RURAL ELECTRIFICATION AND OPTIMIZATION OF HYBRID WIND/PV POWER SYSTEM A Technical Seminar submitted to
JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY in partial fulfillment of the requirement for the award of the degree of MASTER OF TECHNOLOGY in
POWER ENGINEERING & ENERGY SYSTEMS by G.RAMESH (11NO6D6405) Under the Guidance of T.ARUNA KUMARI ASSISTANT PROFESSOR
Department of Electrical and Electronics Engineering,
SREE CHAITANYA COLLEGE OF ENGINEERING (Affiliated to JNTUH, HYDERABAD) THIMMAPOOR, KARIMNAGAR, AP-505 527. 2011-2012
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SREE CHAITANYA COLLEGE OF ENGINEERING, THIMMAPOOR, KARIMNAGAR, AP-505 527
DEPARTMENT OF ELECTRICAL & ELECTRONICS ENGINEERING
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CERTIFICATE This is to certify that the project report entitled “RURAL ELECTRIFICATION AND OPTIMIZATION OF HYBRID WIND/PV POWER SYSTEM” is being submitted by G.RAMESH in partial fulfillment of the requirements for the award of the Degree of Master of Technology in Power Engineering & Energy Systems, depot. of EEE from SCCE, Affiliated to the Jawaharlal Nehru Technological University, is a bona fide work carried out by them under my guidance and supervision. The result embodied in this report has not been submitted to any other University or Institution for the award of any degree or diploma.
Project Guide T.ARUNA KUMARI, Assistant Professor, Department of EEE, Sree Chaitanya College of Engineering.
Head of the Department T.RANJANI, Associate Professor, HOD, Department of EEE, Sree Chaitanya College of Engineering.
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ACKNOWLEDGEMENTS The Satisfaction that accomplishes the successful completion of any task would be incomplete without the mention of the people who make it possible and whose constant guidance and encouragement crown all the efforts with success. It is our privilege and pleasure to express my profound sense of respect, gratitude and indebtedness to our guide Sri. T.ARUNA KUMARI, Assistant Professor Department of EEE, SCCE, for his constant guidance, inspiration, and constant encouragement throughout this project work. We wish to express our deep gratitude to T.RANJANI, Associate Professor and HOD, Department of EEE, SCCE, karimnagar for her cooperation and encouragement, in addition to providing necessary facilities throughout the project work. We sincerely extend our thanks to Dr.R.V.R.K.CHALAM, Principal, SREE CHAITANYA COLLEGE OF ENGINEERING, Karimnagar, for providing all the facilities required for completion of this project. We would like to thank all the staff and all our friends for their good wishes, their helping hand and constructive criticism, which led the successful completion of this project work. We are immensely indebted to our parents, brothers and sisters for their love and unshakable belief in us and the understanding and ever-decreasing grudges for not spending time more often. We will now, since the excuse is in the process of vanishing by being printed on these very pages. Finally, we thank all those who directly and indirectly helped us in this regard. We apologize for not listing everyone here.
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DECLARATION RURAL ELECTRIFICATION AND OPTIMIZATION OF HYBRID WIND/PV POWER SYSTEM ” submitted towards the partial fulfillment of the requirements for the award of the degree of We hereby declare that the work which is being presented in this dissertation entitled, “
Master of Technology in Power Engineering & Energy Systems, Depot. of EEE, S.C.C.E, Karimnagar, is an authentic record of our own work carried out under the guidance of T.ARUNA KUMARI, Assistant Professor, Department of EEE, S.C.C.E, Karimnagar. To the best of our knowledge and belief, this project bears no resemblance with any report submitted to SCCE or any other University for the award of any degree or diploma.
Date: Place : KARIMNAGAR
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1.0
INTRODUCTION ………………...................................................... 7
1. 1 wind turbines 1.2 photovoltaic panels power converters 1.3 rising of living 1.4 increasing importance of energy efficiency
2. 0 2. 1 2.2 2.3 2.4
RENEWABLE ENERGY SOURCES …………………….,……….12 solar radiation wind power smoothing wind power output smoothing solar pv output
DESIGN 3.0 SYSTEM PROCEDURES ………………………………..21 3.1
system models A. MPPT wind power generation branch B. MPPT for pv power generation branch
4.0 ESTABLISHMENT OF WIND/PV HYBRID UNIT ………………29 4. 1 simulation of the hybrid system 4.2 optimization of hybrid system 4.3 design and optimization
5.0
ECONOMIC ANALYSIS ………………………..…….……………35
5. 1 comparation of model 5.2 case study
6.0 RESULTS ………………………………………….……………….…38 7.0 CONCLUSIONS ……………………………………...................……40 8.0
APPENDIX A
………………………………………………………41
APPENDIX B APPENDIX C 9.0 REFERENCES ……………………………………………………….47
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Abstract
With ever-increasing concerns on energy issues, the development of renewable energy sources is becoming more and more attractive. This paper first reviews both the wind power and photovoltaic (PV) power generation techniques and their maximum-power-point tracking (MPPT) methods. Then, a new stand-alone wind– PV hybrid generation system is proposed for application to remote and isolated areas. For the wind power generation branch, a new doubly excited permanentmagnet brushless machine is used to capture the maximum wind power by using online flux control. For the PV power generation branch, a single-ended primary inductance converter is adopted to harness the maximum solar power by tuning the duty cycle.
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1.0 Introduction Among the renewable energy resources, wind power has had the fastest growth in the world (at the rate of 30% annually) in many developed and developing countries over the last 20 years . For example, installed capacity in Germany is more than 20 GW with an annual output of about 40 TWh in 2007 . In order to convert the wind energy to electrical energy, two types of wind turbines are employed; fixed speed and variable speed wind turbines installed onshore or offshore . In the fixed speed wind turbine, electrical generator is connected directly to the power grid. Therefore, the generator runs at constant frequency and speed. Active and reactive power control of these turbines is described in . The variable speed wind turbine (VSWT) is used for more attraction of energy from the wind. The VSWT, which attracts 10–15% more energy, has lower mechanical stress and less power fluctuation in comparison with the fixed speed ones. Furthermore, the wind turbine is divided into two large categories: horizontal and vertical axis wind turbines. Savonius and Sherbious are the most famous vertical axis wind turbines (VAWT). The aerodynamic efficiency of the VAWT is lower than the horizontal type but complexity and price of these types are lower . One of the most important studies in the VSWT is the application of various control schemes for several purposes in the plant. Hybrid power systems are designed for the generation and use of electrical power. They are independent of a large, centralized electricity grid and incorporate more than one type of power source. They may range in size from relatively large island grids to individual household power supplies. In general, a hybrid system might contain alternating current (AC) el generators, an AC distribution system, a DC distribution system, loads, renewable energy resources, energy storage, power converters, rotary converters, coupled diesel system, dump loads, load management options, or a supervisory control system.
1. 1 Wind Turbines Larger isolated AC electrical systems can use wind turbines of the type connected to large central grids. The turbines are typically 10 kW to 500 kW. Most of the wind turbines (WT) larger than 50 kW use induction generators. They turn at a nearly fixed speed, based on the frequency of the AC network to which they are connected. They also require an external source to supply their voltage requirements. Thus, in hybrid power systems they operate only when at least one diesel generator is operating.
1.2 Photovoltaic Panels – Power Converters Sunlight may be used to generate electricity directly via photovoltaic cells. Photovoltaic panels (PV) are inherently a DC power source. As such, they usually operate in conjunction with storage and a separate DC bus. In larger systems, they may be coupled with a dedicated inverter and thus act as de facto AC power source. Electric energy has wonderful properties for improving living conditions, for creating wealth and for providing widespread communication facilities. Electricity literally gives power
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to the people. That is why demand for electric energy will continue to increase. Most electric energy is still produced from fossil fuels with their finite resources and the associated greenhouse gas emissions. It would be wrong to continue the traditional burning of fossil fuels at a high pace until they are depleted. Those carbons and hydrocarbons also provide valuable ingredients for the petrochemical industry. Renewable energy sources have a long way to go before they can fully replace the use of fossil fuel. Most renewable electricity sources from wind, solar radiation and biomass have properties that make them less attractive from an availability and flexibility point of view, at least compared with traditional power plants. It is therefore crucial to develop smart power generation and distribution facilities that can support electricity generation from renewable sources. Such smart power generation units have to make optimum use of the available fuel resources at possibly minimum costs and minimum impact on the environment.
