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Techno-economic evaluation of various hybrid power systems for rural telecom
Renewable and Sustainable Energy Reviews 43 (2015) 553–561
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Renewable and Sustainable Energy Reviews journal homepage: www.elsevier.com/locate/rser
Techno-economic evaluation of various hybrid power systems for rural telecom W. Margaret Amutha n, V. Rajini SSN College of Engineering, Kalavakkam, Chennai, Tamil Nadu, India
art ic l e i nf o
a b s t r a c t
Article history: Received 22 August 2014 Received in revised form 16 October 2014 Accepted 31 October 2014
Nowadays, utility has started to consider the green power technology for having a healthier environment. The green power technologies reduce combustion of fossil fuels and the consequent CO2 emission which is the principle cause of global warming. By maximising the use of the renewable energy, the usage of diesel generator for powering the base transceiver stations could be reduced or removed. This paper aims to investigate the economic, technical and environmental performance of various hybrid power systems for powering remote telecom. Simulations using Hybrid Optimisation Model for Electric Renewable (HOMER) software are performed to determine the Initial Capital, the Total Net Present Cost (TNPC), the Cost of Energy (COE) as well as the system Capacity Shortage of the different supply options. The simulation results suggest a suitable hybrid system which would be the feasible solution for generation of electric power for remote telecom. A detailed analysis, description and modelling of the system are also presented in this paper. & 2014 Elsevier Ltd. All rights reserved.
Keywords: Hybrid power system Optimisation Hybrid Optimisation Model for Electric Renewable (HOMER) Modelling
Contents 1. 2. 3.
4. 5.
n
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 554 Various hybrid systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 554 Modelling of the hybrid system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 554 3.1. Telecom load . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 554 3.2. Solar system model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 556 3.2.1. Solar photovoltaic system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 556 3.3. Wind turbine model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 556 3.3.1. Wind generator system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 556 3.4. Hydrogen storage fuel cell model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 557 3.5. Diesel generator model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 558 3.6. Battery model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 558 3.6.1. Battery bank. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 558 3.7. Converter model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 558 3.8. Grid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 558 HOMER solutions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 558 Results and discussions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 560 5.1. Emissions (kg/year) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 560 5.2. Production (kWh/year) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 560 5.3. Cost ($). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 560 5.4. Fuel. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 560
Corresponding author. E-mail addresses: [email protected] (W. Margaret Amutha), [email protected] (V. Rajini).
http://dx.doi.org/10.1016/j.rser.2014.10.103 1364-0321/& 2014 Elsevier Ltd. All rights reserved.
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5.5. Sensitivity analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.6. Optimisation results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.7. Recommendations and conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1. Introduction In the recent years, India's energy consumption has been increasing at a fast rate in the world due to population growth and economic development [1]. In India, Industrial consumers are the largest group of electricity consumers, followed by the domestic, agricultural and commercial consumers, in that order. The Indian telecommunications industry is one of the fastest growing industries in the world. India is currently adding 8–10 million mobile subscribers every month [2–5]. The power woes of India's telecom sector especially in the rural areas are quite apparent. It is a big challenge for the industry to meet its regular power requirements through traditional fuel, which is expensive [6]. Power deficits coupled with the rising cost of diesel pose a significant challenge to the mid-term growth and profitability of the telecommunication sector. Continued reliance on diesel will also substantially increase the environmental costs in the form of carbon emissions. The telecommunication sector is well placed to transit to a business model which relies on energy efficiency measures in combination with harnessing clean energy sources for its operations. This has compelled the industry to look for alternative green energy solutions. India has one of the highest potentials for harnessing the renewable energy. Renewable energies are also inexhaustible and clean. Renewable Energy Systems, particularly hybrid systems, have the additional advantage of being complimentary [7–9]. A hybrid system consists of two or more renewable energy sources used together to provide green energy, increased system efficiency as well as greater balance in energy supply. Thus, India's growing telecommunication tower industry can achieve substantial cost savings, while reducing their fossil-fuel dependence and carbon footprint, by switching to hybrid renewable power generated electricity supply. The various Renewable Energy Sources (RES) such as solar energy, wind energy, fuel cells and so on are used for telecommunications applications in the developing countries. Many literature references have discussed the economic cost analysis of combinations of hybrid power system [10–13]. Also, there is a lot of literature about design and analysis in the context of renewable energy power generations [14–19]. The main objective of this paper is to compare various hybrid renewable energy systems in all aspects like optimal cost allocation of each individual components present in the system, sensitivity variable solar radiation, wind speed, emissions, electricity production and to examine the best effective renewable based hybrid system configuration. For all the combinations of hybrid power system combinations, the meteorological data of solar radiation and wind speed is taken for Chennai [20–26], India with the Latitude 131 North and Longitude 80.181 East and the pattern of load consumption of typical telecom load profiles are suitably modelled. Here, Hybrid Optimisation Model for Electric Renewable (HOMER) software is used to analyse hybrid power system.
2. Various hybrid systems The intermittent nature of the solar and wind energy under varying climatic conditions requires a feasibility assessment and optimal sizing of hybrid solar and wind energy system. Without proper technical and financial feasibility study, the hybrid
560 560 560 561
alternative energy systems may end up in a poor efficient system. The intent behind this paper is to design, optimise and analyse an effective hybrid power system for a remote telecom station and to compare then with the existing Diesel power scheme. HOMER determines the operational strategy for a hybrid renewable energy system based on three tasks which are simulation, optimisation analysis and sensitivity analysis. It simulates the operation of the system based on the components chosen by the user. So, here the hybrid combinations chosen are (i) Diesel generator (ii) GridDiesel generator (iii) Solar PV-Diesel Generator (iv) Solar PV-Wind system-Diesel generator-Battery (v) Solar PV-Wind system-Diesel generator-Battery-Fuel cell (vi) Solar PV-Wind system-BatteryFuel cell (vii) Solar PV-Wind system-Battery. The architecture of various hybrid system is shown in Fig. 1(i)–(vi). HOMER simulates the system based on the estimation of installing cost, replacement cost, operation cost, fuel and interest. The list of various configurations of hybrid renewable energy will be tabulated from the lowest to the highest total net present cost (TNPC). It then determines the best feasible system configuration which can adequately serve the electric demand. The optimal solution is referring to the lowest total net present cost (TNPC). HOMER compares a wide range of equipment with different constraints and sensitivities to optimise the system design. The analysis is based on the technical properties of the system and the life-cycle cost (LCC) of the system. The LCC comprises the initial capital cost, cost of installation and operation costs over the system's life span. HOMER performs simulations to satisfy the given demand using alternative technology options and resource availability.
