Electricity generation from hybrid PV-wind-biomass system for rural application in Brazil Congcong Song 2017-03-02

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Electricity generation from hybrid PV-wind-biomass system for rural application in Brazil

Congcong Song 2017-03-02

Master of Science Thesis

KTH Industrial Engineering and Management Energy Technology EGI_2017-0018 MSC

Division of Energy Systems Analysis SE-100 44 STOCKHOLM

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Master of Science Thesis EGI_2017-0018 MSC

Electricity generation from hybrid PV-wind-biomass system for rural application in Brazil

Congcong Song

Approved Examiner

Mark Howells

Supervisor

Shahid Hussain Siyal

Abstract

Electrification of households in rural area and isolated regions plays a significant impact on the balanced economic development. Brazil grows with a high population growth rate, but still parts of rural area and isolated regions do not have the accessibility of electric power. This study focuses on the feasibility study of a hybrid PV-wind-biomass power system for rural electrification at Nazaré Paulista in southeast Brazil. This study was performed by using the hybrid renewable energy system software HOMER. The wind and solar data was collected from Surface meteorology and Solar Energy-NASA, and the biomass data was collected and estimated from other previous studies.

The result shows, the hybrid PV-wind-biomass renewable system can meet 1,601 kWh daily demands and 360 kW peak load of the selected rural area. The power system composed of 200 kW PV panels, 200 kW biomass generator, 400 battery banks, and 200 kW converter. All the calculations were performed by Homer and the selection were based on the Net Present Cost (NPC) and Levelized cost of energy (COE). Because of the fossil fuels’ negative impacts on human health and environment, all the energy sources for this system are renewable energies which have less pollution.

Key words: Hybrid system, Renewable energy systems, PV, Wind, Biomass, Levelized cost of energy, Net present cost

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Acknowledgements

First of all, I would like to express my sincere heartfelt thanks to all Sustainable Energy Engineering professors that gave me great assistance during my whole study period and shared their wealth of knowledge with me. Furthermore, I owe my greatest debt of gratitude to my supervisor, Shahid Hussain Siyal (Phd) who kindly agreed at the beginning to assist me to do my research and offered me understanding, patience, invaluable advices and informative suggestions during the period. Finally, I would like to thank to my family members who showed their patience and encouraged me in writing the thesis.

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List of figures

Fig. 1 Schematic layout ...- 4 -

Fig. 2 The PV-wind-biomass hybrid power supply system (Design by author) ...- 7 -

Fig. 3 Map of Nazaré Paulista ...- 8 -

Fig. 4 Estimated daily profile ... - 10 -

Fig. 5 Month availability of wind resource in the area ... - 11 -

Fig. 6 Annual Wind Speed Weibull Distribution ... - 11 -

Fig. 7 Solar radiation availability ... - 13 -

Fig. 8 Biomass accessibility(tones/day) ... - 14 -

Fig. 9 Configuration of hybrid PV-wind-biomass system in HOMER ... - 14 -

Fig. 10 Power curve for WES 250 kW ... - 16 -

Fig. 11 The categorized optimization table ... - 18 -

Fig. 12 Cost summary for the proposed system scenarios ... - 20 -

Fig. 13 Cash flow summary for SC1 ... - 20 -

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List of tables

Tab. 1 Details of Nazaré Paulista ...- 8 -

Tab. 2 Estimated electricity load for a rural house and a school ...- 9 -

Tab. 3 Hourly load profile ...- 9 -

Tab. 4 Monthly average wind speed at 50m above the surface of earth in Nazaré Paulista- 11 -- Tab. 5 Monthly average solar radiation in Nazaré Paulista ... - 12 -

Tab. 6 Monthly average biomass in Nazaré Paulista ... - 14 -

Tab. 7 Technical and economic input data of each component for HOMER model ... - 15 -

Tab. 8 Details for Hoppecke 24 OPzS 3000 ... - 17 -

Tab. 9 System configurations of top three power systems ... - 18 -

Tab. 10 Yearly electrical energy production of each scenario ... - 19 -

Tab. 11 CO2 emission reduced by replacing Bituminous with renewable power system .. - 22 -

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III

List of abbreviations

Abbreviation Description

OECD Organization for Economic Co-operation and Development HOMER Hybrid Optimization Model for Electric Renewables