1.3 Rising standard of living With the developing countries becoming more and more developed, the standard of living is rising, and, at the same time, the demand for energy is increasing. Higher standard of living – and especially higher level of education made possible with that – is connected with decline in population growth, but it is also setting new demands on the production of electricity. The more material prosperity there is, the larger parts of commodities are dependent on electricity. The developing countries rely heavily on the fossil fuels in their energy production, so the demands for more electricity will increase the amount of fossil fuels burnt to produce it. In many cases, it is difficult to find alternative sources of energy either because of natural Conditions – for example lack of rivers to harness for hydropower, or alternating periods of floods and drought making potential hydropower unreliable – the economic situation, or political unrest.
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The proportion of renewable energy is increasing worldwide – for example, wind power has a growth rate of about 20% – and it is important to maintain the trend because of the increased demand for electricity in the developing countries. The solution is not to restrict that demand, but to try to make the role of fossil fuels less dominant. It will be difficult, and it will have to be a common effort. There is no universal solution, no single and simple answer to be found. All the efforts to help the developing countries to adjust their production of energy and electricity to the higher standard of living has to take into account the local conditions. That is the only way to resolve the problem in a sustainable way, in a way acceptable to all involved, and in a way that will have the most benefits both locally and globally. The stakes are high, not just for us, but for the generations to come.
Increasing importance of electricity The total dependence of our society on electricity is obvious – but at the same time surprisingly easy to forget. The role of electricity in modern society is so inherent, that we do not even think about it. It is self-evident that all the appliances at home and at the office, all the communications, heating, air-conditioning, lighting, many modes of transportation, and so on…just work. But they would not if there was no electricity. The need for electricity might seem to be easily fulfilled – all it takes is to put a plug into a socket – apprehending what it takes to produce that electricity might be difficult. With the cordless technology relying on batteries being used all the time more commonly, this comprehension is becoming even more difficult. However, electricity has to be produced, and for the most part it has to be produced now, right at this moment. Surely electricity can be stored, for example in the use of hydro power, when large reservoirs of water contain ”electricity” available for the future use. However, this a very
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restricted type of storage. So in general, storing electricity is possible, but not very efficiently, nor for very long periods of time, nor in large amounts – at least not in any practical way fitting for the main electric power needed by modern society. It is only during a power outage that our almost complete dependence on electricity becomes obvious. Without electricity there is no light, no heat, no warm food or water. There is no communications, no music, no movies. Practically nothing we have been used to utilize at work and in leisure. Some of the problems brought about by the lack of electricity can be solved with solutions like fire for light and warmth, batteries for communications and entertainment, cars with combustion engines for transportation instead of public vehicles like trams, subways, and trains – but all these are more or less temporary solutions, and in many cases eventually dependent on electricity too. And the development is towards an even more profound dependence on electricity. Electrical appliances are more and more frequently used for tasks nobody would have dreamed of only few years ago. While many – if not most – electrical devices are not essential for leading a life, some of them are vitally important, without which people’s lives would be in danger. This is putting an ever-increasing pressure on reliable power plants and grids.
1.4 Increasing importance of energy efficiency The reserves for the fossil fuels are limited and, what is more important, it is impossible to make use of all of those reserves. At the current rate they will not be exhausted for a few decades, but they will become a more and more marginal source of energy. Even prior to that, the price of using the fossil fuels will substantially increase because of the higher costs for acquiring them and the carbon taxes levied on burning of them. There is a limit for the available amount of many non-combustion and renewable energy sources, too. The rivers suitable for hydropower plants are in many countries already harnessed for energy production. Wind and sunlight are practical only in areas having strong winds and a lot of sunshine. Nuclear fission power contains potential risks, in the long run because of the radioactive waste and, more imminently, because of accidents. And the situation of the deployment of nuclear fusion power is more or less the same as it has been for the past decades: still some 30 years in the future. All these potential and real problems mean that a sustainable Solution for the problem of meeting the increasing need for energy, and especially electricity is imperative. It is impossible for the solution to be just increasing the production of electricity with potential increase in the severity of the problems. Whatever the method, there is no possibility for an exponential growth. There are limits set by technology, economics, and resources. An obvious solution is to use energy more efficiently. Much has already been done. The energy efficiency of electric appliances has vastly improved. With the same amount of energy – or electricity – their output is much larger. Because of rising standard of living the total number of appliances in the world will inevitably and continuously increase, so this would also help to decrease the need for increased production
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of electricity. Energy efficiency – and energy conservation – is also helping us to lessen the dependence of our society on electricity.
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2. 0 Renewable energy sources Issues of Wind turbines and Photo-Voltaic Cells: As the wind does not blow all the time nor does the sun shine all the time, solar and wind power alone are poor power sources. Hybridizing solar and wind power sources together with storage
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batteries to cover the periods of time without sun or wind provides a realistic form of power generation. This variable feature of wind turbine power generation is different from conventional fossil fuel, nuclear, or hydro-based power generation. Wind energy has become the least expensive renewable energy technology in existence and has peaked the interest of scientists and educators the world over. A simple relationship existsrelating the power generated by a windturbine and the wind parameters: P = 0.5rA Cpv3hg hb (1) where, r = air density (about 1.225 kg/m3 at sea level, less at higher elevations). A = rotor swept area, exposed to the wind (m2). Cp = Coefficient of performance (.59 to .35 depending on turbine). v = wind speed in meters/sec hg = generator efficiency hb = gearbox/bearings efficiency A mast-mounted anemometer (wind meter) allows the students to directly measure wind speed and to vividly relate this easily felt force-of nature to electrical measurements. Photo-Voltaic or PV cells, known commonly as solar cells, convert the energy from sunlight into DC electricity. PVs offer added advantages over other renewable energy sources in that they give off no noise and require practically no maintenance. PV cells are a familiar element of the scientific calculators owned by many students. Their operating principles and governing relationships are unfortunately not as pedagogically simple as that of wind-turbines. However, they operate using the same semiconductor principles that govern diodes and transistors and the explanation of their functioning is straightforward and helps to make more intuitive many of the principles covered in semiconductor electronic classes. Most industrial uses of electricity require AC or alternating 60 Hz power. Wind-turbines and PV cells provide DC power. A semiconductor-based device known as a power inverter is used to convert the DC power to AC power. This device has a relatively simple operation that is a vivid illustration of many topics traditionally covered in power electronics classes. The inverter also introduces the problem of power quality. Power quality is an extremely important issue in real-life industrial electric power systems. Power quality is the contamination
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of the voltage or frequency characteristics of electric power. The system exhibits many common problems of power quality such as voltage sag (sudden drops in voltage due to over demand of battery capacity and/or loss of wind or sun), harmonic contamination (errors in the 60 Hz frequency due to nonlinear loads such as computers, energy efficient light bulbs, laser printers, scanners), and voltage regulation problems (prolonged drops in voltage due to interactions of system elements). Power quality is an extremely important problem in industrial electricity applications and this setup offers unique opportunities for the students to study power quality problems in a real system. 2. 1 Solar radiation With the exclusion of nuclear and geothermal energy, most energy resources on and in this world originate from the sun. The sun can be seen as a huge nuclear reactor with a radiating power of 300 million exawatt. When this is fully written out, it is 300 000 000 000 000 000 000 000 000 watt. The earth, being just a very small part in the total radiation sphere of the sun, receives only about a quarter of a billionth of this energy, equalling 810 PW. In the year 2008, the total primary energy supply to the world’s economies was 12,267 megatonne oil equivalent, equalling 514 exajoule. Averaging this amount of energy over a full year means a continuous energy flow of 16.3 terawatt (TW). This is only 0.02% of the 810 PW of energy that the earth receives from the sun. Suppose that with a fair distribution of wealth, all habitants of the world would use the same amount of energy as the average US Figure 2.12: Estimated reserves of the major fossil fuels in the world and their depletion. 62 Smart power generation citizen uses today. In that case, the total primary energy input to the world should be four times as high as today. That would mean that capturing slightly less than 0.1% of the energy radiated from the sun to the earth would be sufficient for providing everyone with plenty of energy. The fact is that capturing this amount of energy is not easy. Geologists have calculated that it took the earth some million years to build up the fossil fuel resources that are used now in one year. The current use of fossil fuels resembles a rapid discharge of the earth as a battery, while charging it took an aeon.