3. Modelling of the hybrid system Hybrid Optimisation Model for Electric Renewable (HOMER) software helps us to determine how different renewable, and hybrid systems interact with end-use demand. Based on the availability and potential of renewable energies in the particular area a hybrid energy system is modelled. 3.1. Telecom load The Telecom load (Base Transceiver Station-BTS) is considered as primary load. The BTS is a telecom infrastructure used to facilitate wireless communication between subscriber device and telecoms operator network. The global development of BTS is increasingly taking place in regions in which the power distribution grid often breaks down for long periods of time or where there is no access to the power distribution grid. So the BTS in such regions, diesel generators with batteries are used to back-up the grid for electricity supply and ensure network availability. But these require a high level of maintenance work and consume relatively high amounts of diesel fuel for low level outputs. As a result diesel generators incur high operating expenses. The growing cost of energy (COE) due to increasing diesel prices and concerns over rising greenhouse emissions have caused the telecom companies to focus on better power management methods. The price of diesel since 2004 is shown in Fig. 2.
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Fig. 1. Architecture of system with (i) DG and (ii) Grid/DG. Architecture of hybrid renewable energy system with (iii) SPV/DG, (iv) SPV/Wind/DG/Battery, (v) SPV/Wind/DG/ FC/Battery, (vi) SPV/Wind/FC/Battery and (vii) SPV/Wind/Battery.
The conventional power system feeding a telecom load is shown in Fig. 3. The minimum-size of 1.3 kW is taken for analysis in this paper. There are two types of BTS load. One is indoor BTS and the other is outdoor BTS. Most indoor BTS require air conditioning. For outdoor applications there is no requirement for air conditioning. Daily telecom load profile considered is shown in Fig. 4. The data were measured for the total hourly basis
daily load requirement of a rural telecom. General average power consumption of BTS load is given in Table 1. The conventional topology for BTS shown in Fig. 5 uses a separate dc–dc converter (power conditioning circuit) for each of the renewable energy power sources. These individual converters are connected to a common DC bus which in turn feeds the telecom load. This system makes the system more bulky and expensive.
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Fig. 2. Diesel price since 2004.
Fig. 3. Conventional system feeding a telecom load.
Table 2 Monthly clearness index and solar radiation.
Fig. 4. Daily load profile.
Table1 Typical average power consumption. S.no
Type of BTS
Typical average consumption (kW)
1 2 3
2þ 2þ 2 4þ 4þ 4 6þ 6þ 6
1.3 2 3.5
Month
Clearness index
Radiation
January February March April May June July August September October November December
0.491 0.568 0.632 0.658 0.633 0.562 0.500 0.483 0.485 0.427 0.403 0.429
4.930 5.890 6.640 6.720 6.120 5.240 4.730 4.800 5.010 4.420 4.060 4.240
where Epv is energy (kWh), A is total solar panel area (m2), P is solar panel yield (%), H is annual average solar radiation on tilted panels, PR is performance ratio, coefficient for losses (range is between 0.5 and 0.9; default value is 0.75).
3.2. Solar system model 3.3. Wind turbine model The latitude of the site considered Chennai is 131 North and the longitude is 80.181 East. The time zone is GMTþ 5:30 India. The monthly solar irradiation horizontal data are taken for simulation. The solar system capacity is 2kW. The projected life time of the PV system is 20 years. The plant considered has no tracking system. Monthly clearness index and radiation in the region of Chennai, Tamil Nadu is taken from the website of NASA and is shown below in Table 2 and Fig. 6. 3.2.1. Solar photovoltaic system Based on the solar radiation available on the tilted surface the hourly energy output (EPV) of the PV generator can be calculated according to the following equation: EPV ¼ AnP nH nP R
ðiÞ
The monthly wind speed data is considered and measured at 16 m height. The projected life time of the wind system is 20 years. The wind system capacity is 3 kW. The power curve is shown in Fig. 7. The yearly wind speed of the study region is shown in Table 3. Fig. 8 shows the scaled data monthly averages for wind system. 3.3.1. Wind generator system Hourly energy generated (EWES) by wind generator with rated power output (PWES) is defined by the following expression: P WE ¼ 1=2 n ρ nA n V 3 n C p ðλ; βÞn ηt n ηg
ðiiÞ
EWES ðt Þ ¼ P WES ðt Þ n t
ðiiiÞ
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557
Fig. 5. Conventional topology.
Fig. 6. Solar radiation curve. Scaled data Monthly Averages
1.2 max daily high mean
1.0 0.8 0.6
daily low min
0.4
where ρ is the density of air in 1.22 kg/m3, CP is performance coefficient of the turbine, λ is tip speed ratio of the rotor blade tip speed to wind speed, β is blade pitch angle as 01, v is wind speed (m/s), ηt is wind turbine efficiency, ηg is generator efficiency, and A is area in m2
0.2 0.0 Jan Feb Mar Apr May Jun Jul
Aug Sep Oct Nov Dec Ann
3.4. Hydrogen storage fuel cell model
Month
Fig. 7. Scaled data monthly averages for solar.
Table 3 Wind speed data.
Fuel Cell (FC) is available in different configurations, power ranges, type of electrodes and operating characteristics. Proton Exchange Membrane (PEM) FC has a good start up and shut down characteristics. So, 2 kW fuel cell is considered. The projected life time is 15,000 h. The basic structure of PEM fuel cell has two electrodes (anode and cathode) separated by a solid membrane. In the hydrogen storage system, surplus renewable power goes to an electrolyser which produces hydrogen. Hydrogen goes into a storage tank to be consumed by the fuel cell when required. Hydrogen fuel is fed continuously to the anode and air is fed to the cathode. The internal chemical reaction is as follows: H2 þ 1=2O2 - H2 O
Month
Wind speed (m/s)
January February March April May June July August September October November December
3.900 3.500 3.500 3.500 3.800 4.400 4.200 4.100 3.000 2.800 3.600 4.200
ðivÞ
The hydrogen consumption at rated power Pfc kW of one hour is calculated by HY fc ¼ ½ðP fc n3600Þ=ð2V fc nFÞ
ðvÞ
where HYfc is the amount of hydrogen consumed by fuel cell, Pfc is output power of fuel cell, Vfc is output voltage of fuel cell, F is Faraday's constant. Hydrogen can be produced by the decomposition of water into its elementary components by passing the electric circuits. A water electrolyser consists of several cells connected in series. Two electrodes of the electrolyser are separated by electrolyte. Electrical current through the electrolyser enables the decomposition
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Fig. 8. Scaled data monthly averages for wind.
of water into hydrogen and oxygen by H2 O þelectricity-H2 þ1=2 O2
ðviÞ
According to Faraday's law the amount of Hydrogen produced by rated power Pfc kW electrolyser in one hour is calculated by HY ele ¼ ½ðP fc n3600Þ=ð2V ele nFÞ
ðviiÞ
where HYele is the amount of hydrogen produced by electrolyser, Pele is rated power of electrolyser, Vele is working voltage of electrolyser, and F is Faraday's constant. Hydrogen energy produced by the electrolyser provides solar energy storage in excess demand. The method of transferring the capacity of hydrogen tanks to the unit kWh is given by Etank ðkWhÞ ¼ M tank ðmolÞn2n10 3 kg=mol nLHV kWh=kg ðviiiÞ where Etank and Mtank is the size of hydrogen tank in kWh and LHV is the low heat value of hydrogen in kWh/kg.
