance Peak electrical power/W 3200
1 min max average power output/W 3200(As per IEC 61400 Test Certificate)
Rated wind speed/(m?s–1) 12
Startup/cut in wind speed/(m?s–1) 3.1
Cut out wind speed/(m?s–1) 14–16
Survival wind speed/(m?s–1) 55
Rotor Swept area/m2 15.9
Rotational speed/(r?min–1) 700–800
Blade pitch Fixed
Direction of rotation Clockwise
Over speed control Side furling and dump load
Manual stopping by brake switch installed on the base of the turbine tower
Yaw system Wind direction sensor By tail fin and tail boom
Yaw control Free/passive yaw
Type Mild steel tubular-5” diameter – 20 feet
height on roof top with guy support
Guy material Steel wire rope of 6 mm (for Tubular Tower)
Accessories Suitable turnbuckle, DC lamp, wire clamp, etc.
Tab.4  
Fig.10  
Parameters Values
Voltage configuration/V 48
Power factor/% 80
Battery efficiency/% 85
Battery capacity 48 V 400 Ah
Voltage of each cell (nominal)/V 2
Combination of batteries 24 nos. of 400 Ah
Type of battery Tubular lead acid flooded electrolyte
Positive plate Tubular
Negative plate Pasted flat
Electrolyte Sulphuric acid
Tab.5  
Parameters Values
Inverter capacity/kVA 3
Efficiency/% 90
Duty Continuous
Wave form Sine wave
Ambient/°C 60
Protection I/P under voltage, I/P over Voltage,
O/P Overload, O/P Short – Circuit
Relative humidity/% 98
Power device MOSFET/IGBT
Control Pulse width modulation
Power factor 0.8
Tab.6  
Fig.11  
Component Size Capital cost/US$ Replacement cost/US$ O & M cost/(US$·a−1) Other parameters
PV 0.3 kW 537.00 306.00 0.00 [32] Derating factor: 0.9 [32]; Lifetime: 25 years
Wind 3 kW 4350.00 3000.00 114.00 Reference height: 10 m;
Hub height: 28.10 m; Lifetime: 20 years
Battery 1 kWh 150.00 140.00 15.00 Throughput (kWh): 3000.00;
Roundtrip efficiency: 90%; Lifetime: 15 years
Inverter 1 kW 180.00 150.00 3.00 Efficiency: 96%;
Lifetime: 15 years
Tab.7  
Fig.12  
Fig.13  
Cost summary
(Net present cost)
PV system Wind system Battery Converter Hybrid system
Capital cost 3871.98 4350.00 3600.00 260.01 12082.00
Replacement cost 0.00 1162.49 1650.22 106.42 2919.13
Operation and maintenance cost 0.00 1630.43 5148.71 61.98 6841.12
Fuel cost 0.00 0.00 0.00 0.00 0.00
Salvage value 0.00 –687.89 –342.42 –22.08 –1052.39
TNPC 3871.98 6455.03 10056.51 406.33 20789.85
Tab.8  
Cost summary
(Annualized cost)
PV system Wind system Battery Converter Hybrid system
Capital cost 270.73 304.15 251.71 18.18 844.78
Replacement cost 0.00 81.28 115.38 7.44 204.11
Operation and maintenance cost 0.00 114.00 360.00 4.33 478.33
Fuel cost 0.00 0.00 0.00 0.00 0.00
Salvage value 0.00 –48.10 –23.94 –1.54 –73.58
TAC 270.73 451.34 703.16 28.41 1453.63
Tab.9  
Components Sub-components Cost/W(Rs.) Cost/W(US$)
PV systems PV panels 70.00 1.08
Panel fitment structure 10.00 0.15
Cable and wire 5.00 0.08
Charge controller 3.33 0.05
Total 88.33 1.36
Wind system Aero generator 73.44 1.13
Brake switch, junction box 3.75 0.06
Cable and wire 4.69 0.07
Tower (6.5 m) and support system 12.5 0.19
Total 94.38 1.45
Inverter Per VA 11.67 0.18
Controller and Control panel unit 8.33 0.13
Data monitoring and logging 8.33 0.13
Battery Per Wh 11.46 0.18
Other cost Transport, loading and unloading 1.67 0.003
Civil work, erection and commissioning 11.67 0.18
Total 13.34 0.183
Total project cost 224.17 3.4348
Tab.10  
Cost summary
(Net present cost)
PV system Wind system Battery Converter Hybrid system
Capital cost 4296.00 4640.00 2880.00 540.00 12356.00
Replacement cost 0.00 1241.60 1319.81 220.95 2782.36
Operation and maintenance cost 0.00 1739.97 4120.99 128.78 5989.75
Fuel cost 0.00 0.00 0.00 0.00 0.00
Salvage value 0.00 –734.40 –274.18 –45.90 –1054.48
TNPC 4296.00 6887.17 8046.62 843.83 20073.63
Tab.11  
Cost summary
(Annualized cost)
PV system Wind system Battery Converter Hybrid system
Capital cost 300.25 324.29 201.28 37.74 863.56
Replacement cost 0.00 86.73 72.32 12.20 171.25
Operation and maintenance cost 0.00 119.00 281.84 8.81 409.65
Fuel cost 0.00 0.00 0.00 0.00 0.00