Vegetation has a low efficiency of capturing solar energy. Forests and wheat have a capturing efficiency of only 0.25%, while straw is relatively much better with about 2%. Everybody will agree that even 2% is still a very low number since one cannot cover the world with straw producing plants. As an illustration, if all grain produced in the world would be converted into liquid bio fuel, it would cover only 10% of all current petrol use. In this respect, photo voltaic cells with their solar-energy capturing efficiency of 10 to 15% perform much better than most plants. However, plants will reproduce, whereas solar cells must be replaced regularly. A major
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problem in producing electricity from direct solar radiation is the unpredictability and variability of sunshine. Countries in the higher latitudes, such as Canada and Finland, lack the necessary sunshine at those times of the day and year when electricity is needed most. Fortunately, in areas such as the Middle East and Mexico, the peak in solar radiation practically coincides with the maximum need for cooling buildings. Transporting electric energy via high voltage lines from sunshine countries to darker and colder countries is still prohibited by the required massive investments. Let us use an illustrative example. The distance from the sunny Sahara to northerly Finland is some 5000 kilometer. An ac transmission line of this length would be unstable because of the phase shift between voltage and current and would introduce energy losses of about 10% per 1000 km. An emerging alternative is using high-voltage dc lines. Such dc lines lose about 2 Electricity highly in demand 63 4% energy per 1000 km, so roughly 20% would be lost during the 5000 km trip. Scientists carry out investigations with high-temperature superconducting dc lines that might have a much higher power capacity for a given wire diameter. That is however something for the future. Literature sources mention that a ‘conventional’ high-voltage dc connection with a maximum capacity of 1600 MW covering the 5000 km might require an investment of about 1200 M€, or 750 €/ kW. That seems relatively cheap compared with the estimated costs of the Olkiluoto 3 nuclear power plant of 3750 €/kW mentioned earlier. The photovoltaic power plant in the Sahara that will feed its power output into the dc line should not have a peak output of more than 1600 MW, otherwise the transmission line cannot handle the output. Even in the Sahara, the averaged output of PV-based power plants will not be more than 20% of the peak output, with most of the energy produced in the hours around noon. During the night, PV cells produce nothing. Therefore, the power supplied into the high voltage dc transmission line averaged over a day will only be 20% of if otherwise peaking power had to be installed for covering daytime
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peaks around noon. Expectations, or at least hopes, are that due to technological developments and competition, the price of PV cells will drop to below 1000 €/kW (peak). In Spain, the annual average solar radiation intensity is about 5100 Wh/m2 per day (see figure2.15). In London and Helsinki, the number drops to about 3100 Wh/ (m2day). The correlation between light intensity and the season in figure 2.15 is obvious. In the darker seasons, the irradiation from the sun is substantially lower than in summer. In December in London, only 1000 Wh/(m2day) is received versus 5800 Wh/(m2day) on a summer day. In Helsinki, the difference is even larger. The daily pattern in solar irradiation results in an averaged level that at maximum reaches roughly 30% of the peak level. In practice, the variability in solar irradiation including cloud effects make that the capacity factor of a PV cell at the mentioned locations will never reach a value higher than 20% over the year. In countries with a latitude higher than 50°, a capacity factor of 10% or less is a more realistic figure. Another option for capturing solar energy is using solar radiation for steam production. This technology is called Concentrated Solar Power and uses mirrors to concentrate the solar radiation from over a large area on a small plane to create a high temperature. Part of the heat captured will be used directly for steam-turbine driven generators to generate electricity, while another part will be stored in special molten salts for use when the sun is not shining. This means that such a concept could also produce electricity during the night. Issues are still present with capital costs of at least 4000 €/kW and with reaching a good efficiency.
2.2 Wind power Wind, a renewable energy source indirectly caused by solar radiation, also has problems of variability. At an optimum location, generally offshore, a wind-mill-driven generator will only run at its nominal (= name plate) power during 30% of the time, while at most land-based locations that will take place may be 20% of the time. An example of the dependence of the output of a wind turbine on wind speed is given in figure 2.16. Because wind speed varies in time, the output of a wind park can have a distribution during the year as shown in figure capacity factor of 25% to 35% is the best that can be expected. Figure 2.16 reveals that during a large part of the year, individual wind turbines have no output at all. Therefore, wind parks always needs backup power. Although 24-hour wind level forecasts are quite accurate, wind speeds can change quickly and unpredictably so that the back-up capacity should have the ability to react very fast. Table 2.1 compares the wind speed expressed in m/s with knots and the Beaufort scale, since the latter scale is more familiar for most readers. Difficult situations arise especially when a wind park is operating at its nominal output and the wind speed suddenly increases to values where the wind turbines have to be shut down to prevent damage. That happened for instance in Denmark on January 8, 2005. As a result, electricity production by wind
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power dropped from 2000 MW to about 200 MW in a very short time. Such an event happened on a smaller scale in the North Plain of Germany on August 23, 2010, when a severe storm passed by. The arrays of wind mills were initially spinning at maximum capacity when they had to be stopped due to distribution of a wind-mill-driven generator at an optimum location (blue) and a standard location (red) during a year (= 8760 hours). the high winds. At the same time, it became dead dark so that lighting had to be switched on in a wide area, meaning a substantial increase in electricity demand. Such events require a substantial amount of rapid back-up capacity.
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2.3 Smoothing wind power output The energy output from wind turbines appears to be very variable. Short-duration high peaks are interspersed with periods of moderate output and sometimes up to 10 days without any output at all. To cover 10 days of no output from wind by energy storage, much energy has to be stored.
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High peaks of short duration in wind output allow only a short time for energy storage, while releasing the stored energy back into the grid might take a much longer time. However, the opposite can also be true. An extreme case helps to illustrate these issues. In an example based on data from Denmark, a wind farm with an installed capacity of 500 MW experiences high winds for 3.3 days followed by no wind for 10 days. The total time span of this mental experiment is therefore 3.3 + 10 = 13.3 days. We will now try to find out how energy storage can flatten the variable output of the wind farm into a constant output. Figure 3.39 schematically represents the storage system and figure 3.40 illustrates the result. The averaged output of the wind farm during the 13.3 days in this example equals 500 3.3/(10 + 3.3) ≈ 125 MW, representing a capacity factor of 125/500 100% = 25%. The storage system intended to flatten the output of the wind farm is presumed to have a ‘turn-around efficiency’, or ‘round-trip efficiency’, of 80%, resulting in losing 20% of the energy sent to the storage system. This means that the average output of the combination of wind farm and accumulator will be less than the average output of 125 MW from the wind farm. Some iterative calculations reveal that the average net output from the combined system of wind farm and storage system will be about 105 MW. During the 3.3 days with the high output from the wind farm, the energy splitter ensures that 105 MW is directly sent to consumers.