On the other hand, when the load demand is greater than the available energy generated, the battery bank is in discharging state. Therefore, the available battery bank capacity at hour t can be expressed as EBat ðt Þ ¼ EBat ðt 1Þ Eneeded ðt Þ
Let d be the ratio of minimum allowable SOC voltage limit to the maximum SOC voltage across the battery terminals when it is fully charged. So, the Depth of Discharge (DOD) DOD ¼ ð1 dÞn100
SOC min ¼ ð1–DODÞ=100 3.7. Converter model
Generating sets are selected based on the electrical load they are intended to supply. 2 kW diesel generator power is considered to supply 1.3 kW BTS load. The capital cost considered is $900 and the replacement cost taken is $ 850. The projected life time is 15,000 h.
EREC–OUT ðt Þ ¼ EREC IN ðt ÞnηREC
3.6. Battery model
EREC IN ðt Þ ¼ ESUR AC ðtÞ
The variations of solar and wind energy generation do not match the time distribution of the demand. Therefore, power generation systems dictate the association of battery storage facility to smooth the time–distribution mismatch between the load and solar/wind energy generation and to account for maintenance of the systems. Batteries are considered as a major cost factor in small-scale stand-alone power systems. The battery stacks may contain a number of batteries ranging from 0 to 500 units. A battery of 6 V, 1.34 kW h has been chosen. Number of batteries per string considered is 8.
ESUR AC ðtÞ ¼ EDG ðtÞ
EBat ðt Þ ¼ Battery Capacity ðAhÞ=Battery Current ðAÞ
ðixÞ
ðxiÞ
DOD is a measure of how much energy has been withdrawn from a storage device, expressed as a percentage of full capacity. The maximum value of SOC is 1, and the minimum SOC is determined by maximum depth of discharge (DOD)
3.5. Diesel generator model
3.6.1. Battery bank The battery state of charge (SOC) is the cumulative sum of the daily charge/discharge transfers. At any hour (t) the state of battery is related to the previous state of charge and to the energy production and consumption situation of the system during the time from t 1 to t. During the charging process, when the total output of all systems exceeds the load demand, the available battery bank capacity at hour (t) can be described by
ðxÞ
ðxiiÞ
The rectifier model is given below: ðxiiiÞ
EREC OUT(t) is hourly energy output from rectifier, kWh, EREC IN(t) is hourly energy input to rectifier, kWh, and ηREC is efficiency of rectifier. ðxivÞ ðxvÞ
ESUR AC(t) is the amount of surplus energy from AC source, kWh, EDG (t) is surplus energy from diesel generator to DC power of constant voltage, when the energy generated by the hybrid energy system exceeds the load demand. 3.8. Grid Grid rating is divided in to three: (i) off peak (ii) shoulder and (iii) peak. For off peak $ 20,000 k/Wh price is considered. For shoulder $ 30,000 k/Wh and for peak $ 50,000 k/Wh is considered respectively.
4. HOMER solutions HOMER helps us to determine how different renewable, and hybrid systems interact with end-user demand. Based on the availability and potential of renewable energies in the particular area various combinations of energy systems can be chosen. The choice of the best combination of hybrid sources can be made after comparing their performance.
Table 4 Comparative analysis of various configurations of hybrid systems. Description
DG
Grid/DG
SPV/DG
SPV/WES/Battery/DG
SPV/WES/Battery/DG/FC
SPV/WES/Battery/FC
SPV/WES/Battery
1
DG Inverter Rectifier Solar system Wind system Battery Grid Fuel Cell Emissions (Kg/ Year) Carbon dioxide Carbon monoxide Unburned hydocarbon Particulate matter Sulphur dioxide Nitrogen oxides Production (kWh/ year) Electricity Excess electricity DC load Unmet load kW h/ year Mean electrical output Capacity shortage Cost ($) Total net present cost Levelized cost of energy Operating cost Fuel Fuel consumption Specific fuel consumption Fuel energy input Efficiency Mean electrical efficiency Battery Energy in kWh/Year Energy out kWh/year Storage depletion Losses Annual throughput Expected life
2 kW 2 kW 2 kW
0.5 kW 2 kW 2 kW
2 kW 2 kW 2 kW 2 kW
2 kW 2 kW 2 kW 2 kW 3 kW 48 V
2 kW 2 kW 2 kW 2 kW 3 kW 48 V
2 kW 2 kW 2 kW 3 kW 48 V
4 kW 3 kW 48 V
2 kW
2 kW
2
3
4
5
6
7
2 kW
20,967 51.8 5.73 3.9 42.1 462
4100 4.09 0.453 0.308 13.9 41.7
18,657 46.1 5.1 3.47 37.5 411
4653 11.5 1.27 0.866 9.34 102
1199 3.4 0.377 0.257 2.41 30.4
0.391 0.249 0.0275 0.0187 0 2.22
0 0 0 0 0 0
7290 290 5950 0.000151 832 W 0.0669
3956 þ 3132 7.78E 05 5950 þ 88 0.0001 500 W 0
3489 þ 6415 ¼9804 3200 5950 0.0000852 721 W 0
3489 þ2982 þ 1690 1456 5950 2.98E-07 1030 þ 1710W 0
3489 þ 2982 þ 1811þ 1354 159 5950 þ3157 0 1030 þ 1710W 0
3489 þ 2982 þ 1264 97.3 5444þ 1777 0 1030 þ1710 W 0
6979 þ2982 3926 5554 0 1030 þ1710 W 0
12,30,683 16.182/kW h 95,537/year
16,88,953 22.207/kW h 13,1386/year
12,27,382 16.138/kW h 94,966/year
2,91,274 3.830/kW h 20,118/year
75,515 0.997/kW h 2614/year
887,317 12,751/kW h 65,915/year
734,662 10.347/kW h 54,083/year
7962 L/year 1.092 L/kW h 78,349 kW h/year
629 L/year 0.201 L/kW h 6189 kW h/year
7085 L/year 1.122 L/kW h 69,715 kW h/year
1767 L/year 1.046 L/kW h 17,388 kW h/year
456 þ68 kg/year 0.252 þ 0.05 Kg/kW h 4484 þ 2267
38.2 kg/year 0.03 kg/kW h 1275 kW h/year
9.30%
50.60%
9.10%
9.70%
40.4 þ 59.7%
99.20%
2698 2163 5.19 530 2418 kW h/year 4.61 years
493 395 0.028 98.6 441 kW h/year 8 years
2119 1702 7.47 410 1903 kW h/year 5.86 years
2440 1959 8.94 471 2191 kW h/year 5.09 years
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The detailed comparative analysis of various hybrid power systems and the rating of all the components considered for the analysis are given in Table 4.