Salvage value 0.00 –51.33 –18.97 –3.21 –73.51
TAC 300.25 478.69 536.47 55.54 1370.94
Tab.12  
1 S Diaf, G Notton, M Belhamel, M Haddadi, A Louche. Design and techno-economical optimization for hybrid PV/wind system under various meteorological conditions. Applied Energy, 2008, 85(10): 968–987
https://doi.org/10.1016/j.apenergy.2008.02.012
2 O Nadjemi, T Nacer, A Hamidat, H Salhi. Optimal hybrid PV/wind energy system sizing: application of cuckoo search algorithm for Algerian dairy farms. Renewable & Sustainable Energy Reviews, 2017, 70: 1352–1365
https://doi.org/10.1016/j.rser.2016.12.038
3 A Maleki, M G Khajeh, M Ameri. Optimal sizing of a grid independent hybrid renewable energy system incorporating resource uncertainty, and load uncertainty. International Journal of Electrical Power & Energy Systems, 2016, 83: 514–524
https://doi.org/10.1016/j.ijepes.2016.04.008
4 A Askarzadeh, L dos Santos Coelho. A novel framework for optimization of a grid independent hybrid renewable energy system: a case study of Iran. Solar Energy, 2015, 112: 383–396
https://doi.org/10.1016/j.solener.2014.12.013
5 E S Takle, R H Shaw. Complimentary nature of wind and solar energy at a continental mid-latitude station. International Journal of Energy Research, 1979, 3(2): 103–112
https://doi.org/10.1002/er.4440030202
6 A Razmjoo, M Qolipour, R Shirmohammadi, S M Heibati, I Faraji. Techno-economic evaluation of standalone hybrid solar-wind systems for small residential districts in the central desert of Iran. Environmental Progress & Sustainable Energy, 2017, 36(4): 1194–1207
https://doi.org/10.1002/ep.12554
7 M Smaoui, A Abdelkafi, L Krichen. Optimal sizing of stand-alone photovoltaic/wind/hydrogen hybrid system supplying a desalination unit. Solar Energy, 2015, 120: 263–276
https://doi.org/10.1016/j.solener.2015.07.032
8 M Bianchi, L Branchini, C Ferrari, F Melino. Optimal sizing of grid-independent hybrid photovoltaic-battery power systems for household sector. Applied Energy, 2014, 136: 805–816
https://doi.org/10.1016/j.apenergy.2014.07.058
9 S Sinha, S S Chandel. Improving the reliability of photovoltaic-based hybrid power system with battery storage in low wind locations. Sustainable Energy Technologies and Assessments, 2017, 19: 146–159
https://doi.org/10.1016/j.seta.2017.01.008
10 M Baneshi, F Hadianfard. Techno-economic feasibility of hybrid diesel/PV/wind/battery electricity generation systems for non-residential large electricity consumer sunder southern Iran climate conditions. Energy Conversion and Management, 2016, 127: 233–244
https://doi.org/10.1016/j.enconman.2016.09.008
11 M A Haghighat, S A Avella Escandon, B Najafi, A Shirazi, F Rinaldi. Techno-economic feasibility of photovoltaic, wind, diesel and hybrid electrification systems for off-grid rural electrification in Colombia. Renewable Energy, 2016, 97: 293–305
https://doi.org/10.1016/j.renene.2016.05.086
12 A Kaabeche, M Belhamel, R Ibtiouen. Techno-economic valuation and optimization of integrated photovoltaic/wind energy conversion system. Solar Energy, 2011, 85(10): 2407–2420
https://doi.org/10.1016/j.solener.2011.06.032
13 El-Kordy M N, Badr M A, Abed K A, Ibrahim S M A. Economical evaluation of electricity generation considering externalities. Renewable Energy, 2002, 25(2): 317–328
https://doi.org/10.1016/S0960-1481(01)00054-4
14 A Heydari, A Askarzadeh. Optimization of a biomass-based photovoltaic power plant for an off-grid application subject to loss of power supply probability concept. Applied Energy, 2016, 165: 601–611
https://doi.org/10.1016/j.apenergy.2015.12.095
15 S Upadhyay, M P Sharma. Development of hybrid energy system with cycle charging strategy using particle swarm optimization for a remote area in India. Renewable Energy, 2015, 77: 586–598
https://doi.org/10.1016/j.renene.2014.12.051
16 A Askarzadeh, L dos Santos Coelho. A novel framework for optimization of a grid independent hybrid renewable energy system: a case study of Iran. Solar Energy, 2015, 112: 383–396
