Optimization and Cost of Energy of Renewable Energy System in Health Clinic Building for a Coastal Area in Tamil Nadu , India Using Homer

The renewable energy potential of coastal areas of Tamil Nadu, India ranks along with the utmost in the world. This study proposes optimization and cost of energy of different hybrid renewable energy system to power a health clinic in that building. The National Renewable Energy Laboratory (NREL) optimization computer model for distributed power, “HOMER,” is used to estimate the optimization and its cost of energy. The implementation of RE systems to supply Rural Health Clinics will contribute to reduce both electricity generation cost and to reduce the consumption of fuel while improving health care and quality of life in these isolated coastal regions. We conclude that using the PV+Wind+Diesel+Battery system for these types of applications in justified on technical and economic grounds. The experimental results show that the least cost of energy at Rs 5.00/KWh, is obtained from above said system and also experiment result shows that the COE decreases with 0% of interest. It is noted, that the PV+Wind+Diesel+Battery hybrid system shows the lowest COE and high amount of Renewable energy.


INTRODUCTION
Most of the coastal areas in Tamil Nadu are still under developed and in a chaotic state after the demand of development activities and there is a need to provide these areas with electricity.Small standalone hybrid renewable energy systems can play a strategic role in the region's balanced and sustainable development.The region enjoys a huge amount of renewable energy sources during the entire year.Although capable of providing plentiful and reliable electricity, this resource is presently remaining untapped.The renewable energy sources (NASA, 2012) can satisfy the electrical needs of clinics, schools and other social places in a way that can positively affect healthcare and education, ensuring adequate services for the population.An excellent application of these systems is in health clinics.The relation between health and energy is compounding and as interdependent factors, they largely determine the progress of rural development.Reliable electricity generation on site is capable of delivering high-quality electricity for vaccine refrigeration, lighting, communication, medical appliances, clean water supply and sanitation (Lambert, 2012).The latitude and longitude of considered area, is 9°14' N, 78° 50' E. The climate is generally very hot, with temperatures reaching 49°C in the hot season, from March to September.This study reports the optimization and computes the COE for the different hybrid renewable system.NASA meteorological data has been used for acquiring data of the ambient conditions to measure: hourly (global horizontal irradiance) global irradiance, relative humidity, ambient temperature, direction wind and speed.This recorded data for 2012 have been used to assess renewable energy potential in considered area as shown in Table 1 and 2. The NASA meteorological data found that the yearly solar energy received is 5.0 kWh/m 2 and the wind energy received is at a moderate speed (4 to 6 m/sec).

MATERIALS AND METHODS
Feasibility of the proposed system: The design of the proposed system to power the health clinic is done according to http://www.mem-algeria.org/medical equipments installed in the clinic.The total load capacity is found to be 34.9 kWh/day.The system consists of wind turbine, PV modules, diesel generator, batteries, charge controller, inverter and the necessary wiring and safety devices.The system feasibility analysis was performed using the HOMER software developed by the National Renewable Energy Laboratory (NREL) to evolve the design of micro power systems.HOMER is a computer model that simplifies the task of evaluating design options for both off-grid (Jennings and Green, 2000) and grid-connected (Bakos et al., 2003) power systems for remote, standalone and distributed-generation (Cetin et al., 2009) applications.HOMER's optimization and sensitivity analysis algorithms allow one to evaluate the economic and technical feasibility of a large number of technology options and to account for variation in technology costs and energy resource availability.HOMER models (Ramakumar et al., 1992) both conventional and renewable-energy technologies.HOMER models a power system's physical behavior and its life-cycle (Kabouris and Contaxis, 1992) cost, which is the total cost of installing and operating the system over its life span.HOMER allows the modeler to compare many different design option based on their technical and economic criteria (Antony Day et al., 2011).It also assists in understanding and quantifying the effects of uncertainty or changes in the inputs.