2.4 Smoothing solar PV output Smoothing the daily variations of electricity output from solar PV with energy storage provides another example. On an average summer day, with only a few occasional clouds passing by, the capacity factor of solar PV can reach about 15% in many areas in the world. Figure 3.41 gives in blue the output pattern of a PV unit of 10 kW peak capacity. This output has the shape of the PV output pattern in figure 3.34 for June 21, 2010 in Germany. A PV unit of 10 kW (peak) with a 15% capacity factor will then produce per day: 10 kW 24 hours 0.15 = 36 kWh. With energy storage, we can smooth these 36 kWh into a flat consumption level during the intermediate load hours between 7 am and 23 pm. The smoothed power output is then 36 kWh/(23–7h) = 2.25 kW, if we ignore the energy losses involved with storage. Early in the morning, right after 6 o’clock, the output of the PV cell slightly exceeds the consumption of 2.25 kW so that the battery will store a tiny amount of energy. Between 7 until 8, electricity consumption exceeds electricity production so that the battery releases some energy. From 9 am until 6 pm, the PV system will directly deliver 2.25 kW of electricity to consumers, while the remaining electricity produced is stored in the battery. Ultimately, the battery will store some 25 kWh during the day. With a lead-acid battery, the battery capacity should be at least 50 kWh because of the limited depth of discharge of 50%. This involves an investment of about 50 kWh 75 €/kWh = 4000 €, while the PV cell might cost 30,000 € (= 10 3000 €/kW (peak)). Therefore, daily smoothing of the output of solar PV with batteries will just slightly increase the costs of PV-based electricity in this example. Yet, the costs of such a PV-based electricity supply system are very high because of the high capital investment per effective kW. Even if the price of solar PV cells drops to 1000 €/kW (peak), an investment of 10,000 € + 4000 € = 14,000 € for a unit with 2.25 kW of smoothed output remains very high. The example of storing PV electricity to create a smooth output during intermediate load hours as given here is somewhat positive in respect of costs. In reality, during a very sunny day, the PV cell will send out its peak
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power, resulting temporarily in charging power higher than in the example given above by a factor of 2.5. This means that the energy charging system has to be designed for a high power level. Moreover, even in summer, a series of dark days can occur so that much more storage capacity is needed than given in the example. In addition, the energy losses connected with battery storage have not been taken into account here. In the darker seasons, the output of solar PV systems can be close to zero for a number of months. Suppose there is a large PV plant of 100 MW (peak) in the south of Germany, while half of its annual electricity production is sent to pumped-hydro storage for use in the dark months of November, December, January and February. The capacity factor of solar PV in Germany is only 6%, so the annual electric energy produced by the 100 MW (peak) plant is 100 MW capital invested, the resulting additional costs for storage are at least 755 M€ 0.08/21.6 GWh = 2.8 €/kWh. This example shows that storing solar energy from production in summer for use in winter is not an economically viable option. The examples given prove that storing electric energy over time spans of more than a few days is prohibitively costly. For windbased systems with enough storage to cover 10 days of now into smoothed intermediate load.3 Electricity generation – matching production with demand 1210.06 8760 hours = 52.6 GWh. The elevated water basin to store 90% (due to efficiency loss) of half of this 52.6 GWh will cost about24 GWh 30 M€/GWh = 720 M€ (see table 3.4). The required pumping power capacity is estimated at 70 MW to accommodate the peaks in PV output. The turbine-generator capacity that has to deliver the electricity in the dark months will be about 15 MW. Pump, turbine and generator require an estimated capital investment of some35 M€. Additional transmission line investments have again been left out here. The total investment of 720 + 35 = 755 M€ is needed for supplying only 24 GWh 0.9 = 21.6 GWh per year. The 0.9 is again the efficiency of the water-turbine-generator combination. In assuming annual capital costs, depreciation and operation and maintenance costs of 8% of the ind, the combined costs of electricity production will be at least 23 €cts/ kWh. Storing solar energy from the bright summer days for the dark winter season can raise the costs of solar-PV-based electricity to 400 €cts/ kWh. Producing electricity with coal-fired, gas-fired and nuclear generators costs on average only between 4 and 8 €cts/kWh.
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3. 0 SYSTEM DESIGN PROCEDURES
single-ended primary inductance converter (SEPIC) The proposed wind–PV hybrid generation system possesses the following features. 1) Similar to other wind–PV hybrid generation systems [21]–[23], the proposed system utilizes the battery tank and inverter to couple the wind power and PV power branches. Additionally, the PV power can directly be used for dc field excitation of the doubly excited PM generator, rather than conducting dc/ac conversion that involves inevitable power loss. Thus, this feature is particularly advantageous for a small-size stand-alone wind–PV system in which the PV panels are mounted onto the pole of the wind generator and the resulting PV power is relatively limited. 2) The wind power generation branch and the PV power generation branch of the hybrid generation system can independently be controlled, hence achieving the MPPT simultaneously. 3) Compared with an individual generation system (the wind power or the PV power), the wind– PV hybrid generation system cannot only harness more energy from nature but also allow the wind power and the PV power to complement one another to some extent between day and night. 4) For the wind power generation branch, the doubly excited PM brushless generator, as shown in Fig. 3, adopts the outer rotor topology [24], which enables the rotor to directly couple with the wind blades. Hence, it can eliminate the complicated mechanical transmission and the relevant costs. Also, since the proposed generator adopts two excitations (PMs and dc field windings), it can flexibly regulates its magnetic field distribution and consequently control the output voltage and power. Thus, without using an additional power converter, which usually exists for the conventional MPPT, the generator itself can adjust the output power at a given wind speed and realize the MPPT. 5) For the PV power generation branch, solar energy is directly converted to electricity by the PV panels and then controlled by a SEPIC for the MPPT. This PV power generation branch processes the merits of simple structure and uncomplicated control. 6) As compared with the latest wind–PV hybrid generation systems [21]–[23], the proposed system offers some distinct energy-efficient merits. First, the system in [21] was simply based on parallel operation of a wind-driven induction generator and a battery-coupled PV array via a
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three-phase inverter. This system cannot perform any efficiency optimization for the wind generator or the PV array. Also, because of inevitable rotor copper loss, the induction generator inherently suffers from relatively lower efficiency than the PM brushless generator. Second, the system in [22] was based on parallel operation of a wind-driven PM synchronous generator and PV panels with a battery bank as energy storage. It utilizes a dc/dc converter to perform the MPPT for the PV panels, while it attempts to use a three-phase rectifier and another dc/dc converter to maximize the wind power generation. It is anticipated that this system can offer higher efficiency than the previous one [21] since it utilizes the MPPT to harness PV power and a PM brushless generator to capture wind power. However, the use of a dc/dc converter to maximize the wind power generation is too idealized or impractical, which may even impair the originally captured wind power. The whole system of [22] was assessed by computer simulation only. Third, the system in [23] was based on parallel operation of a wind-driven induction generator and a PV array with a battery bank as energy storage. It employs a three phase spacevector PWM ac/dc converter to regulate the d- and q-axis current in such a way that the captured wind power can be maximized, while it utilizes a dc/dc converter to perform the MPPT for the PV array. This system is more practical than that in [22] and should offer higher efficiency than that in [21], but it still suffers from relatively low efficiency of the induction generator and relatively complex control due to d–q-coordinate transformation. The configuration of the proposed system is similar to that in [22] and [23] but with a special doubly excited PM brushless generator. Hence, it can inherit the high efficiency of PM brushless generators, while it can employ simple dc current control to perform efficiency optimization over a wide range of wind speeds. Therefore, the proposed system can offer higher efficiency than other wind–PV hybrid generation systems. 7) In terms of costs, the proposed hybrid system definitely takes an advantage of lower cost than two individual wind and PV power systems since it can share the same battery tank for energy storage [25]–[27], the same inverter for dc/ac conversion, and the same digital hardware for the MPPT. As compared with other wind–PV hybrid generation systems [21]–[23], the proposed system will be relatively more costly than that in [21] and [23] but less costly than that in [22], which is due to the fact that the induction generator is cheaper than the proposed doubly excited PM brushless generator, while the conventional PM synchronous generator desires more PM materials and, hence, more expensive than the proposed one. Nevertheless, taking into account the reduction of operating cost due to efficiency optimization, the proposed system is still more cost effective than that in [21] and [23].
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3.1 SYSTEM MODELS A. MPPT for Wind Power Generation Branch Based on the Betz theory, the mechanical power extracted from the wind power can be written as [13], [28] Pmech =1/2πCp(λ, β)ρv3 wR2
(1)
where Cp(λ, β) is the wind power conversion efficiency factor with a typical value of 0.4 or below, vw is the wind speed with a typical range of 3–12 m/s, ρ is the air density with a typical value of 1.25 kg/m3, R is the wind blade radius, β is the blade pitch angle, and λ is the TSR that is defined as λ = ωR/vw (2) where ω is the angular speed of the wind turbine shaft or the generator shaft. Taking into account the power losses in the generator and rectifier, the net rectifier output power is Prect = ηPmech (3) where η is the combined efficiency of the generator and rectifier. The conversion efficiency factor Cp(λ, β) is maximized as Cp−max, based on the condition that the TSR takes the specific value of λopt and the blade pitch angle β is equal to zero. The value of Cp−max is always kept as a constant for all existing maximum power points. Therefore, if ω can be controlled at different wind speeds, the maxima of Pmech and Prect can be obtained as Pmech−max =1/2π(Cp−maxρR5 λ3opt)ω3 (4) Prect−max =1/2ηπ_Cp−maxρR5λ3opt_ω3. (5) Regarding the efficiency η as a constant, there is only one variable ω in (5). Fig. 4 shows typical power curves under different wind speeds. It illustrates that, for a given wind speed, the maximum power point can be determined by dPrect/dω= 0. (6) According to the chain rule, (6) can be expressed as dPrect /dω= dPrect dVr dωe/ dVr dωedω= 0
(7)
where Vr is the rectifier output voltage and ωe is the electrical angular speed of the generator. This ωe is related to the turbine shaft (or the generator shaft) speed ω by ωe =pω (8) =p > 0 (9) where p is the number of pole pairs of the generator. The rectifier output voltage Vr is proportional to the generator phase voltage Vph, as given by Vr = kVph (10)
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where k is a constant with a typical value of √6 when open circuited. For normal generation, it yields > 0. (11) From (10) and (11), it deduces to > 0. (12) Therefore, using (7)–(12), (6) can be rewritten as dVr= 0. (13) From Fig. 4, it can be observed that there is only one extreme point of Prect at a specific vw. Hence, there is also only one extreme point of Vr to achieve the maximum value of Prect.
