Solar Analysis Project
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Contents |
Decision Situation
What is the best way to avoid C02 emissions in the Sydney Basin by using Solar Photovoltaic Cells?
Modeling Methodology
The study was undertaken to identify what the cost of electricity would be from a large scale investment in solar photovoltaics. There are a number of parameters that may vary appreciably over the duration of the study period and this effect needs to be taken into consideration. The model was created by first identifying the following:
1. The parameters of the technology. This included conversion efficiencies, capital and operational costs, embedded pollution and longevity. Also included are identified trends in these values that can be extrapolated over the duration of the study.
2. The availability of the resource. For distributed solar, this is done through the determination of the available roof space for both residential and commercial areas and long term averages for insolation. Trends in population and housing growth are also incorporated.
Then the rate at which the technology is adopted and the maximum penetration need to be determined. These play significant roles as distributed solar develops along a much more linear progression than centralized generation. This impacts the cost and efficiency of the system (due to time variance of these values).
Findings
The results of the model are presented in the graphs below. What they indicate is that, although the cost of solar generation is going to decrease over the coming decades, there will still be a need for initial subsidies or tariffs in order to allow the technology to compete economically with conventional centralized, fossil-fuel driven solutions. The following graphs are generated by analytica, from the actual data extracted from this wiki. in the ultimate implementation, this would be automatically done and updated by the math engine and/or other system components
Cost of Electricity The average cost of electricity from the project, listed in effective wholesale prices, was obtained by determining the total cost of the electricity generation (including capital, replacement and operational expenses) and dividing by the total electricity generated, and then subtracting any additional subsidies such as feed in tariffs.
This graph outlines the approximate cost of the energy for each of the principle technologies investigated. Displayed are the basic cost of the electricity without the benefits of REC offsets of feed in tariffs, in addition to indicating the cost with either or both of these subsidies. It can be seen that without subsidies, the cost of generated electricity varies from $53.60/MWh - $61.14/MWh. If the real price of centralized power generation remains the same, this distributed generation will be unable to compete on an open market. However, with the addition of subsidies, the price is decreased sufficiently to approach current market prices for electricity.
Cost of electricity versus the cost of CO2e emissions offset It is possible to compare this electricity price cost with the amount of carbon emissions offset by the same cost.
In NSW CO2 emissions from conventional power sources is approximately 0.906 tonnes CO2e/MWh, and the emissions from the different solar technology types are relatively small, so there is an almost linear correlation between the cost of CO2 abatement and the cost of electricity. As with the graph above, there are four clusters of points correlating to the four following scenarios:
- Including a feed in tariff
- Including REC revenues
- Including both a feed in tariff and REC revenues
- No subsidies
The best result is obtained by the amorphous panel installation, which would be due to the lower capital cost of the panels despite their reduced conversion efficiency.
Total Energy Produced
Investigating the actual energy that will be produced, a number of factors need to be considered. These include the rate of adoption (which played a role with the cost determination), social acceptance of panels, the economic viability of their installation, ROI, and available roof size. Generation will also be impacted by influences such as panels that are installed later in the period of study are assumed to have improved efficiency while seeing lower capital costs, as reflected by current trends.
The total annual generation from the greater Sydney area, within the assumptions of the model, is displayed in the graph below.
The amount generated from the amorphous solar panels climb towards the end of the study to match those of the polycrystalline.
Assumptions
The project has some basic assumptions used to set boundaries to the analysis.
The Discount Rate is 0.05 [1].
The Project Life is 30 years.
For the purposes of the study, the following Zoning Restrictions will apply: (Commercial,Industrial,Residential)(FractionUsed)(0.7,0.0,1.0). The zoning restrictions are the amount of the zone that will be considered within the scope of the project, and are normally applied due to factors associated with the studies involved.
Decision Variables
The following decision variables will be considered for the project:
- Solar Cell Panel Type
- Inverter Type
Model
The model used to generate this output is an Analytica file File:Solar Analysis Schema 2 V2 3.ANA. In order to view the file follow these instructions How to install the Free Analytica Player.
Inputs
References
| Cite | Matthew Sullivan + |
| DecisionSituation | What is the best way to avoid C02 emissions in the Sydney Basin by using Solar Photovoltaic Cells? + |
| DecisionVariable | Property:PanelType +, and Property:InverterType + |
| DiscountRate | 0.05 + |
| ProjectLife | 30 yearsinfo.png'30 years'+ |
| ZoningRestrictions | (Commercial,Industrial,Residential)(FractionUsed)(0.7,0.0,1.0) + |