Assumptions and homer model inputs:
Clinic load analysis: The typical clinic building (http://www.rsvp.nrel.gov)comprises the following rooms: administration room, doctor room, nurses' room, waiting room, two treatment rooms, small pharmacy and two restrooms.The medical equipment, lighting and other devices used in this clinic are the  following: refrigerator (80 W), freezer (80 W), vaporizer (50 W), oxygen concentrator (300 W), electric sterilizer (1500 W), water pump (100 W), color TV set (130 W), 15 florescent lamps (20 W each), seven ceiling fans (60 W each) and three evaporative coolers (500 W each).The estimated daily working hours of the medical equipment and other devices are as follows: fluorescent lamps (exteriors and interiors), 12 h/day; TV set, 6 h/day; refrigerator and freezers, 14 h/day; ceiling fans, 12 h/day; vaporizer, 3 h/day; oxygen concentrator, 2 h/day; electric sterilizer, 3 h/day; and water pump, 6 h/day.The system is assumed to work for 6 days a week.Our analysis found that the total connected wattage is 4460 W and the total average daily load is 31.6 kW h.The load analysis calculation is listed in Table 3.A small base load of 0.18 kW occurs from 5 pm until 7 am.This load is for outside lighting and some inside lighting, whereas the majority of the load occurs during the day time (8 am to 5 pm) (Fig. 1).
The sample clinic to locate in remote costal area called Kilakarai in Tamil Nadu (State) India, (9.27 N, 79.123 E).The wind data and solar radiation data for this region were obtained from the NREL (2011).Table 1 and 2 shows the monthly average solar radiation and wind for this area.The annual average solar radiation is 5.32 kWh/m 2 /day and annual average wind energy is 4.2 m/sec.

SYSTEM COMPONENTS AND ESTIMATED PRICES
The proposed system consists of PV modules (http://eosweb.larc.nasa.gov/)batteries, charge controller, inverter, auxiliary diesel generator (Saheb Koussa et al., 2009) and the rest of the balance systems (McGowan et al., 1996) which includes modules structure, wiring, fuses and other system safety devices.

PV array:
The PV array (without MPPT technique) is an interconnection of PV modules or panels that produces Direct-Current (DC) electricity in direct proportion to the solar radiation incident upon it, independent of its temperature and voltage to which it is exposed.The suggested PV panels to be used in the system simulation are 500 W (Kaldellis and Ninou, 2011) and 24 V and have estimated capital and replacement cost of Rs. 81,000 and 75,600.This cost includes shipping, tariffs, mounting hard system, wiring, installation and labor cost.The lifetime is assumed to be 25 years.A de-rating factor of 90% was (Dalton et al., 2009; Lockington applied to the electricity generated from each panel.The panels were modeled as fixed and tilted south at angle equal to the latitude of the site.Capacities of different PV panels (0, 1, 2, 5, 10 and 20 kW respectively) were considered in the analysis.

Batteries:
The battery is capable of storing a certain amount of DC electricity at fixed round efficiency, García-Valverde et al. (2009) with limits as to how quickly it can be charged or discharged without causing damage and how much energy can cycle through it before it needs to be replaced.HOMER assumes that the properties of the battery constant throughout its lifetime and are not a external factors such as temperature.The chosen battery has a 24-V, 250-Ah capacity and also SOC is 80%.The cost of one battery is Rs 12,000 with a maintenance cost of Rs 250/year.Different numbers of batteries (0, Fig. 2: Optimization for PV-wind-diesel-battery App. Sci. Eng. Technol., 8(19): 2048-2056, 2014 2050