https://doi.org/10.1016/j.solener.2014.12.013
17 A Yahiaoui, K Benmansour, M Tadjine. Control, analysis and optimization of hybrid PV-Diesel-Battery systems for isolated rural city in Algeria. Solar Energy, 2016, 137: 1–10
https://doi.org/10.1016/j.solener.2016.07.050
18 H Rezk, G M Dousoky. Technical and economic analysis of different configurations of stand-alone hybrid renewable power systems–a case study. Renewable & Sustainable Energy Reviews, 2016, 62: 941–953
https://doi.org/10.1016/j.rser.2016.05.023
19 R Dufo-Lopez, J L Bernal-Agustin, J Contreras. Optimization of control strategies for stand-alone renewable energy systems with hydrogen storage. Renewable Energy, 2007, 32(7): 1102–1126
https://doi.org/10.1016/j.renene.2006.04.013
20 R Dufo-Lopez, J L Bernal-Agustin. Design and control strategies of PV–diesel systems using genetic algorithms. Solar Energy, 2005, 79(1): 33–46
https://doi.org/10.1016/j.solener.2004.10.004
21 R A Gupta, R Kumar, A K Bansal. BBO-based small autonomous hybrid power system optimization incorporating wind speed and solar radiation forecasting. Renewable & Sustainable Energy Reviews, 2015, 41: 1366–1375
https://doi.org/10.1016/j.rser.2014.09.017
22 A Maleki, A Askarzadeh. Artificial bee swarm optimization for optimum sizing of a stand-alone PV/WT/FC hybrid system considering LPSP concept. Solar Energy, 2014, 107: 227–235
https://doi.org/10.1016/j.solener.2014.05.016
23 P García-Triviño , L M Fernández-Ramírez, A J Gil-Mena, F Llorens-Iborra , C A Garcıa-Vazquez, F Jurado. Optimized operation combining costs, efficiency and lifetime of a hybrid renewable energy system with energy storage by battery and hydrogen in grid-connected applications. International Journal of Hydrogen Energy, 2016, 41(48): 23132–23144
https://doi.org/10.1016/j.ijhydene.2016.09.140
24 O Nadjemi, T Nacer, A Hamidat, H Salhi. Optimal hybrid PV/wind energy system sizing: application of cuckoo search algorithm for Algerian dairy farms. Renewable & Sustainable Energy Reviews, 2017, 70: 1352–1365
https://doi.org/10.1016/j.rser.2016.12.038
25 S Kamel, C Dahl. The economics of hybrid power systems for sustainable desert agriculture in Egypt. Energy, 2005, 30(8): 1271–1281
https://doi.org/10.1016/j.energy.2004.02.004
26 S Goel, S M Ali. Hybrid energy system for off grid remote telecom tower in Odisha, India. International Journal of Ambient Energy, 2013, 36(3): 116–122
https://doi.org/10.1080/01430750.2013.823110
27 S Cordiner, V Mulone, A Giordani, M Savino, G Tomarchio, T Malkow, G Tsotridis, A Pilenga, M L Karlsen, J Jensen. Fuel cell based Hybrid Renewable Energy Systems for off-grid telecom stations: data analysis from on field demonstration tests. Applied Energy, 2017, 192: 508–518
https://doi.org/10.1016/j.apenergy.2016.08.162
28 D Yamegueu, Y Azoumah, X Py, N Zongo. Experimental study of electricity generation by Solar PV/diesel hybrid systems without battery storage for off-grid areas. Renewable Energy, 2011, 36(6): 1780–1787
https://doi.org/10.1016/j.renene.2010.11.011
29 F Giraud, Z M Salameh. Steady-State performance of a grid-connected rooftop hybrid wind–photovoltaic power system with battery storage. IEEE Transactions on Energy Conversion, 2001, 16(1): 1–7
https://doi.org/10.1109/60.911395
30 P Díaz, C A Arias, R Pena, D Sandoval. FAR from the grid: a rural electrification field study. Renewable Energy, 2010, 35(12): 2829–2834
https://doi.org/10.1016/j.renene.2010.05.005
31 H X Yang, W Zhou, C Z Lou. Optimal design and techno-economic analysis of a hybrid solar–wind power generation system. Applied Energy, 2009, 86(2): 163–169
https://doi.org/10.1016/j.apenergy.2008.03.008
32 K Karakoulidis, K Mavridis, D V Bandekas, P Adoniadis, C Potolias, N Vordos. Techno-economic analysis of a stand-alone hybrid photovoltaic-diesel-battery-fuel cell power system. Renewable Energy, 2011, 36(8): 2238–2244
https://doi.org/10.1016/j.renene.2010.12.003
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed