Sustainable energy generation using hybrid energy system for remote hilly rural area in India

Abstract

Hybrid energy systems are renewable energy system combined in a complementary fashion to ensure dependable power supply at competitive cost. Diesel generators (DGs) are also added here as a back-up source of supply. For remote areas far from a transmission grid, these systems can provide a reliable and cost-effective supply. Addition of DG could instigate environmental pollution in such remote unpolluted areas. In the present work, optimal sizing of hybrid energy system has been attempted for a remote village cluster of Uttarakhand (India) to make available desired power supply at minimum environmental effluence. Hybrid Optimization Model for Electrical Renewable (HOMER) software from National Renewable Energy Laboratory, USA has been employed to attain the objective. The software offered several feasible systems, ranked on the basis of net present cost (NPC). All such systems are further analysed for emissions they have made in the environment. Hence, the optimal system fulfilling the criteria of minimal environmental degradation with sufficiently minimum NPC has been searched for. In the present work, the most appropriate system offered on the basis of NPC is the one which has five wind turbines (10 kW each), one DG (65 kW) and 25 batteries (6 V, 6.94 kW h each). The NPC of the system is $1,252,018, whereas its initial capital cost and levelised cost of energy (COE) are $94,233 and $0.292/kW h, respectively. After further analysis of all the feasible systems on the basis of environmental effluence, the most feasible system explored is the one which has minimal emissions of various pollutants such as carbon dioxide, carbon monoxide, hydrocarbon, particulate matter, sulphur dioxide and nitrous oxide. The system has been obtained on a compromised NPC of $1,270,921 with a capital cost of $148,133 and COE of $0.296/kW h. Components of the system include five wind turbines (10 kW), a 9 kW PV panel and a 65 kW DG along with 30 batteries (6 V, 6.94 kW h each). The system so obtained would prove to be a feasible, optimally sized and sustainable power supply alternative for remote unelectrified hilly rural area.

Keywords:

• hybrid energy system
• net present cost
• optimal system
• renewable energy

1. Introduction

In the past few decades, renewable energy sources have received greater interest and considerable attention has been given to develop efficient energy conversion and utilisation techniques. A majority of the population in India reside in villages and a large number of villages are not served by the national grid due to the high cost involved in erection and maintenance of transmission lines in comparison to low power consumption in such areas (Nayar 1995). Conventional energy sources have long gestation period and draw heavily on exhaustible deposits, affecting the ecological balance adversely. Rapid depletion of fossil fuel resources necessitated an urgent search for alternative energy sources to cater the present-day demand (Elhadidy 2002, Elhadidy and Shaahid 2004). New and renewable energy sources are economically viable and do not suffer from such disadvantages. These alternative energy sources such as solar, wind, biomass, small hydro, etc. have attracted energy sectors to generate power on large scale (Lowe and Lloyd 2001). It is evident that the above renewable energy sources alone cannot provide continuous supply of energy due to seasonal and periodic variations; the effort of doing so result in a high cost system. In this situation, hybrid energy systems are the apparent choice. These systems combine two or more renewable sources along with a back-up source as per the availability of resources and load demand in that area. Such systems are more dependable and have reduced life-cycle cost.

2. Literature review

Sufficient research work has been reported so far based on hybrid energy systems. A brief review of some of the important reported research is given below.

Castle et al. (1981) became pioneers in the field by evaluating merits of hybrid system over standalone PV or wind system. Borowy and Salameh (1994) determined the best fit size of PV array and wind turbine in a wind/PV hybrid system by the least-squares method. Markwart (1996) applied a graphical construction method to determine the optimum size of a PV array and wind turbine in a wind/PV hybrid system, and in the same year, Bagul et al. (1996) determined the optimum size of a PV array and battery storage for a standalone wind/PV hybrid system using a ‘three-event probability density function’. Techno-economic analysis of different sizing methods of the hybrid system has been carried out by Celik (2003). A low-cost, high reliability system consisting of PV, battery and LPG hybrid for remote telecom application has been discussed by Salas and Olias (2000), whereas Shahid and Elhadidy (2007) examined the effect of PV/battery penetration on the cost and operational hours of diesel generator (DG) supplying power to the remote areas of Dharan (UAE).