PDEE Ten-year Energy Expansion Plans

WEO World economic outlook

IEA International Energy Agency

PV Photovoltaic

DC Direct Current

AC Alternating Current

CHP Combined Heat and Power

NASA National Aeronautics and Space Administration

MSW Municipal Solid Wastes

NPC Net Present Cost

COE Levelized Cost of Energy

O&M Operation and Maintenance

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1. Introduction

1.1 Introduction

There is a growing global awareness of energy security and the importance of reliable electricity supply, hence, courtiers are searching for the cost effective ways to increase renewable energy based electricity generation. [1] In the meantime, to guarantee the access to reliable and affordable power is also one of the highlights. According to the forecasts of Kevin J. and Glenn A. [2], the world population is going to reach 8.5 billion by 2030 and is expected to exceed 11 billion by 2100. However, at the same time, most people in the worldwide does not have the accessibility of electric power despite the highly growth rapid of electricity consumption. Base on WEO-2016, more than 16% of the global population is facing the issue of lacking electricity supply, and apparently, most of them are coming from the rural area. [3] To build reliable electricity infrastructure is not only to reach the development goals but also can stimulate the economic development.

The economic and technological development is closely related to the use of energy, for a long time, people use fossil fuels to meet their energy demands. In addition to being used for power generation, fossil fuels are also used for heating and transport.

[4] In the foreseeable future, humans will continue to use fossil fuels on a large scale, and the use will be on the rise. This is because, with the economic development, the global population will show an increasing trend which leads to a large demand for energy and indirectly leads to increased demand for fossil fuels. [5] Although fossil fuels are the primary source of energy production, people are committed to find alternative energy sources because of the negative impacts on human health and environment, especially the climate change issue. [6]

In the worldwide, almost all the Organization for Economic Co-operation and Development (OECD) members and non-OECD countries are working on introducing new energy polices and measurements to increase the energy security and mitigate the climate change issue. In 2005, the final energy use and the greenhouse gas emissions are increased by 23% and 25% compared with the level in 1990. And the non-OECD countries played an important role in these changes.[7]

Brazil is one of the non-OECD countries and the biggest country in Latin America. It has the largest economy in South and Central America and also ranks number five in the world by population.[8] The land area and water area of Brazil are about 8,358,140 km2 and 157,630 km2. Most part of the land area is cover by the forest and accounts for about 62%. Brazil is an important energy producer and the petroleum plays a major role. Energy sources of Brazil consist of primarily hydropower, oil, mineral coal and biofuels. In 2014, fossil fuels were accounted about 60% in the total domestic energy supply and renewable energy sources only represented 40%. [9]

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By 2014, the population in Brazil had already risen to 206.1 million and the rural population accounts for up to 14.6% of total population. [10], [11] The yearly electricity consumption growth rate in Brazil is about 4.5%, but still, there is about 20%

of rural population that does not have the accessibility of electric power. [12] In order to meet the rural demand of electricity and considering about the climate change issues, the Brazilian government is willing to spend $100 billion USD for the future development. The Ten-year energy expansion plans (PDEE) has set the target to increase the share of renewable energy of country's electricity generation matrix to 86.1% by 2023. [13], [14] Building a local off-grid electrification can be the solution to help the rural area and isolated regions to gain the reliable electricity accessibility and a renewable energy system can lead a significant environmental impact. The world has awarded of the negative environmental impact of fossil fuels, so that, to replace fossil fuels with the environmental renewable energy is the inevitable choice.

Brazil is the lead of the renewable electricity generation and mainly from hydropower.

There is about 79% electricity generated by hydroelectric power plants in these latest years and small parts are from other sources, such as wind, biomass and coal.[15]–[17]

The wind and solar power have high potentials in Brazil, but have not been fully investigated and utilized. The wind energy is seen as a fast growth renewable energy in Brazil and still has large potential to be developed and expected to grow 2GW yearly. The National Decennial Energy Plan drew up a constitution to increase the installed wind power capacity to 16GW by 2021 which is about 9% of total electricity consumption.[18], [19] Northeast of Brazil has the richest solar radiation which is around 5.9kWh/m² and most solar and wind power plants are located in this region.