5. Results and discussions The simulation is performed using HOMER for each hour on a yearly basis. The inputs are the hybrid selected system resources data (wind speeds, solar irradiance, and load demand, the technical and economical specifications) described in the previous sections. The results of the various combinations of hybrid system are analysed and compared. The comparison criteria are given below. 5.1. Emissions (kg/year) Before simulating the power system, the emissions factor is determined (kg of pollutant emitted per unit of fuel consumed) for each pollutant. After the simulation, the annual emissions are calculated of that pollutant by multiplying the emissions factor by the total annual fuel consumption. The production of carbon dioxide, carbon monooxide, unburned hydro carbon, particulate matter, sulphur dioxide, nitrogen oxides and uses the values when calculating other Q & M cost are done. As seen from Table 4, (i) the diesel generator is working as a standalone (ii) grid connected diesel generator and (iii) the hybrid system connected with diesel generator has high total net present cost (T NPC). And they also produce maximum CO2 emission of 20967 kg/year, CO of 51.8 kg/year, sulphur dioxide of 42.1 kg/year and nitrogen oxides of 462 kg/year which causes environmental pollution. Those emissions can be reduced by relying on renewable energy sources. By using SPV/Wind/Battery or SPV/Wind Battery/FC hybrid system emissions can be removed or reduced. 5.2. Production (kWh/year) The electricity production of various systems depends on different combinations of hybrid system. Homer calculates the electricity that can be produced by all sources, power required to supply the load, unmet load, and excess electricity. From the simulation results, we notice that the capacity shortage in all cases is 0% except stand-alone DG system. So, these systems can be well adapted to meet 100% of the electric demand from the base transceiver station (BTS), plus the required operating reserve. This is a quality requirement for the mobile telephony sector where any unmet load situation or power shortage throughout the year is not admissible. The excess electricity produced by SPV/Wind/Battery hybrid system is 3926 kW h/year which can be stored in the battery. So, in case of production wise analysis SPV/Wind/Battery combination is viable. 5.3. Cost ($) The total net present cost (TNPC) is Hybrid Optimisation Model for Electric Renewable (HOMER) software's main economic output. HOMER ranks all systems according to the total net present cost (TNPC). The total net present cost (TNPC) of a system is the present value of all the costs that it incurs over its lifetime, minus the present value of all the revenue that it earns over its lifetime. Costs include capital costs, replacement costs, O&M costs, fuel costs, emissions penalties, and the costs of buying power from the grid. Revenues include salvage value and grid sales revenue.
HOMER calculates the total net present cost (TNPC) using the following equation: C NPC ¼ ðC ann;tot Þ=ðCRFði; Rproj ÞÞ
ðxviÞ
where CNPC is total net present cost, Cann,tot is total annualised cost ($/year), CRF is capital recovery factor, i is interest rate, and Rproj is project life time. From this simulation result it is evident that the system connected with diesel generator is quite costly. The hybrid configuration with SPV/ Wind/DG/ FC/Battery has the lowest NPC of $ 75515. The hybrid system SPV/Wind/ Battery has the next lowest NPC of $7, 34,662. So, SPV/Wind/DG/FC/Battery or SPV/Wind/ Battery could be the best choice. 5.4. Fuel Homer finds the energy released per kg of fuel consumed. The fuel cost taken is $0.8/L. This is used to calculate the generator fuel cost. HOMER calculates this value by multiplying the fuel price by the amount of fuel used by the generator in one year. The system configurations connected with DG and FC consumes fuel which again increases the cost of system. So, from the above table it is clear that the SPV/Wind/Battery hybrid system has no fuel consumption. So, the SPV/Wind/Battery system is viable. 5.5. Sensitivity analysis Sensitivity analysis eliminates all infeasible combinations and ranks the feasible combinations taking into account uncertainty of parameters. HOMER allows taking into account future developments, such as increasing or decreasing load demand as well as changes regarding the resources, for example wind speed variations or the diesel prices. Here, various sensitive variables are considered to select the best suited combination for the hybrid system to serve the load demand. 5.6. Optimisation results For each sensitivity case that it solves, HOMER simulates every system in the search space and ranks all the feasible systems according to increasing net present cost (TNPC). 5.7. Recommendations and conclusions Due to the steady growth of Telecom market and associated industries in India, there is a need to develop a new generation DC Power Supplies. It is true that the share of telecom growth in rural areas is much higher than metros. An autonomous energy system combining renewable energy sources, traditional sources and batteries or hydrogen as a storage medium was studied. This paper shows where solar, wind resources are available; deployment of solar, wind can satisfactorily meet energy need of remote Base Transceiver Station (BTS). The simulation results indicate that a hybrid system comprising of SPV/Wind/ Battery or SPV/Wind/Battery/FC can be feasible as this type of has no CO2 and CO emissions. Its environment-friendly nature makes it an attractive option to supplement the energy supply from other sources. The excess electricity can be stored in the battery and used for future use. The cost is also moderately less. Solar and wind are available freely and thus appears to be a promising technology to provide reliable power supply in the remote areas of India. This analysis exhibits that in order to eliminate diesel generator, solar and wind hybrid system can be adopted. The use of solar, wind hybrid system eliminates the emission of carbon
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dioxide. As the penetration of solar, wind system increases, the excess energy is increased. It can be stored and used for future purpose by using battery bank. So, the present arrangement of diesel powered telecom system can be replaced by the SPV/Wind/ Battery system. Also, the tower structure can suitably be modified to integrate wind turbine on the tower itself, saving space and cost of installations. Thus, we have the following advantages. (i) The non-conventional energy SPV/Wind hybrid power system is found to be technically feasible, emission less and cost effective in long run. (ii) Its environment-friendly nature makes it an attractive option to supplement the energy supply in rural areas. (iii) The service providers can have the additional benefit of carbon credit. (iv) Load is satisfied in an optimal way. (v) The land use can be reduced by suitably modifying the BTS tower to accommodate the wind generator.