A solar/geothermal system has been proposed for electricity generation by Lentz and Almanza (2006). A solar gas turbine hybrid system has been discussed by Gou et al. (2007), in which solar energy is used to generate additional steam and the heat released by the exhaust of the gas turbine is used for water preheating and steam superheating.

Somerville and Stevenson (1987) discussed the possibilities of wind and micro-hydro hybrid for isolated communities and a hybrid wind/hydro system has been evaluated for its feasibility in an island of Greece by Bakos (2002). Jaramillo et al. (2004) discussed about the complementary working of hydro and wind power for a case study in Mexico. Hu and Chen (2005) offered a wind/diesel hybrid generation unit in which both wind and DG operated in variable speed mode, whereas Liu and Islam (2006) pointed out the site and size factor on the reliability of the wind/diesel/battery hybrid system. Recently, analysis of a small wind-hydrogen standalone hybrid energy system has been performed by Khan and Iqbal (2009).

3. Problem description

An optimised model of a hybrid energy system has been endeavoured in the present work to supply power to a remote village cluster. The model so obtained would be a sustainable power supply alternative for the intended area. The area is typically a hilly village cluster of Jaunpur block of Tehri Garwal district in Uttarakhand state of India. Jaunpur block of Tehri Garhwal district has been divided into four zones. The selected village area is in zone 4 of the block. The block consists of 259 villages out of which 202 villages are electrified and 57 villages are unelectrified. The intended village cluster in zone 4 consists of 12 unelectrified villages. These villages have 241 households with 1403 inhabitants (Akella et al. 2007). These hilly villages have difficult access and residents therein have poor standard of living. The density of population is also very sparse. All these facts did not catch the attention of utilities for extension of the grid in such remote regions. A hybrid energy system is an appropriate power supply alternative in such situation. It is attempted here to attain low-cost dependable power supply through a hybrid energy system by optimally combining suitable renewable resources of the study area. Hybrid Optimization Model for Electrical Renewable (HOMER) software from National Renewable Energy Laboratory (NREL) has been applied to accomplish this objective. HOMER is a complementary software available on the website of NREL (http://www.nrel.gov/homer).

4. Methodology

Planning and designing a hybrid energy system is a highly complex problem. It is due to the intermittent nature of renewable energy sources, demand uncertainties, nonlinear characteristic of components involved and the fact that sizing and operating strategies of hybrid systems are interdependent (Ashok 2007).

In the present work, a hybrid power supply scheme has been proposed based on the availability and potential of the renewable sources of the intended village area. To find a suitable system type and configuration, i.e. apposite technical combination with an appropriate number and size of components, HOMER search space has been provided with various number and size of components. These components are renewable resource converters, storage devices, back-up devices such as DG and power conditioning equipment. In the optimisation process, HOMER simulates all the systems with various components, in their respective search space. An hourly time series simulation for every possible system type and configuration has been performed for one year. A feasible system will be the one which would satisfy the load demand. HOMER discards all infeasible combinations and ranks the feasible systems according to the increasing net present cost (NPC). In the present work, all such feasible systems are further analysed for emissions they have made in the environment. Hence, the optimal system fulfilling the criteria of minimal environmental degradation with a sufficiently minimum NPC has been searched out. Such a system would be the desired system to fulfil the sustainable energy requirement of the remote unelectrified study area.

5. Proposed scheme

Based on the availability and potential of renewable energies in the remote village cluster of Tehri Garhwal district, a hybrid energy system consisting of wind turbine and solar PV system along with a DG back-up, battery storage and power conditioning equipment is proposed, as shown in Figure 1.

Figure 1 Proposed scheme of hybrid energy generation for the study area.

The details of various parameters such as solar and wind resource potential of the area, load profile of the intended village cluster and description of various components, i.e. size, number and cost of wind turbine, PV array, DG, battery, converter, etc. in the proposed hybrid scheme have been discussed in the following sections. All these values are entered into the input window of the respective component.