The solar power is under good developing, there were about 5 millions solar panels installed in 2009. For the purpose of national energy plans, the solar power still needs to be exploited and there is a substantial potential.[20]

A hybrid energy system consists of more than one energy resources, and for most other studies,[21], [22] using wind power and solar power for electricity generation is the most popular choice. In this study, this hybrid electricity system includes not only wind power and solar power but also biomass energy. The hybrid PV-wind-biomass power plant (not yet implemented) is aimed to produce and utilize the electricity for the residential sector in Brazil.

Furthermore, Hybrid Optimization Model for Electric Renewables (Homer) is the most common software to analysis a hybrid power system. HOMER is developed to build an optimization model and evaluate the technology and economic efficiency of off-grid and on-grid power systems for different generation applications. In this study, HOMER is used to carry the feasibility assessment of the hybrid PV-wind-biomass power system.

The main objective of this study is to design the hybrid PV-wind-biomass power system in Brazil to meet a certain rural electricity requirement and analyze the

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feasibility of this power generation system by considering about the economical and environmental impacts. In order to achieve the objectives, a municipality called Nazaré Paulista with 16.4 thousand populations has been chosen. [23] Homer software is used to design the power system and calculate the electricity productions and analysis the system’s feasibility.

This study paper is divided into three parts: Chapter 1 displays the introduction of this paper; Chapter 2 presents the schematic layout of this work; Chapter 3 shows the Homer analysis of the power system; Chapter 4 is about results and conclusions.

1.2 Objectives of the Thesis

The main objective of this study is to design the hybrid PV-wind-biomass power system to meet a certain load requirement of the Brazil local grid and analyze the feasibility of this power generation system in Brazil.

The specific objectives can be divided as:

 To analysis the energy load for the selected rural area in Brazil

 To analysis and evaluate the renewable energy potential mainly for those three resources, biomass, solar and wind

 To design a PV-wind–biomass hybrid system in Brazil

 Economical and climate mitigate potential analysis of the this hybrid power generation system

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2. Schematic layout of the work

2.1. PV-wind-biomass hybrid power system

The PV-wind-biomass hybrid power is proposed for analysing the feasibility and stability.

The schematic layout of this study is shown in Fig 1 under to meet the electricity demand in the rural area of Nazaré Paulista. Simulation, optimization and sensitivity analysis are elements for HOMER to model the system and analyze the result. During the simulation process, the power system components need to be determined and data needs to be input to meet the electricity load. This process can decide the lifecycle cost of system according to the installing and operating and maintenance cost of different components. In the operating process, after calculation, all the available alternatives will be shown.

The final choice should be based on costs of investment, fuels and maintenance and operation and environment impact. In the sensitivity analysis process, the parameters for components can be adjusted to determine the feasibility of configuration and the differences for the system.

Fig. 1 Schematic layout

2.2. Methodology of economic analysis

HOMER simulates the system by making energy balance calculation for every hour in a year and comparing the hourly electric demand to the system hourly electric supply.

It can calculate the energy flows for each system component and decide how the system works to meet the electric demand. Additionally, it will simulate all the feasible alternatives according to the cost of installing and operating the system, fuels and interest rate.

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After simulation, HOMER shows the top ranked system configurations according to the Net Present Cost (NPC), and also shows the sizes and quantities of the components, the total capital cost and Levelized cost of energy (COE).

NPC is the main economic output in HOMER and means the deviation between the total cost of the system and the total revenue. The total cost of the system includes the capital cost, replacement cost and the operation and maintenance cost of the system, fuel costs and emissions penalties. Revenues include salvage value and grid sales revenue. It is calculated according to the expression below: [24], [25]

C_NPC= C_ann,tot CRF(i, R_proj)

C_ann,tot = total annualized cost of the system [$/yr]

i =annual interest rate [%], in this project, the interest rate is 6%

R_proj = project lifetime [yr], in this project, the lifetime is 25 years

CRF() = capital recovery factor. It can be calculated according to below

CRF(i, n) = i(1 + i)ⁿ (1 + i)ⁿ− 1

n = Total number of years fixed for investment recovery

COE is the average cost per kWh of useful electrical energy produced by the system.

It plays an important role when considering about the system, but HOMER ranks the result according to NPC instead of COE is because NPC is a more trustworthy number.

It is hard to isolate and calculate the cost of electricity or the amount of electricity demand and actually supplied when the system serves both electric and thermal loads.