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Contents lists available at ScienceDirect
Renewable and Sustainable Energy Reviews journal homepage: www.elsevier.com/locate/rser
Techno-economic evaluation of various hybrid power systems for rural telecom W. Margaret Amutha n, V. Rajini SSN College of Engineering, Kalavakkam, Chennai, Tamil Nadu, India
art ic l e i nf o
a b s t r a c t
Article history: Received 22 August 2014 Received in revised form 16 October 2014 Accepted 31 October 2014
Nowadays, utility has started to consider the green power technology for having a healthier environment. The green power technologies reduce combustion of fossil fuels and the consequent CO2 emission which is the principle cause of global warming. By maximising the use of the renewable energy, the usage of diesel generator for powering the base transceiver stations could be reduced or removed. This paper aims to investigate the economic, technical and environmental performance of various hybrid power systems for powering remote telecom. Simulations using Hybrid Optimisation Model for Electric Renewable (HOMER) software are performed to determine the Initial Capital, the Total Net Present Cost (TNPC), the Cost of Energy (COE) as well as the system Capacity Shortage of the different supply options. The simulation results suggest a suitable hybrid system which would be the feasible solution for generation of electric power for remote telecom. A detailed analysis, description and modelling of the system are also presented in this paper. & 2014 Elsevier Ltd. All rights reserved.
Keywords: Hybrid power system Optimisation Hybrid Optimisation Model for Electric Renewable (HOMER) Modelling
Contents 1. 2. 3.
4. 5.
n
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 554 Various hybrid systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 554 Modelling of the hybrid system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 554 3.1. Telecom load . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 554 3.2. Solar system model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 556 3.2.1. Solar photovoltaic system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 556 3.3. Wind turbine model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 556 3.3.1. Wind generator system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 556 3.4. Hydrogen storage fuel cell model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 557 3.5. Diesel generator model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 558 3.6. Battery model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 558 3.6.1. Battery bank. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 558 3.7. Converter model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 558 3.8. Grid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 558 HOMER solutions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 558 Results and discussions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 560 5.1. Emissions (kg/year) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 560 5.2. Production (kWh/year) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 560 5.3. Cost ($). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 560 5.4. Fuel. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 560
Corresponding author. E-mail addresses: [email protected] (W. Margaret Amutha), [email protected] (V. Rajini).
http://dx.doi.org/10.1016/j.rser.2014.10.103 1364-0321/& 2014 Elsevier Ltd. All rights reserved.
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5.5. Sensitivity analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.6. Optimisation results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.7. Recommendations and conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1. Introduction In the recent years, India's energy consumption has been increasing at a fast rate in the world due to population growth and economic development [1]. In India, Industrial consumers are the largest group of electricity consumers, followed by the domestic, agricultural and commercial consumers, in that order. The Indian telecommunications industry is one of the fastest growing industries in the world. India is currently adding 8–10 million mobile subscribers every month [2–5]. The power woes of India's telecom sector especially in the rural areas are quite apparent. It is a big challenge for the industry to meet its regular power requirements through traditional fuel, which is expensive [6]. Power deficits coupled with the rising cost of diesel pose a significant challenge to the mid-term growth and profitability of the telecommunication sector. Continued reliance on diesel will also substantially increase the environmental costs in the form of carbon emissions. The telecommunication sector is well placed to transit to a business model which relies on energy efficiency measures in combination with harnessing clean energy sources for its operations. This has compelled the industry to look for alternative green energy solutions. India has one of the highest potentials for harnessing the renewable energy. Renewable energies are also inexhaustible and clean. Renewable Energy Systems, particularly hybrid systems, have the additional advantage of being complimentary [7–9]. A hybrid system consists of two or more renewable energy sources used together to provide green energy, increased system efficiency as well as greater balance in energy supply. Thus, India's growing telecommunication tower industry can achieve substantial cost savings, while reducing their fossil-fuel dependence and carbon footprint, by switching to hybrid renewable power generated electricity supply. The various Renewable Energy Sources (RES) such as solar energy, wind energy, fuel cells and so on are used for telecommunications applications in the developing countries. Many literature references have discussed the economic cost analysis of combinations of hybrid power system [10–13]. Also, there is a lot of literature about design and analysis in the context of renewable energy power generations [14–19]. The main objective of this paper is to compare various hybrid renewable energy systems in all aspects like optimal cost allocation of each individual components present in the system, sensitivity variable solar radiation, wind speed, emissions, electricity production and to examine the best effective renewable based hybrid system configuration. For all the combinations of hybrid power system combinations, the meteorological data of solar radiation and wind speed is taken for Chennai [20–26], India with the Latitude 131 North and Longitude 80.181 East and the pattern of load consumption of typical telecom load profiles are suitably modelled. Here, Hybrid Optimisation Model for Electric Renewable (HOMER) software is used to analyse hybrid power system.
2. Various hybrid systems The intermittent nature of the solar and wind energy under varying climatic conditions requires a feasibility assessment and optimal sizing of hybrid solar and wind energy system. Without proper technical and financial feasibility study, the hybrid
560 560 560 561
alternative energy systems may end up in a poor efficient system. The intent behind this paper is to design, optimise and analyse an effective hybrid power system for a remote telecom station and to compare then with the existing Diesel power scheme. HOMER determines the operational strategy for a hybrid renewable energy system based on three tasks which are simulation, optimisation analysis and sensitivity analysis. It simulates the operation of the system based on the components chosen by the user. So, here the hybrid combinations chosen are (i) Diesel generator (ii) GridDiesel generator (iii) Solar PV-Diesel Generator (iv) Solar PV-Wind system-Diesel generator-Battery (v) Solar PV-Wind system-Diesel generator-Battery-Fuel cell (vi) Solar PV-Wind system-BatteryFuel cell (vii) Solar PV-Wind system-Battery. The architecture of various hybrid system is shown in Fig. 1(i)–(vi). HOMER simulates the system based on the estimation of installing cost, replacement cost, operation cost, fuel and interest. The list of various configurations of hybrid renewable energy will be tabulated from the lowest to the highest total net present cost (TNPC). It then determines the best feasible system configuration which can adequately serve the electric demand. The optimal solution is referring to the lowest total net present cost (TNPC). HOMER compares a wide range of equipment with different constraints and sensitivities to optimise the system design. The analysis is based on the technical properties of the system and the life-cycle cost (LCC) of the system. The LCC comprises the initial capital cost, cost of installation and operation costs over the system's life span. HOMER performs simulations to satisfy the given demand using alternative technology options and resource availability.