Fig. 5. DC field current control circuit. Fig. 6. MPPT process for the wind power generation branch. For the doubly excited PM brushless machine, its output voltage can be regulated by simply tuning the dc field current [24], which can be expressed as Vr = kVph = k /2π CeΦω (14) where Ce is the electromechanical coefficient and Φ is the flux linkage. For a given vw, ω is also fixed. Thus, Vr is directly proportional to Φ and, hence, the dc field winding current If Φ ∝ If (15) Vr ∝ If .
(16)
Therefore, the rectifier output voltage and, hence, power can be regulated by simply tuning the dc field current. Fig. 5 shows the dc field current control circuit. The H-bridge circuit functions to provide bidirectional control of dc field current so that the dc field coil can provide positive field to
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strengthen the PM field or provide negative field to weaken the PM field, hence achieving flexible flux control for efficiency optimization. It should be noted that there is almost no electromagnetic coupling between the dc field windings and the ac armature windings due to the special structure of the proposed generator. The amplitude of the field current can easily be regulated by adjusting the duty cycle δ of the H-bridge circuit. Fig. 6 shows the MPPT process under a specific wind speed, which is based on the PAO method. If the starting point is from. TABLE I PAO ALGORITHM FOR WIND POWER GENERATION Perturbation Positive
Change in voltage Positive
Change in power Positive
Next Perturbation Positive
Negative
Negative
Negative
Positive
Positive
Positive
Negative
Negative
Negative
Negative
Positive
Negative
The system design method in this paper is shown in Fig.1 [1][2]. First, we calculate the amount of load current. Next, we consider the regional characteristics, i.e., limited space for available, the constraint of weather condition, etc., and determine the available energy. And then, we determine the number of wind power generators, whose total output is comparatively discrete, as shown in equation (1): Wind power generation current < Current demand load (1) In the process of design, we adopt the concept that is that the undercurrent demand is complemented by photovoltaic power generators, whose capacities can vary bit by bit compared with wind power generators. Based on undercurrent demand, the parallel number of photovoltaic power generators is obtained. And then, since this calculation leads a number of candidates, we determine a system predicted on selection criterion as follows: a) Power generation utilization rate is sufficiently high. Generation Power Utilization Rate [%] Gross generation ampacity [Ah] = Loaded current demand[Ah] (2) b) There are no extreme deviations in power generation output ratio of various renewable energies. c) From the viewpoint of output stability of the system, it is desirable that multiple numbers of generators should be provided. d) Comparison is made in terms of construction costs of the systems. e) When similar results have been obtained for most items listed, select the system having much excess current ampacity. In the above design procedures, the undercurrent demand is not generated. Therefore only the battery capacity for 10-day-load backup will become necessary, and we determine the battery capacity.
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Fig. 8. Equivalent circuit of the PV panel.
Fig. 9. Typical current–voltage curves of the PV panel
Fig. 10. SEPIC circuit topology.
Fig. . MPPT flowchart for the wind power generation branch.
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the left-hand side of the maximum power point, the voltage adjustment follows the direction of dPrect/dVr. Thus, the increment of Vr increases Prect. In contrast, if the starting point is from the right-hand side of the maximum power point, the voltage adjustment is opposite to the direction of dPrect/dVr. Thus, the decrement of Vr increases Prect. Therefore, if there is an increase in power, the subsequent perturbation will be kept unchanged until the maximum power point is reached; otherwise, if there is a decrease in power, the perturbation will be reversed. This perturbation algorithm is summarized in Table I. The flowchart of the whole MPPT process is shown in Fig. 7, where Vr int is the initial value of Vr, Vmax and Vmin are the maximum and minimum settings of Vr, δ0 and Δδ are the initial value and step size of the duty cycle of the Hbridge circuit, respectively, and Vrk and Irk are the kth steps of Vr and Ir, respectively. B. MPPT for PV Power Generation Branch Fig. 8 shows the equivalent circuit of a PV module. Its mathematical expression can be written as [29], [30]
Fig. 12. Prototype of the proposed hybrid generation system. (a) Wind power generation branch. (b) PV power generation branch.
Fig. 11. MPPT flowchart for the PV power generation branch
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+ I = IL – ID exp
− 1
−
(17)
where V is the output voltage of the PV module, I is the current output, ID is the diode saturation current, q is the electron charge, A is the material factor of the p-n junction, K is the Boltzmann constant, T is the absolute temperature, RS is the intrinsic series resistance, and RSh is the parallel resistance. From (17), a typical set of current–voltage curves of the PV module can be obtained, as shown in Fig. 9. It can be seen that when the voltage increases, the current goes down. Therefore, the maximum power point occurs at the corner. Hence, by properly tuning the output voltage, the MPPT can be performed under different irradiance levels. Although different MPPT methods have been proposed for PV power generation, the PAO one is still the most common method in practice due to its simplicity and system independence. Thus, the proposed PV power generation branch adopts this method to perform the MPPT. Fig. 10 shows the circuit topology of the SEPIC for the PV power generation branch, where Vpv and Ipv are the output
voltage and current of the PV panels, respectively, L1 and L2 are the circuit inductors, C1 and C are the circuit capacitors, and RL is the load resistor. The SEPIC takes the definite advantage of nonpulsating input current, as well as the capability of both step-up and step-down features. By operating the SEPIC in discontinuous capacitor voltage mode, the input voltage Vi, output voltage Vo, and input resistance Ri can be expressed as (1 − D)
Vi =Vpv = Vo =
Vpv
–
(18) (19)
d= Ri =
2
(20) =
(1 − D)
2
(21)
where Ts and D are the switching period and duty cycle of the control signal, respectively. From (21), it can be seen that Ri changes with D, namely, Ri decreases with the increase of D. Hence, by properly perturbing the duty cycle, the input resistance of the SEPIC can match with the load resistance, hence achieving the maximum power transfer. Fig. 11 shows the corresponding flowchart for the MPPT, where Vbatmax is the maximum charging voltage of the battery tank, D0 and ΔD are the initial value and step size of the duty cycle of the control signal, respectively, and Vpvk and Ipvk are the kth steps of Vpv and Ipv, respectively.
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4.0 Establishment of a Wind/PV Hybrid Unit The hybrid unit contains two complete generating plants, a PV solar cell plant and a wind-turbine system. These sources are connected in parallel to a 12V DC line. The power is next connected to a DC to AC inverter and is then supplied from the inverter’s output to a singlephase 60 HZ, 120 VAC load. The overall project structure is presented in Figure 1. The wind turbine is installed at the top of a steel tower that has a height of 18.3 meters and a diameter of 8.9 cm. The wind turbine depicted is a 0.7 kW unit and the solar panels depicted number four in all with a capacity of 50 Watts each. The instrumentation panel depicted monitors the outputs of the generator using digital panel meters. A small wind turbine was chosen for its low maintenance and many safety features. One of the low maintenance features is the turbine’s brushless alternator and an internal governor. The turbine generates 0.4 kW when turning at its rated speed of 47 km/hr and it is capable of generating up to 0.7 kW at its peak wind speed of 72 km/hr. The actual system’s pictures are shown in Figure 2. The turbine’s blades are made of a carbon fiber reinforced composite that will intentionally deform as the turbine reaches its rated output. This deformation effect changes the shape of the blade, causing it to go into a stall mode, thus limiting the rotation speed of the alternator and preventing damage in high winds. Another feature of the wind turbine is a sophisticated internal regulator that periodically checks the line voltage and corrects for low voltage conditions. The solar panels are 12 VDC units and were chosen for their ultra clear tempered glass that is manufactured for long term durability. Figure 3 shows the DC voltage measured across the 12 volt DC bus where the wind turbine and PV arrays outputs are connected. A slight ripple in power regulation can clearly be seen. This ripple is a function of the unpredictable nature of wind and sunshine along with the dynamic effects of the electrical load. As mentioned earlier, one of the largest problems in systems containing power inverters is power quality. This problem becomes serious if the inverter used in the system does not have a good sinusoidal waveform output and causes problems such as harmonic contamination and poor voltage regulation. According to the IEEE (a professional society which codifies such issues) standards, a maximum of 3 to 4% total harmonic distortion (this is a quantitative measure of how bad the harmonic contamination is) may be allowed from inverter outputs. However, many inverter outputs have much more harmonic distortion than is allowed. The inverter used in this system has a power rating of a 1.5 KVA and was manufactured by Trace Technologies ®. The battery banks contain 4 deep-cycle lead-acid batteries connected in parallel. High power capacity heating resistors, energy efficient light bulbs, incandescent light.