COE is calculated according to the expression below: [26], [27]

COE = C_ann,tot

E_prim,AC+ E_prim,DC+ E_def+ E_grid,sales

C_ann,tot = total annualized cost of the system [$/yr]

E_prim,AC = AC primary load served [kWh/yr]

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E_prim,DC = DC primary load served [kWh/yr]

E_def = deferrable load served [kWh/yr]

E_grid,sales = total grid sales [kWh/yr]

The Salvage value is also considered as the remaining value of the components of the system at the end of the project. It can be calculated as below:

S = C_rep R_rem R_comp

C_rep =replacement cost of the component [$/yr]

R_rem =the remaining life time of the component at the end of the project lifetime

R_comp =the total life time of the component

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3. System modeling

In this chapter, the main emphasis of the work is about modeling this hybrid system by using the collected and predication date, specifying inputs and outputs of the models and getting the simulated results. The aim of designing this hybrid power system is to produce and utilize the electric energy which is from renewable energy sources instead of fossil fuels to meet the energy demand.

It is obvious that this hybrid power system is composed of three sustainable and renewable energy sources: wind power, solar power and biomass. Hybrid power system has greater stability and reliability than any single source power system, so that the maintenance cost is also lower. The pollution emissions are also lower than other power systems because of using renewable energy sources. Fig 2 gives the PV-wind-biomass hybrid power supply system which is designed for analyzing.

Fig. 2 The PV-wind-biomass hybrid power supply system (Design by author)[28], [29]

A municipality called Nazaré Paulista is located in the southeast region of São Paulo state, in Brazil. Nazaré Paulista has around 16.4 thousands inhabitants in the area of 326,254 km2 and the rural population is accounted as 15% of total population. The latitude and the longitude of the municipality are 23.1816° S and 46.3979° W. The average annual temperature in Nazaré Paulista is about 18° C, and the yearly amount of rainfall is significant high. [30], [31] Fig 3 and Tab 1 under show the geographic location and details of the selected city.

DC Bus

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Fig. 3 Map of Nazaré Paulista[23]

Tab. 1 Details of Nazaré Paulista[30], [31]

Parameters Details

Municipality Nazaré Paulista

State São Paulo

Country Brazil

Latitude 23.1816 South

Longitude 46.3979 West

Total population (2010) 16,414

Urban population (2010) 13,911

Rural population (2010) 2503

3.1. Rural area load assessment

This study is aiming to analyze the feasibility of building hybrid PV-wind-biomass power system in rural area in Brazil. Nazaré Paulista is a municipality which is located in the southeast of São Paulo, there are 2503 residents live in the rural area and can be estimated as about 500 houses. The primary load profile for the whole rural area is derived and based on the following assumption:

For these 500 houses, each house has the basic electrical equipments: two compact fluorescent lamps (CFL), ceiling fan, one TV, refrigerator and a small radio.

The village consists of a public utility which is a school with 10 compact fluorescent lamps, ceiling fans, 5 TVs and 5 computers. For the school, the computer's power consumption is relatively large.

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There are two demand peaks every day, one is during the lunch time between 12pm and 13pm, the other one is during the night time from 18pm to 23pm. For houses, refrigerators work 24 hours every day and have stable electricity consumptions.

Tab. 2 Estimated electricity load for a rural house and a school[32]–[37]

Final use Type of load

Power (W)

Quantity Operating hour per day

Hours/Day kWh/Day

Households Lamp 11 2 18:00-24:00 6 0.132 Ceiling fan 120 1 12:00-13:00

18:00-23:00

6 0.72

TV 90 1 12:00-13:00

18:00-23:00

6 0.54

Refragrator 70 1 0-24:00 24 1.68

Radio 20 1 8:00-13:00 5 0.1

School Lamp 11 10 18:00-23:00 5 0.55

Ceiling fan 120 10 12:00-13:00 18:00-23:00

6 7.2

TV 90 5 8:00-12:00

13:00-18:00

9 4.05

Computer 180 5 8:00-12:00

13:00-18:00

9 8.1

Tab 2 shows detailed load demand for proposed appliances in a rural house.

According to this estimation, the total daily electricity demand for a rural house is 3.172 kWh and for one school is 19.9 kWh. According to this load profile, the maximum demand of this rural village is around 151.23 kW, and the daily energy consumption is approixmately 1,600.5 kWh/d.