SYSTEM COMPONENTS AND ESTIMATED PRICES
The proposed system consists of PV modules batteries, charge controller, inverter, auxiliary diesel generator (Saheb-., 2009) and the rest of the balance-of-., 1996) which includes modules structure, wiring, fuses and other system safety array (without MPPT technique) is an interconnection of PV modules or panels that Current (DC) electricity in direct proportion to the solar radiation incident upon it, independent of its temperature and voltage to which it suggested PV panels to be used in the system simulation are 500 W (Kaldellis and Ninou, 2011) and 24 V and have estimated capital and and 75,600.This cost s, mounting hard-ware, control cost.The lifetime rating factor of 90% ., 2009; Lockington et al., 2008) applied to the electricity generated from each panel.The panels were modeled as fixed and tilted south at an angle equal to the latitude of the site.Capacities of different PV panels (0, 1, 2, 5, 10 and 20 kW, ) were considered in the analysis.
The battery is capable of storing a certain amount of DC electricity at fixed round-trip energy .( 2009) with limits as to how quickly it can be charged or discharged without causing damage and how much energy can cycle through it before it needs to be replaced.HOMER assumes that the properties of the battery remain constant throughout its lifetime and are not affected by external factors such as temperature.The chosen battery Ah capacity and also SOC is 80%.The cost of one battery is Rs 12,000 with a maintenance umbers of batteries (0, 1, 5 and 10, respectively) were considered in this analysis.
Inverter: An inverter converts electric power from DC to Alternating Current (AC).Its effi to be 90% (Ibrahim et al., 2008) for all sizes considered.The estimated life time is 15 years and various size are s (0, 1, 5 and 10 kW considered in this study.
Generator: A generator consumes fuel to produce electricity and possibly heat as a by range of generators are available (die propane and bio-fuel) (Ibrahim et al analysis, considers a generator producing electricity that operates on diesel fuel, because it is more e than the others and its lifetime is longer.The estimated price of the generator is Rs 81/W and various capacities sizes are considered (0, 1 and 2 kW, respectively analysis.

System analysis:
Optimization results: In the optimization process, HOMER simulates every system con search space and displays the feasible ones in a table, sorted by total net present cost.) were considered in this An inverter converts electric power from DC fficiency is assumed ., 2008) for all sizes estimated life time is 15 years and various size are s (0, 1, 5 and 10 kW, respectively) A generator consumes fuel to produce electricity and possibly heat as a by-product.A vast range of generators are available (diesel, gasoline, et al., 2008).This analysis, considers a generator producing electricity that operates on diesel fuel, because it is more efficient than the others and its lifetime is longer.The estimated r is Rs 81/W and various capacities , respectively) in the In the optimization process, HOMER simulates every system configuration in the search space and displays the feasible ones in a table, PV-wind-diesel-battery: The Fig. 2 shows that optimization result for PV-wind-diesel-battery hybrid system.This system consists of one 2 kW PV array, one BWC Excel-S wind turbine, one 1 kW diesel generator, 1 battery and a 1kW power converter, with lower COE at Rs 17.This COE remain constant even with changing of PV, wind turbine, generator and converter but, increases when the battery bank increases.The maximum COE is observed for higher rating of battery bank at Rs 19.The important conclusion is that COE is mainly dependant on battery bank.The Fig. 2 show that this hybrid system can supply the power to isolated clinic with minimum fuel consumption 1221/year, the reason being that contribution of power from renewable energy sources are 69%.The Fig. 3 shows relationship between costs of different components which are associated with PVwind-Diesel-battery system.As can be seen from Fig. 3, the operating cost is very low for this system.
Wind-diesel-battery: The Fig. 4 reveals, the second economically viable standalone hybrid wind-dieselbattery system which consists of one XLS-turbine, one1 kW diesel generator, 5 batteries and a 1 kW power converter, with COE of Rs 19.11/kWh.The COE of this system increases with increase in diesel generator and battery bank.
The Fig. 5 shows relationship between costs of different components which are associated with wind-Diesel-battery system.As can be seen from the Fig. 5, the operating cost is low for this type system, but there is a reduction in capital cost and an increase in operating cost as compared to PV-wind-diesel-battery system.