3. Modelling of the hybrid system Hybrid Optimisation Model for Electric Renewable (HOMER) software helps us to determine how different renewable, and hybrid systems interact with end-use demand. Based on the availability and potential of renewable energies in the particular area a hybrid energy system is modelled. 3.1. Telecom load The Telecom load (Base Transceiver Station-BTS) is considered as primary load. The BTS is a telecom infrastructure used to facilitate wireless communication between subscriber device and telecoms operator network. The global development of BTS is increasingly taking place in regions in which the power distribution grid often breaks down for long periods of time or where there is no access to the power distribution grid. So the BTS in such regions, diesel generators with batteries are used to back-up the grid for electricity supply and ensure network availability. But these require a high level of maintenance work and consume relatively high amounts of diesel fuel for low level outputs. As a result diesel generators incur high operating expenses. The growing cost of energy (COE) due to increasing diesel prices and concerns over rising greenhouse emissions have caused the telecom companies to focus on better power management methods. The price of diesel since 2004 is shown in Fig. 2.
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Fig. 1. Architecture of system with (i) DG and (ii) Grid/DG. Architecture of hybrid renewable energy system with (iii) SPV/DG, (iv) SPV/Wind/DG/Battery, (v) SPV/Wind/DG/ FC/Battery, (vi) SPV/Wind/FC/Battery and (vii) SPV/Wind/Battery.
The conventional power system feeding a telecom load is shown in Fig. 3. The minimum-size of 1.3 kW is taken for analysis in this paper. There are two types of BTS load. One is indoor BTS and the other is outdoor BTS. Most indoor BTS require air conditioning. For outdoor applications there is no requirement for air conditioning. Daily telecom load profile considered is shown in Fig. 4. The data were measured for the total hourly basis
daily load requirement of a rural telecom. General average power consumption of BTS load is given in Table 1. The conventional topology for BTS shown in Fig. 5 uses a separate dc–dc converter (power conditioning circuit) for each of the renewable energy power sources. These individual converters are connected to a common DC bus which in turn feeds the telecom load. This system makes the system more bulky and expensive.
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Fig. 2. Diesel price since 2004.
Fig. 3. Conventional system feeding a telecom load.
Table 2 Monthly clearness index and solar radiation.
Fig. 4. Daily load profile.
Table1 Typical average power consumption. S.no
Type of BTS
Typical average consumption (kW)
1 2 3
2þ 2þ 2 4þ 4þ 4 6þ 6þ 6
1.3 2 3.5
Month
Clearness index
Radiation
January February March April May June July August September October November December
0.491 0.568 0.632 0.658 0.633 0.562 0.500 0.483 0.485 0.427 0.403 0.429
4.930 5.890 6.640 6.720 6.120 5.240 4.730 4.800 5.010 4.420 4.060 4.240
where Epv is energy (kWh), A is total solar panel area (m2), P is solar panel yield (%), H is annual average solar radiation on tilted panels, PR is performance ratio, coefficient for losses (range is between 0.5 and 0.9; default value is 0.75).
3.2. Solar system model 3.3. Wind turbine model The latitude of the site considered Chennai is 131 North and the longitude is 80.181 East. The time zone is GMTþ 5:30 India. The monthly solar irradiation horizontal data are taken for simulation. The solar system capacity is 2kW. The projected life time of the PV system is 20 years. The plant considered has no tracking system. Monthly clearness index and radiation in the region of Chennai, Tamil Nadu is taken from the website of NASA and is shown below in Table 2 and Fig. 6. 3.2.1. Solar photovoltaic system Based on the solar radiation available on the tilted surface the hourly energy output (EPV) of the PV generator can be calculated according to the following equation: EPV ¼ AnP nH nP R
ðiÞ
The monthly wind speed data is considered and measured at 16 m height. The projected life time of the wind system is 20 years. The wind system capacity is 3 kW. The power curve is shown in Fig. 7. The yearly wind speed of the study region is shown in Table 3. Fig. 8 shows the scaled data monthly averages for wind system. 3.3.1. Wind generator system Hourly energy generated (EWES) by wind generator with rated power output (PWES) is defined by the following expression: P WE ¼ 1=2 n ρ nA n V 3 n C p ðλ; βÞn ηt n ηg
ðiiÞ
EWES ðt Þ ¼ P WES ðt Þ n t
ðiiiÞ
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557
Fig. 5. Conventional topology.
Fig. 6. Solar radiation curve. Scaled data Monthly Averages
1.2 max daily high mean
1.0 0.8 0.6
daily low min
0.4
where ρ is the density of air in 1.22 kg/m3, CP is performance coefficient of the turbine, λ is tip speed ratio of the rotor blade tip speed to wind speed, β is blade pitch angle as 01, v is wind speed (m/s), ηt is wind turbine efficiency, ηg is generator efficiency, and A is area in m2
0.2 0.0 Jan Feb Mar Apr May Jun Jul
Aug Sep Oct Nov Dec Ann
3.4. Hydrogen storage fuel cell model
Month
Fig. 7. Scaled data monthly averages for solar.
Table 3 Wind speed data.
Fuel Cell (FC) is available in different configurations, power ranges, type of electrodes and operating characteristics. Proton Exchange Membrane (PEM) FC has a good start up and shut down characteristics. So, 2 kW fuel cell is considered. The projected life time is 15,000 h. The basic structure of PEM fuel cell has two electrodes (anode and cathode) separated by a solid membrane. In the hydrogen storage system, surplus renewable power goes to an electrolyser which produces hydrogen. Hydrogen goes into a storage tank to be consumed by the fuel cell when required. Hydrogen fuel is fed continuously to the anode and air is fed to the cathode. The internal chemical reaction is as follows: H2 þ 1=2O2 - H2 O
Month
Wind speed (m/s)
January February March April May June July August September October November December
3.900 3.500 3.500 3.500 3.800 4.400 4.200 4.100 3.000 2.800 3.600 4.200
ðivÞ
The hydrogen consumption at rated power Pfc kW of one hour is calculated by HY fc ¼ ½ðP fc n3600Þ=ð2V fc nFÞ
ðvÞ
where HYfc is the amount of hydrogen consumed by fuel cell, Pfc is output power of fuel cell, Vfc is output voltage of fuel cell, F is Faraday's constant. Hydrogen can be produced by the decomposition of water into its elementary components by passing the electric circuits. A water electrolyser consists of several cells connected in series. Two electrodes of the electrolyser are separated by electrolyte. Electrical current through the electrolyser enables the decomposition
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Fig. 8. Scaled data monthly averages for wind.
of water into hydrogen and oxygen by H2 O þelectricity-H2 þ1=2 O2
ðviÞ
According to Faraday's law the amount of Hydrogen produced by rated power Pfc kW electrolyser in one hour is calculated by HY ele ¼ ½ðP fc n3600Þ=ð2V ele nFÞ
ðviiÞ
where HYele is the amount of hydrogen produced by electrolyser, Pele is rated power of electrolyser, Vele is working voltage of electrolyser, and F is Faraday's constant. Hydrogen energy produced by the electrolyser provides solar energy storage in excess demand. The method of transferring the capacity of hydrogen tanks to the unit kWh is given by Etank ðkWhÞ ¼ M tank ðmolÞn2n10 3 kg=mol nLHV kWh=kg ðviiiÞ where Etank and Mtank is the size of hydrogen tank in kWh and LHV is the low heat value of hydrogen in kWh/kg.