Tab. 3 Hourly load profile

Hour Load (kw) Hour Load (kw)

00:00 35 12:00 151.2

01:00 35 13:00 36.35

02:00 ³⁵ 14:00 ^36.35

03:00 35 15:00 36.35

04:00 35 16:00 36.35

05:00 ³⁵ 17:00 ^36.35

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06:00 35 18:00 151.23

07:00 35 19:00 151.23

08:00 ^46.35 20:00 ^151.23

09:00 46.35 21:00 151.23

10:00 46.35 22:00 151.23

11:00 ^46.35 23:00 ⁴⁶

Fig. 4 Estimated daily profile

3.2. Resources assessment

The selected rural area has the significant additional development potential of renewable energy sources to meet the electricity requirement.

3.2.1. Wind resource

On a global scale, wind power has experienced a rapid growth rate. In 2011, the total installed capacity reached approximately 240GW and new installed capacity was around 40GW compares with 2010. [38] In Brazil, southern and northeast have relatively large wind power potentials and most wind farms focus on offshore wind energy since the higher wind speed in coastal area. The working principle for wind turbine to produce electricity is to convert the kinetic energy into mechanical or electric energy when the wind blows through.

Monthly average wind speed at 50m above the surface of earth of Brazil can be found from Surface meteorology and Solar Energy-NASA and is used as wind resource input data in HOMER. The slowest wind speed and the highest wind speed are 3.54 m/s and 4.58 m/s and the annual average wind speed is about 3.99 m/s.

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Tab. 4 Monthly average wind speed at 50m above the surface of earth in Nazaré Paulista [39]

Month Wind speed (m/s) Month Wind speed (m/s)

January 3.83 July 3.72

February 3.71 August 4.03

March 3.80 September 4.50

April 3.58 October 4.58

May 3.62 November 4.55

June 3.54 December 4.43

Annual average 3.99

In order to calculate the wind energy yield of the wind turbine, the probability density distribution of the wind speed must been figured out. Because the wind power is unsteady, there is a two-parameter Weibull distribution which is often used to characterize wind regimes in HOMER. The graph below shows a typical distribution of wind speeds and the best-fit Weibull distribution. The Weibull k value is also called Weibull shape factor which is a parameter that indicates the breadth of a distribution of wind speeds over a year. In this case, the breadth of distribution of wind speed k is 1.96.[40], [41]

Fig. 5 Month availability of wind resource in the area

Fig. 6 Annual Wind Speed Weibull Distribution

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3.2.2. Solar resource

The sunlight in Brazil is sufficient for solar power plants expanding on account of the location. It is located on the equator and therefore the average solar irradiation in this country is considerable high.

In order to get final result in HOMER, the solar resources data is one of the important input data. In this part, the latitude and longitude of the selected location and the amount of solar radiation available to the photovoltaic (PV) array throughout the year are necessary to calculate the output of the PV array each hour of the year.

Considering at the location is 23.1816 S and 46.3979 W, the monthly average solar radiation can be taken from Surface meteorology and Solar Energy-NASA. It is ranges from 3.58 kWh/m2 /day and 5.55 kWh/m2 /day, and the annual average solar radiation is 5.33kWh/m2 /day. [39]

Tab. 5 Monthly average solar radiation in Nazaré Paulista [39]

Month Solar radiation (kWh/m2 /day)

Annual average 4.64

HOMER displays the monthly average radiation and clearness index in the solar resource table and graph. The clearness index is an indicator of the clearness of the atmosphere and ranges from 0 and 1.Theoretically, the higher clearness index means the weather condition is sunnier. [42], [43] In this study, the average clearness index in Nazaré Paulista is around 0.498 and most counties are between 0.25 and 0.75.

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Fig. 7 Solar radiation availability

3.2.3. Biomass resource

In this study, the main resource for the generator is biomass. In Brazil, there is a large potential of biomass to be further developed and it could be the resource for electric power supply in Brazil. By increasing the share of bioenergy in the energy matrix can potentially reduce the emissions caused by the use of fossil fuels. According to Lora and Andrade [44], in 2006, the biomass electricity corresponded around 4.4% of the total electricity. The main sources of biomass are listed as sugar cane bagasse, firewood, and agricultural residues.

In this study, agricultural residues are considered as the source of biomass in HOMER.

