Homer Report
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Transcript of Homer Report
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1. Introduction:
Nowadays, the mankind is living an energy crisis. The most optimist forecasts reveal the fact
that the main classic energy resources (oil and natural gas) will be exhausted until 2050. Also,
the combustion causes the greenhouse effect which will determine an apocalyptical scenario in
the next (80-100) years. In this scenario, the only solution is finding and using new energy
resources, inexhaustible and clean, which will substitute in the next 50 years the current
resources based on fossil fuels.
The growing share of renewable energy production is predictable but depends both on
reducing the production costs and on finding new electrical energy storage solutions. This will
ensure the injection into the power system of large quantities of renewable energy. Even more,
the legislation regarding environment protection imposes the usage of this kind of energy. In
March 2007, a European agreement was signed, which impose the reduction of CO2emission
with 20% until 2020 and 50% until 2050, but also using the bio-fuels with a share of 10%.
2. Renewable energy used for residential consumers
Wind energy is used by the wind turbines, which nowadays have rated powers up to 3 MW. The
investments in this area are growing day by day, wind energy being used by consumers in rural
and extra-urban areas with important wind potential.
3. Description of HOMER softwarean optimal analysis tool
Homer (Hybrid Optimization Model for Electric Renewals) was developed by NREL (NationalRenewable Energy Laboratory, Colorado USA), as a work platform for optimal selection of
independent, interconnected or distributed power sources for consumers, connected or not
connected to the public grid.
The processed information by HOMER refers to:
power sources: photovoltaic panels, wind turbines, small hydropower plants, diesel
generators, biomass, biogas, fuel cells, public grid;
energy storage: hydrogen, batteries;consumers: daily and annual load curves, water
Pumping, heating, ventilation and air conditioning.
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Using HOMER involves the following steps:
- In the initial phase, all the technical possible combinations for supplying the consumers using
the specified power sources are determined. Next, the energy balance for 8760 h/year and all
the possible alternatives to provide the energy are determined;
- In the second phase, for every alternative a full economical estimation (considering all theexpensed regarding the initial investments, maintenance, repairing, modernization, interests
and benefits) is computed.
- The third phase optimizes economically the proposed solutions and presents them in
ascending order of costs per life cycle;
- In the fourth phase, sensitivity indexes of the results considering the variations of the input
data are computed.
Finally, from the presented results, the user can decide which the best solution to supply the
consumers is.
4. Case study using HOMER
For the case study, a medium size extra-urban residential area in Coimbatore, Peelamedu (11.0183
N, 76.9725 Coimbatore)is considered. Each house accommodates 3-4 persons and has an installed
electrical power of 5 kW. For all the considered area, the primary load is scaled to an annual
average of 1250kWh/d and a peak of 150kW and the deferrable load scaled to an annual
average of 2.83kWh/d and a peak of 100kW.
Load Consumption(kWh/yr) Fraction
AC primary load 450,080 74%
Deferrable load 1,035 0%
Electrolyzer load 159,604 26%
Total 610,719 100%
Fig 1.Load details for a day
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Fig 2.Seasonal profile of the primary
load.
Fig 3.Monthly profile of deferrable load.
5. Resources.
The HOMER software can generate the clearness index from the solar radiation
data according to the latitude of the place has been chosen. If the solar radiation
data is not available, clearness index can also be used to generate the solar
radiation data. Therefore, either the clearness index or the solar radiation data can
be used to represent the solar resource input, as long as the data of latitude is
available to the HOMER software.
Month Daily solar radiation (kWh/m2/day) Wind speed (m/s) at 10m
Jan 5.459 3.650
Feb 6.375 3.190
Mar 6.746 3.290
Apr 6.502 3.230
May 5.720 3.810
Jun 4.673 5.520
Jul 4.503 5.530
Aug 4.592 5.020
Sep 5.123 3.090
Oct 4.809 3.000
Nov 4.811 3.210
Dec 5.054 4.060
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Fig: solar resource of peelamedu.
Fig: wind resource of peelamedu.
6. System Components.
1.Photovoltaic Array In order to optimize the PV array ,PV of sizes
250kW,500kW and 750kW are considered
2.Wind turbines To optimize the wind requirements, NEPC wind turbines (6
numbers)are included in the power system
3.Fuel Cell Fuel cells with 50 kg capacity are considered to meet the
requirements. The fuel input to the system is liquid
hydrogen
4.Battery Batteries with string numbers 10,15,20,25 and each string
having 19 batteries are connected to supply the bus
requirement of 228v
5.Converter Converters with capacity 150 kW are used for dc/ac
conversions
6.Electrolyser The electrolyzer unit of sizes 100 and 150kW are included
to store the fuel and supply when needed
7.Hydrogen Tank A hydrogen tank with 50 kg capacity is used for the supply
needs
The above number of units and the system components are connected and simulated to obtain the best cost analysis
and power analysis.
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NEPC:
Since in India NEPC is one of the commonly used windmill generator we had simulated and modeled our power system
using NEPC. To add the windmill to the HOMER library we had referred the power curve of NEPC 250kW wind generator.