5.1 Solar and wind resource potential

Annual average global solar radiation of the study area is 5.13 kW h/m² per day. Potential of solar radiation of the area has been obtained from the website of Ministry of new and renewable energy sources (Solar Radiant energy over India, available at http://www.mnes.nic.in/sec/solar-resources.htm). The website provided yearly data of direct, global, diffused and reflected solar radiation for some chosen places in the country. Data for any specific area could be determined by the radiation network showing solar radiant exposure throughout the country for the whole year. In the present work, global solar radiant exposure data have been used for calculation. Figure 2(a) shows the details of the solar radiation in the area.

Figure 2 (a)–(b) Details of the wind and solar resource potential of the study area.

The annual average wind speed in the area is 5.01 m/s. Details of the wind potential are made available from the published literature by Centre for Wind Energy Technology (‘Wind energy resources survey in India’ Vol VI 2001). The details are available for some selected states of the country where the wind potential is found to be significant. Recently, the potential has been observed and found significant for the Uttarakhand state. A place named Bachhelikhal in Tehri Garhwal district near the selected study area is the meteorological station for observing the wind potential and the same data have been used in the present study. The wind resource potential of the study area has been depicted in Figure 2(b).

5.2 Connected load

Determination of the average connected load of households in the hilly rural area, which is not yet electrified, has been made feasible by the estimation method. The expected consumption pattern of the area throughout the year has been estimated, keeping in mind demographic characteristics of the local population, land features, density of population in each village, prevailing climate and social requirements of inhabitants. A previous work done for load estimation in the rural area has been a great help in determining the load requirement for this rural hilly area (Nouni et al. 2008). The expected load consumption profile of the area is shown in Figure 3. The daily load requirement of the intended village cluster is found to be 1101 kW h per day and the peak load is found to be 65 kW.

Figure 3 Expected yearly load consumption profile of the area.

5.3 Size and cost of equipment

Capital, replacement and operation and maintenance (O&M) costs play a vital role in determining the optimal size of generation mix in a hybrid energy system. The capital cost is the initial investment cost of a component, whereas the replacement cost here is the cost of replacing that component at the end of its lifetime. It is different from the salvage value of a component. The O&M cost is the annual operating and maintaining cost of any component (http://www.nrel.gov/homer).

Various components of the proposed system, i.e. wind turbine, PV system, DG, battery, etc. have been provided a suitable range of sizes as input in their respective input windows in HOMER. While selecting sizes for a component, various factors such as load requirement of the area, availability in the market, place of installation and cost-effectiveness of instruments have to be kept in mind. These ranges of sizes build the search space for simulation so that the optimal system would be searched out from all feasible systems satisfying the power balance equation. The size and cost of various components of the proposed hybrid system are enumerated here.

5.3.1 Wind turbine

A 10 kW horizontal axis wind turbine (number ranges from 0 to 5) has been used for simulation, keeping all the above factors in mind. The cost of the turbine has been obtained from a thorough market study. It is preferred to have an Indian option as that would be more suitable for home conditions, free from costly delivery charges and after sales service and maintenance would be easier. For this purpose, AR-10000 wind turbine has been selected for the simulation (Vaigunth Ener Tek (p) Ltd Chennai (Tamilnadu) India, http://www.v-enertek.com). The capital, replacement and O&M costs of the turbine have been given in Table 1 (Wind energy prospects and potential 2004).

5.3.2 PV array

PV array draws a major chunk of investment in the establishment of the overall solar PV system. In the present work, PV array ranging from 0 to 30 kW capacities has been used for simulation. For the cost of array, market has been searched out and the cost used as input is the average cost of a PV array in the Indian market (Solar Photovoltaic – prospects and potential 2004). The capital, replacement and O&M costs of a PV array utilised in the simulation are specified in Table 1.

Table 1 Details of the capital, replacement and O&M costs of various equipment employed in the proposed scheme.