In Brazil, the total production of agricultural residues in 2001 was 138.5 million tones and the biomass availability is calculated and estimated based on [44]. After calculation and estimation, the yearly biomass production for the whole country is 0.672 tonnes/person. So, the daily biomass availability for the rural area in Nazaré Paulista is 4.61 tonnes/day which equals to 4182.12 kg/day. The month wise availability of biomass in the study is shown in Tab 6 and Fig 8.

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- 14 - Tab. 6 Monthly average biomass in Nazaré Paulista[44]

Month Available Biomass (tonnes/day)

Annual Average 4.616

Fig. 8 Biomass accessibility(tones/day)

3.3. Components assessment

Fig. 9 Configuration of hybrid PV-wind-biomass system in HOMER

Fig 9 shows the configuration of this hybrid power system. The PV-wind-biomass hybrid power system consists of PV arrays, wind turbines, biomass gasifier, battery banks and inverters. AC electricity is generated from wind turbine and biomass gasifier and it can be used directly. But the PV arrays generate DC electricity that needs to be converted to AC electricity in the converter. The battery bank in this system is called Hoppecke 24 OPzS 3000 that can store up the over generated electricity and use it in emergent situations. The electricity input in the battery is expressed as DC electricity, so that, the AC electricity needs to pass through the

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converter and transform to DC electricity. The economical data inputs in HOMER software includes the capital costs, maintenance costs and replacement costs of system components are provided in Tab 7. The project life of this study is 25 years and the annual real interest rate is 6%.

Tab. 7 Technical and economic input data of each component for HOMER mode[34], [45]–[48]

WES 250 Wind turbine

Maximum hub height 50m

Rated power 250 kW

Life time 20 years

Rated wind speed 13m/s

Initial cost 2300 US$/kW

Replacement cost 1500 US$/kW

O & M cost 2 US$/kW/year

PV panel

Derating factor(%) 80%

Life time 20 years

O & M cost 4 US$/kW/year

Biomass gasifier

Life time 15000 operating hours

O & M cost 0.06 US$/h

Hoppecke 24 OPzS 3000 Battery

Life time 5 years

Initial cost 1392 US$/battery

Replacement cost 1300 US$/battery

O & M cost 14 US$/year

Converter

Efficiency 90%

O & M cost 167 US$/year

Wind turbine

The working principle for wind turbine is to convert the kinetic energy into mechanical or electric energy. For the wind turbine, cut-in (start-up) speed, normal speed and cut-out (maximum) speed are usually used to describe the turbine working processes. When the wind speed reaches the normal speed, the wind turbine will generate a steady power which does not change with the wind speed increase. The

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blade length and rotor diameter can influence the turbine rotor swept area, and therefore decide the wind power output. In the hybrid power system, WES 250 kW with a 20 years life time was chosen to produce wind energy.

Fig. 10 Power curve for WES 250 kW[49]

The power curve represents varies between turbine power outputs and wind speeds.

For WES wind turbine, the rated output power is 250 kW. The cut-in speed for this turbine is smaller than 3 m/s that mean the turbine starts rotating and producing power at this minimum wind speed and keeps increasing rapidly with the wind speed increase. Until the speed creeps up to 13 m/s, the wind turbine is able to produce electric power at its maximum which is 250 kW. Considering of the safety and stability, all the wind turbines have maximum wind speeds to protect turbine structure.

If the wind speed is increased up to the cut-out speed, the wind turbine will be shut down to prevent the damage to the rotor. For WES 250, the cut out speed is 25 m/s.

When the wind speed reaches or higher than this critical point, it will stop working to prevent from the damage.[49]

PV Array

In this paper, PV panel with a 20 years life time is selected. The working principle for PV panels is to absorb the sunlight and convert solar energy into direct current (DC) and then convert into alternating current (AC) to meet the electricity demand.[50]

After PV panels collect sunlight, the electricity flows between PV cells and the DC electricity is generated. The DC electricity will go through the electricity converter to be transformed.

Biomass gasifier

Biomass gasification technology is ripe enough for using in power generation and easily to combine with co-firing technology. Most gasification power plants are

0 50 100 150 200 250 300

0 1 2 3 4 5 6 7 8 9 10 11 12 12.5 13 14 15 16

Power Output (kW)

Wind Speed (m/s) Power Curve

Cut-in Speed

Rated Output

speed Rated

Output Power

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combined heat and power (CHP) plants because of the high efficiency and both heat and electricity are generated. Part of heat is used in this system and the rest of heat and all the electricity are delivered to the heating system and electric grid system.