On the other hand, when the load demand is greater than the available energy generated, the battery bank is in discharging state. Therefore, the available battery bank capacity at hour t can be expressed as EBat ðt Þ ¼ EBat ðt 1Þ Eneeded ðt Þ
Let d be the ratio of minimum allowable SOC voltage limit to the maximum SOC voltage across the battery terminals when it is fully charged. So, the Depth of Discharge (DOD) DOD ¼ ð1 dÞn100
SOC min ¼ ð1–DODÞ=100 3.7. Converter model
Generating sets are selected based on the electrical load they are intended to supply. 2 kW diesel generator power is considered to supply 1.3 kW BTS load. The capital cost considered is $900 and the replacement cost taken is $ 850. The projected life time is 15,000 h.
EREC–OUT ðt Þ ¼ EREC IN ðt ÞnηREC
3.6. Battery model
EREC IN ðt Þ ¼ ESUR AC ðtÞ
The variations of solar and wind energy generation do not match the time distribution of the demand. Therefore, power generation systems dictate the association of battery storage facility to smooth the time–distribution mismatch between the load and solar/wind energy generation and to account for maintenance of the systems. Batteries are considered as a major cost factor in small-scale stand-alone power systems. The battery stacks may contain a number of batteries ranging from 0 to 500 units. A battery of 6 V, 1.34 kW h has been chosen. Number of batteries per string considered is 8.
ESUR AC ðtÞ ¼ EDG ðtÞ
EBat ðt Þ ¼ Battery Capacity ðAhÞ=Battery Current ðAÞ
ðixÞ
ðxiÞ
DOD is a measure of how much energy has been withdrawn from a storage device, expressed as a percentage of full capacity. The maximum value of SOC is 1, and the minimum SOC is determined by maximum depth of discharge (DOD)
3.5. Diesel generator model
3.6.1. Battery bank The battery state of charge (SOC) is the cumulative sum of the daily charge/discharge transfers. At any hour (t) the state of battery is related to the previous state of charge and to the energy production and consumption situation of the system during the time from t 1 to t. During the charging process, when the total output of all systems exceeds the load demand, the available battery bank capacity at hour (t) can be described by
ðxÞ
ðxiiÞ
The rectifier model is given below: ðxiiiÞ
EREC OUT(t) is hourly energy output from rectifier, kWh, EREC IN(t) is hourly energy input to rectifier, kWh, and ηREC is efficiency of rectifier. ðxivÞ ðxvÞ
ESUR AC(t) is the amount of surplus energy from AC source, kWh, EDG (t) is surplus energy from diesel generator to DC power of constant voltage, when the energy generated by the hybrid energy system exceeds the load demand. 3.8. Grid Grid rating is divided in to three: (i) off peak (ii) shoulder and (iii) peak. For off peak $ 20,000 k/Wh price is considered. For shoulder $ 30,000 k/Wh and for peak $ 50,000 k/Wh is considered respectively.
4. HOMER solutions HOMER helps us to determine how different renewable, and hybrid systems interact with end-user demand. Based on the availability and potential of renewable energies in the particular area various combinations of energy systems can be chosen. The choice of the best combination of hybrid sources can be made after comparing their performance.
Table 4 Comparative analysis of various configurations of hybrid systems. Description
DG
Grid/DG
SPV/DG
SPV/WES/Battery/DG
SPV/WES/Battery/DG/FC
SPV/WES/Battery/FC
SPV/WES/Battery
1
DG Inverter Rectifier Solar system Wind system Battery Grid Fuel Cell Emissions (Kg/ Year) Carbon dioxide Carbon monoxide Unburned hydocarbon Particulate matter Sulphur dioxide Nitrogen oxides Production (kWh/ year) Electricity Excess electricity DC load Unmet load kW h/ year Mean electrical output Capacity shortage Cost ($) Total net present cost Levelized cost of energy Operating cost Fuel Fuel consumption Specific fuel consumption Fuel energy input Efficiency Mean electrical efficiency Battery Energy in kWh/Year Energy out kWh/year Storage depletion Losses Annual throughput Expected life
2 kW 2 kW 2 kW
0.5 kW 2 kW 2 kW
2 kW 2 kW 2 kW 2 kW
2 kW 2 kW 2 kW 2 kW 3 kW 48 V
2 kW 2 kW 2 kW 2 kW 3 kW 48 V
2 kW 2 kW 2 kW 3 kW 48 V
4 kW 3 kW 48 V
2 kW
2 kW
2
3
4
5
6
7
2 kW
20,967 51.8 5.73 3.9 42.1 462
4100 4.09 0.453 0.308 13.9 41.7
18,657 46.1 5.1 3.47 37.5 411
4653 11.5 1.27 0.866 9.34 102
1199 3.4 0.377 0.257 2.41 30.4
0.391 0.249 0.0275 0.0187 0 2.22
0 0 0 0 0 0
7290 290 5950 0.000151 832 W 0.0669
3956 þ 3132 7.78E 05 5950 þ 88 0.0001 500 W 0
3489 þ 6415 ¼9804 3200 5950 0.0000852 721 W 0
3489 þ2982 þ 1690 1456 5950 2.98E-07 1030 þ 1710W 0
3489 þ 2982 þ 1811þ 1354 159 5950 þ3157 0 1030 þ 1710W 0
3489 þ 2982 þ 1264 97.3 5444þ 1777 0 1030 þ1710 W 0
6979 þ2982 3926 5554 0 1030 þ1710 W 0
12,30,683 16.182/kW h 95,537/year
16,88,953 22.207/kW h 13,1386/year
12,27,382 16.138/kW h 94,966/year
2,91,274 3.830/kW h 20,118/year
75,515 0.997/kW h 2614/year
887,317 12,751/kW h 65,915/year
734,662 10.347/kW h 54,083/year
7962 L/year 1.092 L/kW h 78,349 kW h/year
629 L/year 0.201 L/kW h 6189 kW h/year
7085 L/year 1.122 L/kW h 69,715 kW h/year
1767 L/year 1.046 L/kW h 17,388 kW h/year
456 þ68 kg/year 0.252 þ 0.05 Kg/kW h 4484 þ 2267
38.2 kg/year 0.03 kg/kW h 1275 kW h/year
9.30%
50.60%
9.10%
9.70%
40.4 þ 59.7%
99.20%
2698 2163 5.19 530 2418 kW h/year 4.61 years
493 395 0.028 98.6 441 kW h/year 8 years
2119 1702 7.47 410 1903 kW h/year 5.86 years
2440 1959 8.94 471 2191 kW h/year 5.09 years
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The detailed comparative analysis of various hybrid power systems and the rating of all the components considered for the analysis are given in Table 4.