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Figure 1. Established Wind/PV hybrid power generation unit.
30
Figure 2. Actual pictures of wind/PV hybrid power station.
bulbs, and two small AC motors constitute electrical loads that can be applied to the system. To monitor and store the voltage, current, power, and harmonic contamination data, two Fluke ® power quality analyzers (types 39 and 41) are used in the system. In addition, permanently
Figure 4&5. AC load voltage and current waveforms, current harmonic spectrum of system mounted AC/DC digital panel meters form part of the system’s instrumentation. A laptop computer is interfaced to the system via the Fluke power quality analyzers to store data in realtime. Figure 4 illustrates such data as voltage and current waveforms on the load side of the inverter in the case of small heat and lighting loads connected to the system. As shown in figure 4, the current waveform is much more distorted than voltage waveform. Since current harmonic contamination has a more detrimental effects on industrial power quality problems than voltage harmonic contamination, the current harmonic spectrum of the inverter output is vivid illustration of the pitfalls present in the measurement of real power quality problems in industrial simulations. Figure 5 illustrates the current harmonic spectrum in the case of nonlinear loads. A harmonic spectrum is a graphical plot of harmonic contamination on the y- axis and the
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frequency where this contamination occurs on the x-axis. This plot is commonly used in industry to study harmonic contamination and its possible remedies. Voltage sags may cause a crucial damage to high precision measurement and protection devices, especially computer equipment present in many highly-automated industrial plants. A voltage sag example for the system is shown in Figure 6.
Figure 6. Voltage sags recorded in the wind/PV system.
-----------------------------------------------------------------------------------------------------------------------
Figure 7. PSCAD/EMTDC Simulation of system with load and RLC filter.
4. 1 Simulation of the Hybrid System Figure 7 presents the overall system including a passive RLC filter on the AC side of inverter. This filter is a circuit made up of a resistor (R), inductor (L), and a capacitor (C). Such filters are
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commonly installed in industrial situations to remedy power quality problems. The inverter is of a twelve pulse type and the inverter and the control circuit models are both standard When To Consider An Hybrid Solar-Wind System Even during the same day, in many regions worldwide or in some periods of the year, there are different and opposite wind and solar resource patterns. And those different patterns can make the hybrid systems the best option for electricity production. The Combination The combination involved on hybrid systems is rather obvious: to get a target goal of, say, 120 kWh of electricity per month we can use a single 3kW wind turbine (instead of a 6kW one...) and a solar system with a smaller array of modules. Size And Price An hybrid wind-solar electric system demands an higher initial investment than single larger systems: large wind and solar PV systems are proportionally cheaper than two smaller systems... But the hybrid solution is the best option whenever there is a significant improvement in terms of output and efficiency - which happens when the sun and the wind resources have opposite cycles and intensities during the same day or in some seasons.
4.2 OPTIMIZATION OF HYBRID SYSTEMS Different types of hybrid systems and modeling [3] procedures, performance studies of hybrid systems, operating strategies, economic analysis and case studies are discussed in details. The technical terms of interest are: Deficiency of power supply probability The Deficiency of Power Supply Probability (DPSP) is defined as the sum of the deficit in power generated by hybrid system with respect to the total annual load. Relative excess power generated The Relative Excess Power Generated (REPG) for the hybrid system is defined as a ratio of the total annual excess power generated by the hybrid system in a year to that of the total annual load.
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Energy to load ratio Energy to Load Ratio (ELR) is used for designing the system and analyzing performance of the hybrid system. It is the ratio of energy produced by the renewable components to energy demand. Life cycle cost Life Cycle Cost (LCC) of a hybrid system consists of initial capital investment, the present value of operation and maintenance cost and the battery replacement cost. Life cycle cost analysis is a tool used to compare the ultimate delivered costs of technologies with different cost structures. Levelised energy costs The Levelised Energy Costs (LEC) is defined as the ratio of the product of LCC with capacity rate factor (CRF) to the energy generated per year. Life cycle unit cost Life Cycle Unit Cost (LUC) is defined as the ratio of life cycle unit cost to the total power generated for a given period of time. 4.3. DESIGN AND OPTIMIZATION METHODOLOGY 5 In a PV-wind hybrid system with battery autonomy, the optimization of the size of the individual systems can be made in a variety of ways, depending upon the choice of parameters of 8 interest. Unlike the LPSP [2] and graphical construction methods the algorithm developed in the present work, employs an iterative technique to determine the optimum size of solar panels, wind machines and capacity of batteries of a hybrid system based on Levelised Energy Cost (LEC), Life Cycle Unit Cost (LUC), Life Cycle Cost (LCC), Deficiency of Power Supply Probability (DPSP) and Relative Excess Power Generation (REPG). The structure of the model developed consists of a database that serves as a backhand tool during the computation and in the front end, calculations on size of the wind, solar and battery systems are carried out following an iterative scheme based on the respective average daily data on energy generated. Initially, the size of wind machines required to meet the average daily demand is calculated on a daily basis throughout a year from which the maximum and minimum size of the wind machines required is determined. Then, a loop is operated between the maximum size of the wind machine type chosen and the calculated minimum size of the wind machine. For each size of the wind machine, the size of solar panel is determined for the difference in load (EL-Ew) on a daily average basis, from which the maximum and minimum size of the PV panel required are found. Then an inner loop for each size of the wind machine is operated between the minimum and maximum size of the chosen solar type. Next, the size of the battery system is calculated for the deficit in energy generated by both the wind and PV system on a daily basis throughout the year. Thus for each size of the wind and solar PV system combination, the maximum and minimum size of the battery are calculated. Innermost loop for every assigned size of the wind and PV system is then operated between the minimum and maximum size of the chosen battery model. The inner most loop is executed completely first, the second loop next and finally the outer loop. The quantities of interest are then evaluated from the results obtained for the set of combinations of wind/PV/battery system. The optimal size of wind/PV/battery system of a specific type can then be obtained from the final output with respect to DPSP, based on LCC or LUC or LEC and REPG.
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It can be understood that the optimization of hybrid systems are carried out in order to minimize the deficiency as well as the excess power generated thereby reducing the cost of the system. However matching the load requirements for a most probable period throughout the year is difficult in most of the cases. Therefore in the present analysis, battery banks are designed/optimized taking into account the deficiency in power generated throughout the year, during the combined operation of wind and PV system. 5.0 ECONOMIC ANALYSIS It is pertinent that economic justification should be made while attempting to optimize the size of integrated power generation systems favoring an affordable unit price of power 7 produced. The economic analysis of the hybrid system has been made and the cost aspects have also been taken into account for optimization of the size of the systems. Using the model developed various costs namely, LEC, LUC and LCC have been computed considering the life period and replacement costs of the individual systems. Life cycle cost analysis is a tool used to compare the ultimate delivered cost of technologies with different cost structures the pay back analysis method for PV wind hybrid system depends on the various parameters such as investment, replacement cost, annual operation and maintenance cost, income etc. Table-1 shows the cost values of the economic parameters and components for the base case. 5. 1 Comparison of model The model output data is compared with the real time output data, which is obtained for a hybrid plant installed at Chunnambar, Pondicherry. Chunnambar Island is located about 3km o
from the nearest motorable road (Pondicherry-Cuddalore road). The latitude is 11.46 N and o
longitude 70.46 E. The location is on the beach and receives good sunshine that is complemented by local wind. Mean annual wind speeds are relatively low in Chunnambar Island and the annual average wind speed is about 4.55 m/s at 25m height. Solar radiant flux is 2
abundant at the location. The mean daily insolation is in the range of 4.8-6.9 kWh/m . The daily energy requirement at the site is 12.11 kWh/day and the annual energy consumption is 4320 kWh. The plant is installed with wind machine 3.3 kW and capacity of solar panel 1.8 kWp. From Table-2 it is observed that the output from the model for a 3.3 kW wind energy system is 3569 kWh whereas the real output from the site was only 3347 kWh per year. The variation is estimated to be 6.22%. Similarly for a 1.8 kWp solar photovoltaic generation system, the predicted power generation was found to be 3094 kWh against the real value, 2872 kWh. The estimated variation is 7.18%. The percentage variation of total energy generation between the model output and the real value is found to be 6.66%. 5.2. Case study For a given location, the choice of various combinations of the sizes of wind machines, solar PV array and battery is made from the results obtained from the computations. The optimal selection of a suitable combination of solar, wind and battery capacities for a specific type can be made based on the calculated values of the quantities such as DPSP, REPG, LCC, LEC and LUC. For a given DPSP, an optimal combination of the system is obtained based on the minimum LCC or LEC or minimum REPG.