Fig: Power curve of NEPC at 10m.
The lifetime of the same windmill is about 25 years and it includes a capital cost of 20830$.From the power curve
initially we had included 4 quantity of NEPC. But when the HOMER simulated the system it suggested including more
number of Windmills. By this way we had arrived with different architecture each having different configurations.
PHOTOVOLTAIC ARRAY
We all know that a country like India is having enough solar radiation throughout the year. So we had considered
Photovoltaic array of different power capacities. But the cost of these PV array is very high .It poses constrain for us to
have only limited number of PVs.If we look at any system from the simulation results the cost of PV is 50% of the initial
cost if the system includes PV array. The Lifetime of PVs is also 25 years. The De-rating Factor, Slope, Azimuthal angle
differs from place to place and it is given as per the latitude and longitude.
Fig: Cost flow graph for a system with PV.
FUEL CELL:
Being a Hybrid Power System using only renewable resources instead of using fossil fuel generators we had considered
Fuel Cells. The source or the fuel for these Fuel Cells is from Hydrogen Tank which stores the required Hydrogen (fuel).
This Hydrogen is generated from the electrolyzer. So we had to go in for connecting Electrolyzer also as a part of system
component.
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CONVERTERS AND BATERRIES:
As in the system we considered DC components which serve the AC load converters
must also be considered. The value of the required converter and batteries varies
as per the total amount of AC/DC power generated. But those values can be easily
found as every time HOMER simulates it suggests the value of the eachcomponents that makes the system feasible.
ANALYSIS OF RESULTS:
Three power systems configurations using different energy storage technologies,
namely
PV/Wind/Battery system,
PV/Fuel cell/Battery system.
PV/Wind/Fuel cell/Battery system
All the above systems are simulated in HOMER environment for optimal sizing
which minimizes the system cost. The simulation results provide comparison
among these configurations. Simulation studies are classified as: Case A
(PV/Wind/Battery system), Case B (PV/Wind/Fuel cell/Battery system), Case C
(PV/Wind/Fuel cell/Battery system).
Case A (PV/Wind/Battery system)
System Architecture:
PV Array 500 kW
Wind turbine 6 NEPC
Battery 380 Vision 6FM200DInverter 150 kW
Rectifier 150 kW
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Electrical:
Cost summary
Total net present cost $ 2,344,849
Levelized cost of energy $ 0.405/kWh
Operating cost $ 70,003/yr
Case B (PV/Fuel cell/Battery system)
System architecture:
PV Array 750 kW
Fuel Cell 50 kW
Battery 475 Vision 6FM200D
Inverter 150 kWRectifier 150 kW
Electrolyzer 150 kW
Hydrogen Tank 50 kg
Dispatch strategy Cycle Charging
Component Production(kWh/yr) Fraction
PV array 1,268,987 91%
Fuel Cell 130,583 9%
Total 1,399,570 100%
Component Production(kWh/yr) Fraction
PV array 845,992 42%Wind
turbines
1,178,469 58%
Total 2,024,461 100%
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Cost:
Total net present cost $ 3,421,929
Levelized cost of energy $ 0.593/kWh
Operating cost $ 80,138/yr
Case C (PV/Wind/Fuel cell/Battery system).
System architecture
PV Array 250 kW
Wind turbine 6 NEPC
Fuel Cell 50 kW
Battery 285 Vision 6FM200D
Inverter 150 kW
Rectifier 150 kW
Electrolyzer 100 kW
Hydrogen Tank 50 kg
Dispatch strategy Cycle Charging
Cost summary:
The operating cost here is the minimum of all the three configurations. So HOMER
shows this system architecture as the optimal system out of all possible
combinations.
Total net present cost $ 1,969,859
Levelized cost of energy $ 0.342/kWh
Operating cost $ 50,251/yr
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ELECTRICAL:
The total amount of load needed is shared by three sources and also compared to
the previous technologies 70% of load is met by Windmills and thus reducing the
initial capital cost actually incurred.