Component detail	Capital cost ($)	Replacement cost ($)	O&M cost ($/yr)
Solar PV system (1 kW)	5600	5000	10
Wind turbine (10 kW)	11,000	10,000	110
Battery (6V, 6.94 kW h)	700	600	0.1
Converter (1 kW)	140	126	15
DG (70 kW)	18,000	18,000	0.150 ($/h)

5.3.3 Diesel generator

DG works as a back-up generator in the hybrid energy system, hence the size of the DG in the system will be at least equal to or more than the peak load of the intended area. In the present case, the peak load of the area is 65 kW, hence the DG size may range from 65 to 100 kW. The cost of a 70 kW DG as obtained after market search is $18,000, whereas for a 100 kW DG it will be $25,000. The detail of these costs is shown in Table 1 as used in the simulation (http://www.reddygenerators.com).

5.3.4 Battery

Battery is required for storage, hence the size of the battery should be sufficient to supply the load in days of emergency. Battery storage is actually an array of battery stack. For the present work, a battery of 6 V, 6.94 kW h has been chosen. Its number for simulation ranges from 0 to 50. The cost of a battery is $700 (http://www.nmsea.org/Curriculum/Primer/from_oil_wells_to_solar_cells.htm) and its replacement and O&M costs as used for simulation are shown in Table 1.

5.3.5 Converter

Converter can work as a rectifier or an inverter. Inverter mode is required to supply power from the PV system or battery to the load, whereas the rectifier mode will work to store excess power from the DG to the battery. In the present case, the size of the inverter ranges from 0 to 50 kW for simulation purpose. The cost of the converter is again searched out from a market study (http://www.nmsea.org) and the average cost which is used for simulation is shown in Table 1. The search space showing various sizes of components is depicted in Table 2.

Table 2 HOMER search space showing various sizes of components used for simulation.

No.	PV array (1 kW)	Wind turbine (10 kW)	DG (kW)	Battery (6V, 6.94 kW h)	Converter (kW)
1	0	0	60	0	20
2	1	1	65	5	25
3	2	2	70	10	30
4	3	3	75	15	35
5	4	4	80	20	40
6	5	5	85	25	45
7	6	–	90	30	50
8	7	–	95	35	55
9	8	–	100	40	60
10	9	–	–	45	65
11	10	–	–	50	–
12		–	–	–	–
13		–	–	–	–
14	⋮	–	–	–	–
15		–	–	–	–
16	30	–	–	–	–

Diesel cost plays an important role while designing a hybrid energy system as DG is an integral part of the hybrid supply scheme to ensure a reliable power supply. In the present study, the cost of diesel is the existing diesel cost in market in $/l. The cost of diesel, which has been entered into the input window, is 0.8 $/l.

Replacement cost of a component is the cost of replacing the component at the end of its lifetime, hence the replacement cost of the solar PV system is less than the capital cost of the same as the foundation of a PV array need not be replaced after the lifetime of the PV array. Second, the cost of the PV cell is expected to be reduced after 20 years, compared to the present cost. In the case of the wind turbine, only the turbine needs to be replaced after its lifetime and not the tower. Hence, its replacement cost will be reduced to the present capital cost. For DG, however, the capital and replacement costs are the same as the whole DG needs to be replaced after its lifetime.

The O&M cost for the solar PV system will not be much as there is no moving part associated with it, whereas there will be 1% O&M cost associated with the wind turbine. However, the O&M cost of DG has been obtained from the published literature (Akella et al. 2007).

6. Results and discussion

Selection and sizing of components of the hybrid energy system has been exercised using NREL's HOMER software. HOMER is a general purpose software for hybrid energy system design and is helpful in modelling standalone and grid-connected power supply systems. Various inputs required to be supplied in the software are renewable resource potential (one year data), load demand of the area (estimated one year data), component technical details, size and costs, constraints, controls, dispatch strategy, project lifetime, annual real interest rate, etc. HOMER performs hundreds or thousands of hourly simulations (to ensure best possible matching of demand and supply) and offers a list of feasible schemes ranked on the basis of the NPC.

The hybrid system simulated in the present investigation consists of different combinations of the PV and wind energy system supplemented with battery bank and DG. The study explores a suitable mix of various interlinked parameters such as PV array power (kWp), wind turbine capacity (KW), battery number and size and DG capacity to match the load profile of the area. A snapshot of the result showing various feasible combinations ranked on the basis of the total NPC of the system has been depicted in Table 3.