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o
o
A case study is attempted at a place called Poompuhar (11 8’N, 79 51’E), located in Tamil Nadu, India. The choice of the site has been made based on the fact that the wind and solar power throughout the year is adequate for setting up a hybrid power generation. The mean daily 2 insolation was found to be 5.63 kWh/m and the annual average wind speed was about 4.8m/sec at 25 m height. The daily energy requirement at the site is 450 kWh/day. The model developed is used for design, analysis and optimizing a hybrid system for this location considering various parameters of the location. In the developed model of PV-wind hybrid system the specific data related to the location o o Poompuhar (11 8’N, 79 51’E) are given as inputs by considering the parameter DPSP of 0.20, 2 the wind velocity 4.8m/sec at 25m height, solar insolation 5.63 kWh/m , environment temperature of 32°C for a load of 450 kWh/day. Wind system parameters like cut-in-speed of 3m/sec, cut-off-speed of 25m/sec, rated speed of 12m/s, rotor diameter of 25m, hub height of 40m, PV parameters like peak module power of 52 Wp. It computes the output parameters like PV capacity, array configuration, number of modules, tilt angle, battery capacity, wind machine capacity, Life cycle cost and pay back period. The computed output parameters are PV capacity of 57 kWp and 110 modules; 3 days of autonomy tubular stationary batteries, tilt angle 15° and 50 kW wind system. This generates an annual output of 1189159kWh from solar PV system and 43998kWh from wind system with a life cycle cost of Rs.445 lakhs with a pay back period of 11.8 years. The variation of deficiency of power supply probability with respect to solar PV system capacity is shown in Figure-1. It is seen that 50 kW wind machine with 18 kWp solar PV capacity has 0.5 DPSP. By increasing the solar PV system capacity to 78 kWp the DPSP is reduced to 0.01 and hence the reliability is increased to 99%. Similarly, a two 50 kW wind machine with 18 kWp solar PV system capacity has 0.35 DPSP whereas two 50 kW wind system with 60 kWp PV system capacity has 0.01 DPSP. From the Figure-1, it was found that 50 kW wind system with 78 kWp PV system capacity may satisfy the load requirement for most of the time during the year. Increasing the solar PV system capacity of above 82 kWp with 50 kW wind system does not improve the reliability of the system. Figure-2 indicates the variation of levelised energy cost with respect to solar PV system capacity for variable wind system capacity. It is observed from the Figure-2 that for a 50 kW wind machine with 3 days of battery autonomy that the levelised energy cost decreases with increase in solar PV capacity. For the system with a 50 kW wind machine and 43 kWp PV module, the levelised energy cost is as high as Rs.80.00 per kWh whereas by installing two 50 kW wind machines with 43 kWp PV system capacity, the levelised energy cost is Rs.72.00 per kWh. Increasing the capacity of wind machine can decrease the levelised energy cost. It is also examined from the above Figure 2 that at larger solar PV capacity, the variation of levelised energy cost is small. At lower capacity of solar PV the levelised energy cost is high. Figure-3 shows the variation of DPSP with respect to life cycle cost for standalone photovoltaic, wind and hybrid system. The life cycle cost decreases with increase in DPSP for standalone and hybrid systems. For a considered DPSP of 0.2, the life cycle cost of hybrid system is Rs.550 lakhs and for a solar system it is Rs.675 lakhs whereas for wind system it is Rs.750 lakhs. For the same system life cycle cost, the hybrid system ensures the lowest DPSP values and proves most optimal in terms of performance cost relationship. It is also observed from the Figure 3 that
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achieving a further small decrease in DPSP in the lower levels there is a sharp increase in the life cycle cost for the hybrid and standalone photovoltaic systems. Figure-4 shows the variation of system capacity with respect to energy to load ratio of solar or wind for a given DPSP of 0.1 at Poompuhar. The energy to load ratio of solar PV increases from 0 to 1 indicated left to right in the Figure-4, whereas for wind it decreases from 1 to 0 indicated from right to left in the Figure-4. For example, 0.46 solar or wind refers to 46% solar PV and 54% wind energy generated with respect to load. It is seen from the Figure-4 that the energy to load ratio of solar PV or wind increases with increase in capacity of solar PV system or decrease in wind system capacity. The capacity of the wind and solar system required can be found from the Figure-4 for a given energy to load ratio. This combination obtained may or may not result in the optimum hybrid system. It is observed from the Figure-4 that when the energy to load ratio of solar PV or wind is at 0.72, the system capacity of solar PV and wind system is 50 kW each. It was concluded from the Figure-4 for a given annual average daily load demand for 450 kWh for the location under consideration the optimum combination of solar PV wind hybrid system can be obtained at solar energy to load ratio of 0.72 at 0.1 DPSP. This is a unique value for this selected location. The life cycle cost of the hybrid system with respect to energy to load ratio of solar or wind for a given DPSP is shown in Figure-5. It implies that the life cycle cost of the hybrid system depends largely on the energy to load ratio. The LCC decreases gradually with increase in energy to load ratio of solar or wind upto a certain value and then it increases sharply. This is mainly due to the large storage capacity of battery required when the hybrid system has major contribution from the solar system. It is noted from the Figure-5 that a minimum cost of energy to load ratio of solar occurs at a value of 0.72 for 450 kWh/day. The Figure-5 also represents the minimum cost of each combination of the considered solar PV wind hybrid system and indicates a minimum life cycle cost of Rs.688 lakhs at 0.72 of energy to load ratio. The comparative cost of grid line extension energy source with PV wind hybrid system is a vital parameter to decide the viability of installing a PV wind hybrid system. The break-even point for a grid extension varies with the load demand. Figure-6 indicates the variation of life cycle cost of PV wind hybrid system and grid extension systems with respect to energy demand for variable PV life cycle cost. It is evident from the study that, to meet out the daily energy demand of 75 kWh a fixed life cycle cost of Rs.150 lakhs is required for a grid line extension of 50 km for 11 kV line.This LCC does not vary even when the load demand is less than 75 kWh/day for the same grid line extension. But in the autonomous PV-wind hybrid system LCC is Rs.150 lakhs for a daily energy demand of 75 kWh, and for a load less than 75 kWh the LCC proportionately reduces. Similarly, a fixed LCC of Rs.250 lakhs is required to meet out the load demand of 150 kWh per day or less than that for a grid line extension of 100 km. As in the earlier case here again for PVwind hybrid system life cycle cost required for a load demand of 150 kWh per day is Rs.250 lakhs and for load less than 150 kWh, the LCC proportionately reduces. The drop in the slope refers to the reduction of cost from Rs.160.00 to Rs.100.00 of PV module per peak watt as indicated in the Figure-6. The amount of drop in the slope meets out an additional energy demand, which makes the PV wind system economically viable. It is obvious from the Figure-6 that when the cost of PV module decreases then the viability range of load demand for PV wind hybrid system increases from 75 kWh to 125 kWh per day for grid extension distance of 50km. In comparison with the grid extension, it is concluded that the
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PV wind hybrid has more economical viability when the grid extension distance is longer than 50 km and load demand is lower than 75 kWh/day. 6. RESULTS Fig. 12 shows the prototype of the whole wind–PV hybrid generation system. In this system, the dc motor is fed by a four-quadrant programmable power supply, which can realtime control the rotor speed and torque in accordance with realistic wind profile characteristics. Meanwhile, a group of tungsten halogen lamps are controlled by a programmable light dimmer to emulate various sunlight irradiances. First, the performances of the wind power generation branch are assessed. Fig. 13 shows the rectifier output power characteristics under different speeds. It verifies that the characteristics of the output power versus the output voltage have an obvious maximum power point under each speed. Also, these maximum power points can be achieved by simply regulating the dc field current. Moreover, the characteristics of the maximum output power and the combined generator–rectifier efficiency versus the speed are shown in Fig. 14. It can be observed that both the maximum power point and efficiency increase with the speed. The maximum power point increment is simply due to the increase of input wind power. The efficiency increment is due to the fact that the rated speed of the proposed generator is designed at 600 r/min (corresponding to the wind speed of 15 m/s). In general, the combined generator–rectifier efficiency of the conventional wind power generation system is