In this study, an energy generator is combined with wind turbine and PV arrays to produce the renewable electricity. Biomass is the fuel for the generator and three main working processes are included in gasification process: pyrolysis, gasification and combustion. The estimated biomass fuel price is 25 US dollar per tone and the carbon content of the biomass is 30%.

Battery

For a solar system, the battery bank is needed to capture excess energy and supply during nights or days with low solar irradiation.[51] In this work, Hoppecke 24 OPzS 3000 is chosen to storage the excess energy. Table 3-7 shows the details about this battery. According to DIN 40735-1, the maximum capacity at 10h discharge should be at least 3000 Ah. In the reality, the designed 10h discharged capacity is up to 3220 Ah.

This module’s capacity is considerable high enough for a solar power system.

Tab. 8 Details for Hoppecke 24 OPzS 3000[52]

Manufacturer Hoppecke

C_nom/1.80 V (Ah) 3000

C₁₀/1.80 V (Ah) 3220

C₅/1.77 V (Ah) 2795

C₃/1.75 V (Ah) 2394

C₁/1.67 V (Ah) 1568

C_nom: Normal capacity at 10h discharge according to DIN 40735-1 C₁₀, C₅, C₃, C₁: Capacity at 10h, 5h, 3h, 1h discharge

Converter

A converter (inverter) is used to convert the electricity between AC voltage and DC voltage. [53] The efficiency is assumed to be 90% and it has a 20 years lifetime. The estimated capital and replacement cost of the converter is US$ 1675/kW and US$ 1400/kW.

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4. Results and discussion

After simulation, HOMER shows the top ranked system configurations according to NPC. Fig 11 below summarized top ranked system configurations obtained from the simulation results.

Fig. 11 The categorized optimization table

4.1. Technical Analysis

Tab. 9 System configurations of top three power systems

PV (kW)

Wind turbine

Generator (kW)

Battery Converter (kW)

Total NPC COE ($/kW) Scenario

1

200 N/A 200 400 200 $2,580,157 0.346

Scenario 2

N/A N/A 200 400 200 $2,699,663 0.362

Scenario 3

300 1 200 200 200 $2,954,729 0.396

Three best scenarios resulted from the simulations are showed in Tab 9 and described in details below:

1) Hybrid PV-biomass power system composed of 200 kW PV panels, 200 kW biomass generator, 400 battery banks and 200 kW converter.

2) Biomass system alone composed of 200 kW biomass generator, 400 battery banks and 200 kW converter.

3) Hybrid PV-wind-biomass power system composed of 300 kW PV panels, a 250 kW wind turbine, 200 kW biomass generator, 200 battery banks and 200 kW

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converter.

Tab 10 shows the share of electricity production from each system component for each main scenario.

Tab. 10 Yearly electrical energy production of each scenario

SC1 SC2 SC3

Production MWh % MWh % MWh %

PV 287 40 N/A 0 430 48

Wind N/A 0 N/A 0 145 16

Biomass 431 60 687 100 313 35 Total 718 100 687 100 889 100

SC1 consists of two renewable sources, solar and biomass. In SC2, all the electric power is generated from biomass energy. SC3 includes solar, wind, and biomass and in this system solar is the main energy resource of the production, followed by biomass.

SC1 presents the lowest costs of NPC and LCOE compared to the other scenarios, so that, this system is the most cost effective. The average daily electric power demand in this rural area is 1601 kWh/d which leads to a yearly electricity demand as approximately 600 MWh. All of these systems can produce the electric power more than the local demand which means these systems are feasible because they could potentially produce enough electric power to meet the energy demand in the rural area.

However, as shown in Tab 10, comparing these three systems, SC3 could produce the most electricity, but there is a larger amount of excess electricity which is a big waste.

For other two scenarios, SC1 could also produce 30 MWh more than SC2 due to the consisting of two energy resources, but it can meet the electricity demand at a relatively low cost. Future more, in future, the excess electricity produced by SC1 could be sold to the grid or neighbor cities when this system is developed to a grid connected system to increase the system revenues. Thus, SC1 can be seen as the best option for rural electrification in this area.

4.2. Financial Analysis

HOMER calculates and shows the total cost and income of this hybrid power system.