PV-diesel-battery:
The Fig. 6 reveals data on PVdiesel-battery system.In this system Renewable energy share is 58% of the total energy production; the generator will be running about 5472 h/year consuming 1621 L of fuel.The system configuration incorporates 5 KW of PV along with a 1 kw generator, 1 batteries and an inverter capacity of 5 KW for an initial cost of Rs 13,33,800.The NPC over the lifetime of the system is Rs 28,06,488.As can seen from Fig. 6 COE increases with decrease in PV module.This is due to the fact that as the PV module decrease, the contribution from renewable energy source decreases with corresponding increase in fuel consumption.The optimal hybrid power system proposed by HOMER includes PV, diesel generator, battery and inverter (Fig. 7).The components needed to satisfy the demand of 34.9 kWh/day are 5 KW of PV panel, 1 kw capacity diesel generator, 1 batteries and 5 kw inverter.The capital cost of this system is Rs 13,33,800 and the NPC is Rs 28,06,488.The RE fraction represents 58% of the energy production.The generator will be running 5,472 h and will consume 1621 L/year of diesel fuel.The least cost system is wind turbine with diesel generator consisting of 1 KW of wind turbine, 1 KW diesel generator, 5 batteries and 1 KW inverter capacity for an initial capital cost of Rs 13,33800 and a NPC of Rs 28,06,488 and COE of Rs 19/KWh.PV-wind-battery only: The Fig. 8 details the optimization of PV-wind-battery system.As can be seen, this is the most expensive system of all the hybrid system considered.This is due to the fact that this system being totally renewable energy sources require large number of battery banks.
The Fig. 9 gives the cost structure of PV-windbattery system.As can be seen from Fig. 9, the operating cost is almost negligible but capital cost and total cost are very high.
Effect of interest and diesel on electricity cost: These types of projects in developing countries are usually undertaken by the government and hence the assumption of 0% interest rate when analyzing the system.The effect of different interest rates on the cost of electricity produced for all types of systessm are shown in Table 4.The figure showed that at 6% interest rate, the cost of the electricity produced is almost 75% of actual cost of energy.Similarly the effect of price of fuel has a large impact on the cost of electricity produced (Fig. 4).The simulation showed that varying the price from Rs 50/L to 55/L increases the cost of electricity produced from Rs 5.00/KWh to Rs 7.00 KW/h for the PV+Wind+Diesel+Battery system.The effect of fuel price and interest rate on the COE for other system can be seen in Table 4.

Comparison of COE:
A summary of the COE and RF of the different types of hybrid system are listed in Table 5.It is interesting to note, that the PV+Wind+Diesel+Battery hybrid system shows the lowest COE and high amount of RF (the portion of power generated by the renewable energy source compared to that of the total power drawn from the system).The second lowest COE of Rs 7.00/KWh is for Wind+Diesel+Battery hybrid system.The reason for the increase in COE for the other system is that contribution of RF is reduced and automatically increasing the consumption of fuel.The highest COE and also high amount of RF (100%) belongs to PV+Wind+Battery.The conclusion from the study of Table 5 is that any one renewable energy sources with diesel to produce the power for isolated clinic, leads to decrease in COE.

CONCLUSION
From the analysis and the experimental verification the following conclusion are drawn: • The Health clinic at remote coastal areas of Tamil Nadu in India can render satisfactory service to the community around if they are given hybridstandalone power system.• The optimized and least expensive model of such stand alone hybrid system is fund to be PV-diesel-Wind power-battery-converter system.• As the capital cost is high, the government should provide such system through a subsidized project.

Fig. 1 :
Fig. 1: Block diagram of renewable energy system Figure shows the results of the sample wind hybrid renewable energy sources.Each row in the table represents a feasible system configuration.The first four columns contain icons indicating the presence of the different components, the next four columns indicate the number or size of each component and the next columns contain the key simulation results: namely, the total capital cost of the system, the total net present cost, the levelized cost of energy (cost per kilowatt hour), the annual fuel consumption and the number of hours the generator operates per year.The complete simulation results, for different stand alo renewable system (PV-Wind-battery, Wind battery, PV-diesel-battery, PV-wind shown in Fig. 2, 4, 6 and 8. battery Fig. 3: Cost for PV-wind-diesel-battery

Fig. 8 :
Fig. 8: Optimization for PV-wind-battery Fig. 10: (a) The photograph of the experimental setup for solar panel, (b) the photograph of the experimental setup for battery bank, (c) the photograph of the experimental setup for generator

Table 1 :
Monthly average solar radiation

Table 4 :
Effect of interest rate and diesel price on electricity cost