Your essay on renewable energy can be not only interesting, but also easy to do if you use such topics. A well-chosen topic is your key to success and an opportunity to express your ideas. Students will be able to write excellent academic papers about alternative energy if they understand the meaning and importance of biomass, wind power, hydroelectric power, and solar power. It is possible to write good alternative energy essay, if you take into consideration the following options and topics:.
Students, having an assignment to write a renewable energy essay, should be aware of some basic tips of writing academic papers:. The world ecological condition is a phenomenon that worries many people around the globe. One of the most important issue in the context of an ecological state of the planet is energy sources.
There are two main problems related to them. The first problem is pollution caused by the extraction and using some of the energy sources. The next problem is that extraction of some sources has increased dramatically in recent years, which leads to their depletion. In this way, there appeared necessity to find ecological and renewable energy sources.
It must be noticed that in Massachusetts are used different sources of renewable energy, their usage by the government and it is even discussing and planning to completely switch Massachusetts on usage sources of renewable energy.
Considering renewable energy sources one can notice that both, solar and wind energy are used in Massachusetts. Clean energy has become an economic driver in Massachusetts, with more than ten thousand clean-energy jobs created Calter, Thomas J. There was onshore commercial wind development along the coast in Massachusetts. Ridge crests in the mountains in the west of the state have good wind potential. Offshore wind is roughly 16 cents per kilowatt hour, according to an industry report, and the cost for onshore wind is even lower Calter, Thomas J.
It can be considered as positive for ecology that government of Massachusetts understood all its potential and economical benefits of clean energy. Such state of affairs is related to three points. In this way, the advantage of solar energy is in the fact that it can be used in all the state without differences of the geographical and other specificities of the area. The next important point is in the constancy of generated energy.
The wind is more erratic than solar panels which generate a certain amount of electricity even on cloudy days Kramer. The last point is that solar panels can produce more energy that the wind turbines.
Thus, solar energy is more relevant to use in Massachusetts. The facts shown above allowed one to make a conclusion that Massachusetts has an effective environmental policy, including the use of renewable energy sources. However, because of the list of evidence, such as independence from area for using, the constancy of generated energy, and profitability, solar energy is more relevant to use in Massachusetts.
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HOMER performs the analyses to explore a wide range of design questions that are below:. Conceptual relationship between simulation, optimization and sensitivity analysis. The above figure 4. The optimization oval encloses the simulation oval to represent the fact that a single optimization consists of multiple simulations. Similarly, the sensitivity analysis oval encompasses the optimization oval because a single sensitivity analysis consists of multiple optimizations.
HOMER simulates the operation of a system by making energy balance calculations for each of the 8, hours in a year. For each hour, HOMER compares the electric and thermal load in the hour to the energy that the system can supply in that hour. For systems that include batteries or fuel-powered generators, HOMER also decides for each hour how to operate the generators and whether to charge or discharge the batteries. HOMER performs energy balance calculations for each system configuration that we want to consider.
It then determines whether a configuration is feasible i. A user can then view hourly energy flows for each component as well as annual cost and performance summaries. After simulating all of the possible system configurations, HOMER displays a list of feasible systems, sorted by lifecycle cost. We can easily find the least cost system at the top of the list or we can scan the list for other feasible systems.
Sometimes we may find it useful to see how the results vary with changes in inputs, either because they are uncertain or because they represent a range of applications. We can perform a sensitivity analysis on almost any input by assigning more than one value to each input of interest. HOMER repeats the optimization process for each value of the input so that the user can examine the effect of changes in the value on the results.
We can specify as many sensitivity variables as we want and analyze the results -. In a microgrid power system, a component is any part of a whole power system that generates, delivers, converts or stores energy. The microgrid comprises in four major components that are wind turbine or solar photovoltaics, generator, converter and storage batteries.
There are two intermittent renewable sources for electricity generation that are wind turbines and solar photovoltaics. Wind turbines convert wind energy into ac or dc electricity and PV modules convert solar radiation into dc electricity.
Generator is a dispatch-able energy source, meaning that the system can control it as needed and it consumes fuel to produce AC or DC electricity. Converter is used to convert electrical energy into another form and it converts electricity from ac alternating current to dc direct current or from dc to ac.
Finally, storage batteries are used for storing the DC electricity. This is the minimum wind speed needed to start the wind turbine which depends on turbine design and to generate output power. The cut-out wind speed represents the speed point where the turbine should stop rotating due to the potential damage that can be done if the wind speed increases more than that .
This is the wind speed at which the wind generator reaches its rated output. Note that not all wind generators are created equal even if they have comparable rated outputs.
This measurement is taken at an uninformed wind speed that the manufacturer designs for. It tends to be at or just below the governing wind speed of the wind generator.