in the range of 50%–75% under the wind speed of 4–12 m/s. For the proposed wind power generation system, it can be seen that its efficiency is already over 70% when the rotor speed is 300 r/min (corresponding to the wind speed of 9 m/s). Hence, the proposed wind power generation branch can efficiently convert wind energy to electrical energy over the major speed range. In order to evaluate the validity of MPPT as compared with the case that adopts a fixed dc field current, the middle value (2 A) of the whole field current range (0–4 A) is selected. The use of dc field current that is equal to 2 A almost corresponds to the maximum power point at 100 r/min. Fig. 15 shows Fig. 15. Wind generator characteristics of maximum output power and power improvement versus speed with MPPT. Fig. 16. PV panel output power characteristics versus duty cycle under different irradiances. the characteristics of the maximum output power and power improvement as compared with the case under a fixed dc field current of 2 A versus the speed under MPPT. It can be seen that the power improvement is significant, which is about 25% at the rotor speed of 600 r/min. Second, the PV power generation branch characteristics are analyzed. Fig. 16 shows the characteristics of the PV output power versus the duty cycle under different irradiances. It verifies that the PV power generation branch can readily perform the MPPT and achieve the maximum output power at a given irradiance. as compared with the case under the fixed dc field current of 2 A and the fixed duty cycle of 50%. The corresponding power improvement is from 3% to 25.1%. Hence, it verifies that the proposed system with MPPT can efficiently extract energy from the wind and PV sources. It is worthy to note that the prototype is mainly used for experimental verification. Thus, it is designed at low power levels that adversely affect the efficiency. Since some major losses such as the core loss and the windage and friction losses of the generator are independent of the power level, it is expected that the efficiency will be much better when the power level is elevated to the order of kilowatts. In order to evaluate the validity of MPPT as compared with the case that adopts a fixed duty cycle, the middle value (50%) of the whole duty cycle range (0%–100%) is selected. The
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use of duty cycle that is equal to 50% almost corresponds to the maximum power point at 100 W/m2. The characteristics of the maximum output power and power improvement versus the irradiance are shown in Fig. 17. It can be found that the maximum output power increases with the irradiance, which well agrees with the principle of the PV panels. Also, the power improvement under MPPT as compared with the case under the fixed duty cycle of 50% is significant, which is about 30% at the irradiance of 600 W/m2. Such an improvement agrees with the expectation since the converter operating at a fixed duty cycle cannot perform effective power transfer. Third, the wind–PV hybrid generation characteristics are evaluated. Fig. 18 shows the total output power under MPPT Finally, Fig. 19(a) shows typical daily profiles of wind speed and solar irradiance in October in Hong Kong. Fig. 19(b) shows the corresponding output powers. It can be seen that the wind is weak at most daytime and power and PV power are complementary to some extent. becomes strong at nighttime (particularly at midnight), while sunshine occurs at daytime and reaches the peak at noon. Hence, it confirms that the wind
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7.0 CONCLUSIONS In the present scenario standalone solar photovoltaic and wind systems have been promoted around the globe on a comparatively larger scale. These independent systems cannot provide continuous source of energy, as they are seasonal. The solar and wind energies are complement in nature. By integrating and optimizing the solar photovoltaic and wind systems, the reliability of the systems can be improved and the unit cost of power can be minimized. In this paper, a new wind–PV hybrid generation system has been proposed and implemented. This stand-alone hybrid generation system can fully utilize the characteristics of the proposed wind generator and the PV panels to extract the maximum power from the wind and solar energy sources. Namely, the MPPT of the doubly excited PM brushless generator is achieved by online tuning its dc field current, while the MPPT Fig. 19. Complementary wind–PV hybrid generation. (a) Daily profiles of wind speed and irradiance. (b) Daily profiles of wind power and PV power. of the PV panels is attained by online tuning the duty cycle of the SEPIC. Also, this hybrid generation system takes a distinct merit that the wind power and PV power inherently complement one another to certain extent, hence facilitating continuous output power from day to night. A PV wind hybrid systems is designed for rural electrification for the required load at specified Deficiency of Power Supply Probability (DPSP). A new methodology has been developed to determine the size of the PV wind hybrid system using site parameters, types of wind systems, types of solar photovoltaic system, number of days of autonomy of battery and life period of the system. A primary model was developed to optimize PV-wind hybrid system for any specific location, by considering the parameters DPSP and REPG. The developed model processes the input parameters pertaining to the wind velocity, solar insolation, environment temperature, load distribution, wind and PV system parameters like cut-in-speed, cut-off-speed, rated speed, rotor diameter, hub height, peak module power, capacity of the PV panel and wind systems. It computes the output parameters like PV capacity, array configuration, number of modules, tilt angle, inverter capacity, battery capacity, charge controller capacity and wind machine capacity. The optimal size of the hybrid system is determined based on the calculated values of REPG for a specified DPSP. Thus the model suggests the optimum combination of the capacity of wind, PV and battery units of a chosen type that can generate power with a minimum REPG by implementation of iterative technique. A secondary model developed for optimizing techno economic aspects like LCC, LEC or LUC considering the parameters like life period of solar system, wind system, battery discount rate, escalation rate, cost of the module, wind machine, battery, inverter BOS components and CO2 mitigation cost for solar photovoltaic wind hybrid system.
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8 APPENDIX A
Fig Flowchart for optimum utilization of PV-Wind Hybrid system
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APPENDIX B Table-1. Cost values of the economic parameters and components for the base case
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APPENDIX C
Table-2.Comparison of model and real time energy outputs for site Chunnambar, Pondicherry.
Figure-2. Variation of deficiency of power supply probability with respect to solar PV system capacity at Poompuhar.
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Figure-3. Variation of levelised energy cost with respect to solar PV system capacity with variable wind system capacity for 3 days of battery autonomy at Poompuhar.
Figure-4. Variation of deficiency of power supply probability with respect to life cycle cost for Standalone photovoltaic, wind and hybrid systems at Poompuhar.
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APPENDIX D
Working Procedure: During day time, DC Power generated by the Solar PV array is stored in the Battery Bank through a Hybrid Controller, which maximizes charging current and prevents excessive discharge/overcharge. Wind turbine generator starts generating power when wind speed exceeds cut-in speed of the Mini Wind Turbine (above 2.7 m/s). Output from the Wind Battery Charger is also stored in the Battery Bank through Hybrid Controller. During windy periods excess energy generated by the Wind Battery Charger is dissipated through a progressive heater (Dump Load). The wind turbine is self-regulated type with protection for Overspeed. Energy stored in the battery is drawn by electricals loads through the inverter, which converts PC power into AC power. The inverter has in-built protection for Short-Circuit, Reverse Polarity, Low Battery Voltage and Over Load. The Batter Bank is designed to feed the loads up to two days, during Non-Sun/Wind days.
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SOLAR PV - WIND HYBRID POWER SPECIFICATIONS of 5 –10 kW 1) PV Array Power = 2100 to 3600 watts 2) Micro Wind turbine/generator = 3.5 to 6.5 kW 3) System Voltage = 48 4) Battery Bank Capacity, Ah(@C10) Industry Standard 5) Solar PV Module, Model – Industry standard 6) No.of Solar PV Modules Industry standard 7) Inverter Rating (VA) 5000 8) Output AC Wave form Sine-wave 9) Output AC Voltage (Vnom), +/-10% = 230 V/AC 10) Output Ac Frequency, Hertz, +/-0.5 % = 50 Hz. Additional Specs For Lamination And Mounting Of Solar Panels. Single crystalline solar cells, which is the industry standard. Solar cells to be laminated between high transmitivity, impact-resistant glass using ultra violet resistant polymer to provide environmental protection, reliability and ruggedness. Anodized aluminium frame to facilitate mounting and installation.
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