Table 3 A snapshot of the results showing feasible supply schemes for the study area ranked in the order of increasing NPC.

Notes: Gen1, generator 1; Batt, battery; Conv., converter; Disp. Strgy, display strategy; Ren. Frac, renewable fraction.

There were 200 feasible systems obtained after simulation of various systems. The simulation and optimisation process took about 4 h 25 min 40 s on an Intel Pentium IV 3.00 GHz system. The optimisation results suggests that, on the basis of least NPC, the most appropriate system is the one having five wind turbines and a 65 kW DG along with 25 batteries and a 35 kW converter. The NPC of this system is $1,252,018 and the initial capital is $94,233. However, such remote unpolluted areas may degrade the environment due to the presence of DG in the proposed scheme. DG are unavoidable in such schemes due to their dependability, therefore a system has to be searched out having least environmental degradation with sufficiently minimum NPC. All feasible systems are further analysed for the emissions they have made in the environment. The level of various pollutants, i.e. carbon dioxide, carbon monoxide, unburned hydrocarbons, particulate matter, sulphur dioxide and nitrous oxide, has been examined for their emission in the environment. Figure 4(a)–(f) shows the graphical plot of emission in kg/year of all these pollutants for some significant feasible systems. The x-axis shows the rank of feasible systems on the basis of the NPC as offered by the software.

Figure 4 (a)–(f) Emission of carbon dioxide, carbon monoxide, hydrocarbons, particulate matter, sulphur dioxide and nitrous oxide, respectively, for various feasible systems. The x-axis shows the rank of feasible systems. The number written beneath the plot line in each figure indicates the minimum level of pollution of CO₂, CO, HC, particulate matter, SO₂ and NO _x , respectively.

The figure illustrates the emission of these pollutants for some significant feasible systems. The emission trend shows that the feasible system ranked 184 (numbered 20 in the figure) having the least pollution of all the above-mentioned pollutants. Each figure shows the minimum level of pollution of that pollutant by a number written below. The optimal system so obtained has been highlighted in Table 3, which consists of a 9 kW PV array with five wind turbines of 10 kW and one DG of 65 kW along with 30 batteries and a converter of 35 kW capacity. The COE of the system is $0.296/kW h and consists of 20% renewable fraction. It can also be observed that the emission trend is not dependent on the amount of diesel consumed or DG working hours. The energy contribution made by each energy converter in the feasible system has been illustrated in Figure 5.

Figure 5 Contribution of electrical energy by various energy converters in the optimal system.

The figure shows the annual as well as the monthly average contribution of energy made by each converter in the optimal system. Excess electricity, unmet electric load and capacity shortage by the system have also been illustrated in the figure. All these values are almost negligible for a total load of 401,885 kW h served by the system. The presence of DG makes the system robust and dependable in the case of failure of renewable sources.

7. Conclusion

Optimal generation mix has been endeavoured for a remote village cluster in Uttarakhand state, India. The HOMER software of NREL, USA has been used as the planning tool for sizing optimisation of the system. The proposed hybrid system includes two renewable resources, namely solar and wind, along with DG as the back-up and battery as the storage device. The optimisation results obtained from the simulation suggest that, on the basis of least NPC, the most appropriate system is the one having five wind turbines of 10 kW and DG of 65 kW along with 25 batteries of 6 V, 6.94 kW h capacity. All feasible systems are further analysed for least environmental degradation. Figure 4(a)–(f) shows the plot of emissions made by some significant feasible systems. The plot made it clear that the system ranked 184 is the required system with least emission of pollutants. This system is highlighted in Table 3, which consists of a 9 kW PV system with five wind turbines of 10 kW and one DG of 65 kW along with 30 batteries. The amount of minimum emission of carbon dioxide, carbon monoxide, hydrocarbons, particulate matter, sulphur dioxide and nitrous oxide has been indicated in the respective plots. Although the suggested system has an NPC higher than the rank one system with a minimum NPC of $1,252,018 but on a compromised NPC of $1,270,921, environmental degradation has been reduced to a minimum, which signifies that optimal hybrid energy system is suitable for the present power demand and appropriate for sustainable environment.