Any wind generator may peak at a higher output than the rated output. The faster you spin a wind generator the more it will produce until it overproduces to the point that it burns out.
Manufacturers rate their generators at a safe level well below the point of self-destruction. This figure may be the same as rated output, or it may be higher.
Wind generators reach their peak output while governing, which occurs over a range of wind speeds above their rated wind speed . The mean wind speed for a usual day of a month can be calculated by averaging all the recorded wind speeds for the month.
The mean wind speeds are then upgraded to the hub height. Wind speeds increase with height . The calculated mean wind speeds are speeds recorded near the ground surface. Since the hubs of wind turbine are usually more than ten meters high, the mean wind speeds at a particular height will be greater than V i.
Therefore, to obtain mean wind speeds, V i has to be projected to the hub height. The projected V i is calculated using the power-law equation shown -. The power-law exponent, x depends upon the roughness of the surface.
A random variable v can be expressed with a Weibull distribution by utilizing the probability density function pdf as given by Stevens and Smulders  and shown below:. Where c is a scale parameter with the same units as the random variable and k is a shape parameter.
The electric power output of a wind turbine is primarily a function of wind speed  and as shown below:. The average wind power output from a wind turbine is the power produced at each wind speed multiplied by the fraction of the time that wind speed is experienced and integrated over all possible wind speeds.
The average power output of a turbine is a very important parameter for any wind power system since it determines the total energy production and hence the total income. It is a much better indicator of economics than the rated power, which can easily be chosen at too large a value. The formula of average wind power output can be obtained by substituting 3 and 4 into 5 , which gives equation 6 below :. The software HOMER models a wind turbine as a device that converts the kinetic energy of the wind into AC or DC electricity according to a particular power curve, which is a graph of power output versus wind speed at hub height.
An example of power curve is shown in figure 4. HOMER assumes that the power curve applies at a standard air density of 1. First, it determines the average wind speed for the hour at the anemometer height by referring to the wind resource data. Fourth, it multiplies that power output value by the air density ratio, which is the ratio of the actual air density to the standard air density.
Standard Atmosphere  and assumes that the air density ratio is constant throughout the year. The engineering software package HOMER is used for modelling the hybrid power system, in the software the size of PV array is always specified in terms of rated capacity.
The rated capacity accounts for both the area and the efficiency of PV module, so neither of those parameters appears clearly in the software. The derating factor is a scaling factor meant to account for effects of dust on the panel, wire losses, elevated temperature or anything else that would cause the output of the PV array to deviate from that expected under ideal conditions.
The HOMER software does not account for the fact that the power output of a PV array decreases with increasing panel temperature but we can reduce the derating factor to crudely correct for this effect when modelling systems for hot climates.
In reality the output of a PV array does depend strongly and nonlinearly on the voltage to which it is exposed. The maximum power point the voltage at which the power output is maximized depends on the solar radiation and the temperature.
If the PV array is connected directly to a dc load or a battery bank then it will often be exposed to a voltage different from the maximum power point and performance will suffer. A maximum power point tracker MPPT is a solid state device placed between the PV array and the rest of the dc components of the system that decouples the array voltage from that of the rest of the system and ensures that the array voltage is always equal to the maximum power point.
By ignoring the effect of voltage to which the PV array is exposed, HOMER effectively assumes that a maximum power point tracker is present in the system.
To explain the cost of PV array the user specifies its initial capital cost in U. The replacement cost is the cost of replacing the PV array at the end of its useful lifetime which the user specifies in years. By default the replacement cost is equal to the capital cost but the two can differ for several reasons --.
A generator consumes fuel to produce AC or DC electricity. The generator can be AC or DC and can consume a different fuel. The principal physical properties of the generator are its maximum and minimum electrical power output, its expected lifetime in operating hours, the type of fuel it consumes and its fuel curve which relates the quantity of fuel consumed to the electrical power produced. A diesel generator is used for the microgrid system. Where F 0 is the fuel curve intercept coefficient, F 1 is the fuel curve slope, Y gen the rated capacity of the generator kW and P gen the electrical output of the generator kW.
The units of F depend on the measurement units of the fuel. In the same way the units of F 0 and F 1 depend on the measurement units of the fuel. For a generator that provides heat as well as electricity, the design engineer also specifies the heat recovery ratio. HOMER assumes that the generator converts all the fuel energy into either electricity or waste heat. The heat recovery ratio is the fraction of that waste heat that can be captured to serve the thermal load.