5. Results and discussions The simulation is performed using HOMER for each hour on a yearly basis. The inputs are the hybrid selected system resources data (wind speeds, solar irradiance, and load demand, the technical and economical specifications) described in the previous sections. The results of the various combinations of hybrid system are analysed and compared. The comparison criteria are given below. 5.1. Emissions (kg/year) Before simulating the power system, the emissions factor is determined (kg of pollutant emitted per unit of fuel consumed) for each pollutant. After the simulation, the annual emissions are calculated of that pollutant by multiplying the emissions factor by the total annual fuel consumption. The production of carbon dioxide, carbon monooxide, unburned hydro carbon, particulate matter, sulphur dioxide, nitrogen oxides and uses the values when calculating other Q & M cost are done. As seen from Table 4, (i) the diesel generator is working as a standalone (ii) grid connected diesel generator and (iii) the hybrid system connected with diesel generator has high total net present cost (T NPC). And they also produce maximum CO2 emission of 20967 kg/year, CO of 51.8 kg/year, sulphur dioxide of 42.1 kg/year and nitrogen oxides of 462 kg/year which causes environmental pollution. Those emissions can be reduced by relying on renewable energy sources. By using SPV/Wind/Battery or SPV/Wind Battery/FC hybrid system emissions can be removed or reduced. 5.2. Production (kWh/year) The electricity production of various systems depends on different combinations of hybrid system. Homer calculates the electricity that can be produced by all sources, power required to supply the load, unmet load, and excess electricity. From the simulation results, we notice that the capacity shortage in all cases is 0% except stand-alone DG system. So, these systems can be well adapted to meet 100% of the electric demand from the base transceiver station (BTS), plus the required operating reserve. This is a quality requirement for the mobile telephony sector where any unmet load situation or power shortage throughout the year is not admissible. The excess electricity produced by SPV/Wind/Battery hybrid system is 3926 kW h/year which can be stored in the battery. So, in case of production wise analysis SPV/Wind/Battery combination is viable. 5.3. Cost ($) The total net present cost (TNPC) is Hybrid Optimisation Model for Electric Renewable (HOMER) software's main economic output. HOMER ranks all systems according to the total net present cost (TNPC). The total net present cost (TNPC) of a system is the present value of all the costs that it incurs over its lifetime, minus the present value of all the revenue that it earns over its lifetime. Costs include capital costs, replacement costs, O&M costs, fuel costs, emissions penalties, and the costs of buying power from the grid. Revenues include salvage value and grid sales revenue.
HOMER calculates the total net present cost (TNPC) using the following equation: C NPC ¼ ðC ann;tot Þ=ðCRFði; Rproj ÞÞ
ðxviÞ
where CNPC is total net present cost, Cann,tot is total annualised cost ($/year), CRF is capital recovery factor, i is interest rate, and Rproj is project life time. From this simulation result it is evident that the system connected with diesel generator is quite costly. The hybrid configuration with SPV/ Wind/DG/ FC/Battery has the lowest NPC of $ 75515. The hybrid system SPV/Wind/ Battery has the next lowest NPC of $7, 34,662. So, SPV/Wind/DG/FC/Battery or SPV/Wind/ Battery could be the best choice. 5.4. Fuel Homer finds the energy released per kg of fuel consumed. The fuel cost taken is $0.8/L. This is used to calculate the generator fuel cost. HOMER calculates this value by multiplying the fuel price by the amount of fuel used by the generator in one year. The system configurations connected with DG and FC consumes fuel which again increases the cost of system. So, from the above table it is clear that the SPV/Wind/Battery hybrid system has no fuel consumption. So, the SPV/Wind/Battery system is viable. 5.5. Sensitivity analysis Sensitivity analysis eliminates all infeasible combinations and ranks the feasible combinations taking into account uncertainty of parameters. HOMER allows taking into account future developments, such as increasing or decreasing load demand as well as changes regarding the resources, for example wind speed variations or the diesel prices. Here, various sensitive variables are considered to select the best suited combination for the hybrid system to serve the load demand. 5.6. Optimisation results For each sensitivity case that it solves, HOMER simulates every system in the search space and ranks all the feasible systems according to increasing net present cost (TNPC). 5.7. Recommendations and conclusions Due to the steady growth of Telecom market and associated industries in India, there is a need to develop a new generation DC Power Supplies. It is true that the share of telecom growth in rural areas is much higher than metros. An autonomous energy system combining renewable energy sources, traditional sources and batteries or hydrogen as a storage medium was studied. This paper shows where solar, wind resources are available; deployment of solar, wind can satisfactorily meet energy need of remote Base Transceiver Station (BTS). The simulation results indicate that a hybrid system comprising of SPV/Wind/ Battery or SPV/Wind/Battery/FC can be feasible as this type of has no CO2 and CO emissions. Its environment-friendly nature makes it an attractive option to supplement the energy supply from other sources. The excess electricity can be stored in the battery and used for future use. The cost is also moderately less. Solar and wind are available freely and thus appears to be a promising technology to provide reliable power supply in the remote areas of India. This analysis exhibits that in order to eliminate diesel generator, solar and wind hybrid system can be adopted. The use of solar, wind hybrid system eliminates the emission of carbon
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dioxide. As the penetration of solar, wind system increases, the excess energy is increased. It can be stored and used for future purpose by using battery bank. So, the present arrangement of diesel powered telecom system can be replaced by the SPV/Wind/ Battery system. Also, the tower structure can suitably be modified to integrate wind turbine on the tower itself, saving space and cost of installations. Thus, we have the following advantages. (i) The non-conventional energy SPV/Wind hybrid power system is found to be technically feasible, emission less and cost effective in long run. (ii) Its environment-friendly nature makes it an attractive option to supplement the energy supply in rural areas. (iii) The service providers can have the additional benefit of carbon credit. (iv) Load is satisfied in an optimal way. (v) The land use can be reduced by suitably modifying the BTS tower to accommodate the wind generator.
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