From a purely economic perspective, the total net present cost of this project means all the costs that it incurs over its lifetime minus the present value of all the revenue that it earns over its lifetime. The cost details of selected main scenarios are showed as below:

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Fig. 12 Cost summary for the proposed system scenarios

According to Fig 12 above, it is easily to see that the hybrid system SC1 presents the lowest cost of NPC and LCOE compared to the other scenarios. By comparing these three systems, the capital cost of SC2 is the lowest, but the cost of replacement and operating is much higher than other two systems. Also, this is a biomass alone system, hence, the cost of purchasing fuels is also much higher than others. SC1 tends to be lower capital cost and replacement cost, but a little higher operating cost than SC3. At the end of the project, HOMER shows the salvage which means the remaining value in a component of the power system at the end of the project lifetime. SC2 has the lowest salvage and the others are nearly the same. According to the above, HOMER shows that SC1 is the most economical system in order to meet the electricity demand in the rural area.

Fig. 13 Cash flow summary for SC1

2.58 2.7

2.95

0.35 0.36 0.4

SC1 SC2 SC3

NPC($*10^5) LCOE ($/kWh)

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4.3. Environment analysis

The aim of this project is to provide electricity for rural area from renewable energies.

The reason of replacing fossil fuels with environment friendly and sustainable fuels is because it can potentially reduce the CO2 emissions. Here, coal is seen as a comparative object to study possible pollution reductions. According to US. Energy Information Administration (EIA), coal can be well classified as Bituminous, Sub-bituminous, and Lignite. [54] For example, when producing electricity by Bituminous, there is around 0.94 kg CO2 is emitted per kWh. On the other hand, renewable energies can be seen as nearly emission free. Therefore, by replacing fossil fuels with renewable energies in electrification, a large amount of CO2 emission can be avoided. In this project, by multiplying emission factor of Bituminous and the electricity production of each energy resources and each power

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system, the potentially emission reductions could be found. Tab 11below shows the results of CO2 avoided by those three renewable power system. For all of these systems, more than 6.5* 10^5 kg CO2 can be avoided by each renewable power system.

Tab. 11 CO2 emission reduced by replacing Bituminous with renewable power system

SC1 SC2 SC3

Electricity production

(MWh)

Emission reduction (*10^5 kg)

(MWh)

PV 287 2.7 430 4.0

Wind 145 1.4

Biomass 431 4.1 687 6.5 313 2.9

Total 718 6.8 687 6.5 889 8.3

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5. Conclusion

With the rapid development of the economy, sustainable development and energy security are becoming more and more important. Increasingly, renewable energy gains attention and plays an important role in the current and future development. In order to reduce the greenhouse effect and gas emission, renewable energy will gradually replace fossil fuels but in a long-time period.

The current work purpose is to analyze the feasibility of the hybrid PV-wind-biomass power system in Brazil from economic and environment sectors. It also made a deep research on the present energy situation and development potentials of renewable energy. Solar energy, wind energy, and biomass are newly developed sustainable resources with a lot of scope for development in Brazil. Brazil is located Eastern South America and neighboring with the Atlantic Ocean, the annual average solar insulation and wind velocity are 4.64 kWh/m2 /day and 3.99 m/s respectively in the selected location and the annual average potential is approximately 4.616 tones/day for biomass energy resource.

The hybrid PV-wind-biomass power system was modeled and analyzed by HOMER simulation software. The best suitable design with high economic value includes 200 kW PV panels, 200 kW biomass generator, 400 battery banks, and 200 kW converter.

It can potentially produce enough electricity to meet the local demand. The initial cost for this system is about 2.6 million US dollars which is quite high, but if considering from a long-term, the benefits will be greatly enhanced because of the existence of components. Furthermore, replacing fossil fuels with renewable energies in electrification sector can also contribute positively in reducing CO2 emission.

Recommendations and future work

For future work, it should be based on:

 Continued study on the subject and improve the hybrid system to a grid connected system.

 Implementation of the system to some degree to test the feasibility and stability.

 Doing tests and analysis to find if biomass prices have impacts on the feasibility of the system

 Doing more economic analysis to propose a suitable and realistic electricity price.

 Doing emission tests after implementation of this system to find potential methods to control and mitigate the amount of emission.

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Electricity generation from hybrid PV-wind-biomass system for rural application in Brazil Congcong Song 2017-03-02