The design engineer can schedule the operation of the generator to force it ON or OFF at certain times. During times that the generator is forced ON, HOMER decides at what power output level it operates which may be anywhere between its minimum and maximum power output. The fixed cost of energy is the cost per hour of simply running the generator without producing any electricity. The marginal cost of energy is the additional cost per kilowatt-hour of producing electricity from that generator.
The effective price of fuel includes the cost penalties if any associated with the emissions of pollutants from the generator. HOMER calculates the marginal cost of energy of the generator using the following equation: Where F 1 is the fuel curve slope in quantity of fuel per hour per kilowatt-hour and C fuel,eff is the effective price of fuel including the cost of any penalties on emissions in dollars per quantity of fuel .
Although renewable resources are attractive, they are not always dependable in the absence of energy storage devices. As a result, renewable resources are often used together with energy storage devices. However, in many cases, such systems are the least understood and the most vulnerable component of the system . Among different types of energy storage devices, lead-acid batteries are still the most commonly used devices to store and deliver electricity in the range from 5V to 24V DC -.
The battery bank is a collection of one or more individual batteries. The software package HOMER models a single battery as a device capable of storing a certain amount of dc electricity at a fixed round-trip energy efficiency with limits as; how quickly it can be charged or discharged, how deeply it can be discharged without causing damage and how much energy can cycle through it before it needs replacement.
HOMER assumes that the properties of the batteries remain constant throughout its lifetime and are not affected by external factors such as temperature. In HOMER, the key physical properties of the battery are its nominal voltage, capacity curve, lifetime curve, minimum state of charge and round-trip efficiency.
The capacity curve shows the discharge capacity of the battery in ampere-hours versus the discharge current in amperes. Manufacturers determine each point on this curve by measuring the ampere-hours that can be discharged at a constant current out of a fully charged battery. Capacity typically decreases with increasing discharge current. The lifetime curve shows the number of discharge-charge cycles the battery can withstand versus the cycle depth.
The number of cycles to failure typically decreases with increasing cycle depth. The minimum state of charge is the state of charge below which the battery must not be discharged to avoid permanent damage. In the system simulation, HOMER does not allow the battery to be discharged any deeper than this limit. The round-trip efficiency indicates the percentage of the energy going into the battery that can be drawn back out.
Three parameters describe the battery. The maximum capacity of the battery is the combined size of the available and bound tanks. The capacity ratio is the ratio of the size of the available tank to the combined size of the two tanks. The rate constant is analogous to the size of the pipe between the tanks. The kinetic battery model explains the shape of the typical battery capacity curve as shown in figure 4.
Modelling the battery as a two-tank system rather than a single-tank system has two effects. First, it means the battery cannot be fully charged or discharged all at once, a complete charge requires an infinite amount of time at a charge current that asymptotically approaches zero.
HOMER tracks the levels in the two tanks each hour and models both these effects. The above figure shows a lifetime curve of a deep-cycle lead-acid battery. The number of cycles to failure shown in the graph as the lighter-coloured points drops sharply with increasing depth of discharge.
For each point on this curve, one can calculate the lifetime throughput the amount of energy that cycled through the battery before failure by finding the product of the number of cycles, the depth of discharge, the nominal voltage of the battery and the aforementioned maximum capacity of the battery.
The lifetime throughput curve as shown in the above figure as black dots typically shows a much weaker dependence on the cycle depth. HOMER makes the simplifying assumption that the lifetime throughput is independent of the depth of discharge. The value that HOMER suggests for this lifetime throughput is the average of the points from the lifetime curve above the minimum state of charge but the user can modify this value to be more or less conservative.
The assumption that lifetime throughput is independent of cycle depth means that HOMER can estimate the life of the battery bank simply by monitoring the amount of energy cycling through it, without having to consider the depth of the various charge-discharge cycles.
HOMER calculates the life of the battery bank in years as:. Since the battery bank is a dispatch-able power source, HOMER calculates its fixed and marginal cost of energy for comparison with other dispatch-able sources.
Unlike the generator, there is no cost associated with operating the battery bank so that it is ready to produce energy; hence its fixed cost of energy is zero.
For its marginal cost of energy, HOMER uses the sum of the battery wear cost the cost per kilowatt-hour of cycling energy through the battery bank and the battery energy cost the average cost of the energy stored in the battery bank.
HOMER calculates the battery wear cost as below:. HOMER calculates the battery energy cost each hour of the simulation by dividing the total year-to-date cost of charging the battery bank by the total year-to-date amount of energy put into the battery bank.
Under the load-following dispatch strategy, the battery bank is only ever charged by surplus electricity, so the cost associated with charging the battery bank is always zero. Under the cycle-charging strategy however, a generator will produce extra electricity and hence consume additional fuel for the express purpose of charging the battery bank, so the cost associated with charging the battery bank is not zero .