Component Production(kWh/yr) Fraction
PV array 422,996 25%
Wind turbines 1,178,469 70%
Fuel Cell 81,156 5%
Total 1,682,621 100%
Component Wise Analysis of the Optimal System:
PV:
Quantity Value Units
Rated capacity 250 kW
Mean output 48.3 kWMean output 1,159 kWh/d
Capacity factor 19.3 %
Total production 422,996 kWh/yr
Quantity Value Units
Minimum output 0.00 kW
Maximum output 295 kW
PV penetration 92.7 %
Hours of operation 4,413 hr/yr
Levelized cost 0.105 $/kWh
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AC Wind Turbine: NEPC
Variable Value Units
Total rated capacity 1,500 kW
Mean output 135 kW
Capacity factor 8.97 %
Total production 1,178,469 kWh/yr
Variable Value Units
Minimum output 0.00 kW
Maximum output 1,449 kW
Wind penetration 258 %
Hours of operation 4,530 hr/yr
Levelized cost 0.00881 $/kWh
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Fuel Cell
Quantity Value Units
Hours of operation 2,148 hr/yr
Number of starts 699 starts/yr
Operational life 18.6 Yr
Capacity factor 18.5 %
Fixed generation cost 8.75 $/hr
Marginal generation cost 0.00 $/kWh/yr
Quantity Value Units
Electrical production 81,156 kWh/yr
Mean electrical output 37.8 kW
Min. electrical output 0.00000000000000100 kW
Max. electrical output 50.0 kW
Quantity Value Units
Hydrogen consumption 4,869 kg/yr
Specific fuel consumption 0.060 kg/kWh
Fuel energy input 162,313 kWh/yr
Mean electrical efficiency 50.0 %
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Battery
Quantity Value
String size 19
Strings in parallel 15
Batteries 285
Bus voltage (V) 228
Quantity Value Units
Nominal capacity 684 kWh
Usable nominal capacity 410 kWh
Autonomy 7.86 Hr
Lifetime throughput 261,345 kWh
Battery wear cost 0.610 $/kWh
Average energy cost 0.000 $/kWh
Quantity Value Units
Energy in 52,103 kWh/yr
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Energy out 41,689 kWh/yr
Storage depletion 7.88 kWh/yr
Losses 10,406 kWh/yr
Annual throughput 46,610 kWh/yr
Expected life 5.61 Yr
Converter
Quantity Inverter Rectifier Units
Capacity 150 150 kW
Mean output 24 10 kW
Minimum output 0 0 kW
Maximum output 150 150 kW
Capacity factor 15.9 7.0 %
Quantity Inverter Rectifier Units
Hours of operation 4,788 1,957 hrs/yr
Energy in 232,823 108,129 kWh/yr
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Energy out 209,541 91,910 kWh/yr
Losses 23,282 16,219 kWh/yr
HydrogenTank
Variable Value Units
Hydrogen production 4,909 kg/yr
Hydrogen consumption 4,869 kg/yr
Hydrogen tank autonomy 31.9 Hours
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Emissions
Pollutant Emissions (kg/yr)
Carbon dioxide -49.7
Carbon monoxide 31.7
Unburned hydocarbons 3.51
Particulate matter 2.39
Sulfur dioxide 0
Nitrogen oxides 282
Sensitivity Analysis
A challenge that often confronts the system designer is uncertainty in key
variables. Sensitivity analysis can help the designer to understand the effects of
uncertainty and make good design decisions despite the uncertainty. A sensitivity
analysis can be performed by entering multiple values for a particular input
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variable. HOMER repeats its optimization process for each value of that variable.
An input variable for which you have specified multiple values is called a sensitive
variable, and many sensitive variables can be defined. A sensitivity analysis can be
referred to as one-dimensional if there is a single sensitive variable. If there are
two sensitive variables, it is a two-dimensional sensitivity analysis, and so on.
HOMER's has the most powerful graphical capabilities which is developed to help
and examine the results of sensitivity analyses of two or more dimensions.
Since Avg.Wind Speed of Coimbatore is too low if the same system is to be
implemented in nearby area where there is large amount of wind available we had
included the Sensitivity analysis of Avg.Wind Speed Vs Global Solar Energy.
Challenges Faced:
When performing a sensitivity analysis on the load, many sizes of each equipment type must
be considered to meet the range of loads evaluated. To reduce the computation times HOMER
runs were performed in an iterative process. Initially, the optimization search space
considered only a few component sizes over a large range. Similarly, the sensitivity analyses
covered a large range with few points. This helped to decrease the initial run-time. With each
successive run, more options and variables were added to increase the resolution and fill in
the search and sensitivity spaces.
Obtaining data for analyses such as these is always challenging. This is especially
true for the wide variety of windmills that are commercially available. It is often
hard to know a priori which inputs deserve a lot of effort getting precise data.
Rough estimates of variables, such as O&M cost, lifetime, and part-load efficiency,
can be entered into the program. A HOMER sensitivity analysis on these variables
can then inform the user of the value of improving the accuracy of that input
variable.
Glossary:
1.Salvage present value or the recovery value: The net value of the equipmentused at the end of the system's service life. The salvage or the residual value
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of components is based on the possibilities of alternative uses at the end of
the project lifetime.
2.Feasible system: A system that satisfies the specified constraints.3.Levelized cost of energy: The average cost of producing one kilowatt-hour of
electricity, including capital, replacement, fuel, operating and maintenance
costs.
4.Maximum annual capacity shortage: The percentage of the yearly total loadthat is allowed to go unserved by the system.
5.Net present cost: The present value of the cost of installing and operating thesystem over the lifetime of the project (also referred to as lifecycle cost).
6.Optimal system type: The combination of power-generation technologieswith the lowest net present cost.
7.Renewable energy fraction: The portion of a systems total electricalproduction that originates from renewable power sources.
8.Search space: The set of all system configurations that HOMER evaluates.9.Sensitivity analysis: An investigation into the extent to which changes in
certain inputs affect a models outputs.
10.System type: A combination of power-generation technologies.