The converter size which is a decision variable refers to the inverter capacity, meaning the maximum amount of AC power that the device can produce by inverting DC power.
The model design engineer specifies the rectifier capacity which is the maximum amount of DC power that the device can produce by rectifying AC power as a percentage of the inverter capacity. The rectifier capacity is therefore not a separate decision variable.
HOMER assumes that the inverter and rectifier capacities are not surge capacities that the device can withstand for only short periods of time but rather continuous capacities that the device can withstand for as long as necessary. Doing so requires the inverter to synchronize to the AC frequency, an ability that some inverters do not have. The final physical properties of the converter are its inversion and rectification efficiencies which HOMER assumes to be constant. The economic properties of the converter are its capital and replacement cost in U.
A load profile will vary according to customer type typical examples include residential, commercial and industrial , temperature and holiday seasons. Generation companies use this information to plan how much power they will need to generate at any given time . Load Profile is a broad term that can refer to a number of different forms of data.
It can refer to demand and consumption data or it can be a reference to derived data types, such as Regression and Profile Coefficients. However, all these data types have one thing in common that they represent the pattern of electricity usage of a segment of supply market customers . The peak may be a theoretical maximum, rather than a measured maximum -.
The ratio expressed as a percentage of the number of kWh supplied during a given period to the number of kWh that would have been supplied had the maximum demand been maintained throughout that period . There are two different types of domestic load profiles case studies scenarios for the simulations of microgrid system, which are as follows:.
The load profile mostly depends on occupancy pattern so analyzing the load profile, it is necessary to identify the cluster of household. I worked on five most common cases or scenarios of UK domestic occupancy pattern due to having less information regarding household occupancy pattern, which are under below:.
In this case unoccupied period is from One of the occupants may have part time job in the morning in this type of household occupancy pattern. Here unoccupied period is from This type of household occupants may have a child to look after when school closed.
In this case the house is occupied all the time because this type of household occupants may have retired couples, children to look after and single. Unoccupied period is from One of the occupants in this type of household may have a part time job in the afternoon session . This is the average of above all five different scenarios of domestic load profile pattern in the UK at the present.
In Pakistan, the load profile depends on user electricity consumption and occupancy; so analyzing the load profile, it is necessary to identify the group of household. I worked on three most common scenarios of Pakistan household occupancy pattern depending on low consumption, medium consumption and high consumption electricity users.
All three types of scenarios are calculated on assumption based with the average of all four seasons spring, summer, autumn and winter , that are below:. There are two people living in one bed room house in this type of occupancy and are low electricity consumption users. This type of occupancy is under four persons living in three bed room house and they are medium electricity users.
In this scenario, there are five persons living in five bed room house. One of the occupants may have full time job, one school child and they are high electricity users. This is the typical load profile which is the average of above three different scenarios of domestic load profile in the Pakistan.
There are two different case studies carried out in the two different places for the design of microgrid power system. The both case studies are specified below:. The first case study for designing the microgrid system is carried out in the Isle of Arran, Scotland, UK. Arran is the seventh largest island in the Scotland and it is in the North Ayrshire unitary council area. It has an area of square miles square kilometres , meters height and 50 miles from Glasgow City.
The southern half of the island, being less mountainous has a more favourable climate than the northern half and the east coast is more sheltered from the prevailing winds than the west and south. Wind energy is one the best renewable energy resource RES in Scotland and Isle of Arran is the best location due to fast winds blowing. It was decided to use available renewable energy sources based on hourly or daily energy consumption by implementing a small scale microgrid power system. To verify the reduction in carbon emissions or green house gases GHG and economic viability, a microgrid hybrid power system is proposed to feed a typical house located in remote area of the Isle of Arran, Scotland.
Monthly average wind resources data and average domestic loads are used as input parameters. The schematic diagram of the microgrid power system is modeled in the HOMER, which is shown in figure 5. The average load profile of the UK domestic household or remote household is below in figure 5.
This wind turbine is intended for a range of conditions especially rural locations. In the generator, diesel is used as a fuel and its annual average price 0. It shows the contributions of wind turbine generation and generation by diesel generator for the microgrid system. So, as a result the total cost of the microgrid system will reduce.
So, new total cost of the system would be:. The second case study for microgrid system design is carried out in the Multan, Punjab, Pakistan. The closest major city is Sahiwal. You can choose all of the features, any combination of the features, or choose your own features—it is completely up to YOU. The price per page does NOT increase, no matter how many features you choose.
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Renewable Energy Introduction. Renewable energy is the term used to describe energy that occur naturally and repeatedly in the environment and can be harnessed for human benefit. This includes energy from the sun, wind, biomass, hydro, waves or tides.
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