The financial analysis predicts a CSP plant’s lifetime payback in economic aspect. Its results show whether a plant is profitable, but could not prove whether it is energy feasible, especially for renewable energy, which cost is usually lowered due to
incentives and subsides. Thus, if a renewable power is only evaluated by its economic payback, the decision may be seriously distorted, for example, a power plant with good profit, but not having positive net energy may be approved.
The energy payback is evaluated with the net energy analysis (NEA), as shown in Figure 45. It identifies energy flows that are consumed and produced by a system. These energy flows include direct energy flows - energy consumed and produced from inception to salvage, and indirect energy flows – energy flows associated with materials and human labor, including material mining, manufacturing, transportation and installation,
operation and maintenance, disposal, and recycle. The net energy of a system is calculated as:
net produced consumed
Figure 45: Demonstration of Net Energy
The net energy is a key parameter to evaluate the attribution of a plant, it could be used to determine whether a power plant is an energy source, carrier, or sink. If the lifetime energy recovered from the plant is more than the energy consumed, the plant is an energy source. If it is equal, it is an energy carrier, which converts one form of energy into another without gain or loss of energy. Otherwise it is regarded as an energy sink. Energy harvest systems should not be energy sinks, since their operation consumes more external energy than their production. Therefore the total energy production is reduced. Figure 46 shows a typical power plant’s net energy performance during its lifecycle.
Energy Produce
Procedure
Total Energy Production
Energy used for production
Net Energy
Production
Figure 46: A typical power plant’s energy outputs and energy costs [68]
However, one important factor about the NEA is that energy contained in fuels (coal, natural gas, wind, solar and else) is not included as an input because the NEA is defined to estimate the energy cost or investment to support a specific process [69]. If energy sources are included, the analysis result would be negative constantly, and the analysis would change to describe a physical energy conversion efficiency of the process instead.
However, to implement a fairly accurate analysis may be quite difficult and complicated, even impracticable, because:
First, it is impossible to find all indirect energy flows. Take human labor as an example, as shown in Figure 47: A person who works in a power plant needs to consume physical power. The consumed energy is represented as the energy coming with food. There is
additional energy required for preparing the food, such as the energy consumed in food transportation, planting, fertilization and irrigation, which all need to be considered. In addition, anything associated with people’s living, for instance, the housing,
transportation, entertainment or medical care, all result in significant energy flows. Therefore the list can be infinite, which makes it unrealistic to analyze.
Figure 47: Demonstration of energy flows caused by human labor
Second, the accurate energy flow involved with each activity is not available, because the consumed energy is not easy to measure, and the consumed energy associated with each activity/procedure/product is not absolutely the same. Numerous factors, such as
Physical Power used in work
Energy consumed in transportation, residence and recreation Energy consumed to design, maintain vehicles, houses and else
Food consumed to support daily work
Energy used to supply electricity Energy consumed to grow food Other indirect and direct cost involves with it.
location, weather, environment, economic level may affect the energy flow. So it is hard to obtain specified energy flows data for a specified CSP plant.
Therefore, only major energy flows are estimated. These energy flows data are obtained from different sources. The result is used to evaluate the energy payback performance of CSP plants.
4.1.2 Evaluation Parameters
Besides lifetime net energy, there are some other parameters which also could be used to evaluate the system’s status and characteristics.
4.1.2.1 Energy Return on Investment (EROI)
The EROI is defined as the ratio of the lifetime cumulative energy production to the energy flows invested in a system.
Energy return to society Energy required to get that energy
production lifetime EROI consumption lifetime E F E
(197)A qualified CSP plant should have an EROI larger than one. Large EROI represents higher energy recovery rate, which is more preferable.
4.1.2.2 Energy Payback Time (EPT)
The EPT is defined as the time, usually in years, that takes the system to produce the amount of energy equal to the lifetime cumulative consumption energy. If the annual energy production is fixed, the EPT, tEPT, can be calculated as:
, consumption lifetime EPT production annual E t E
(198)However, CSP plants are supposed to have a decreasing electricity production during their lifetime due to aging and degradation. In this case, the EPT should be calculated according to: , , ,0 EPT year t
production annual consumption
year lifetime
E E
(199)4.1.3 Method to Estimate Required Energy
Several different methods are used to estimate the required energy, they are:
1. Direct method, which accounts for all materials and energy flows within the system boundary. The energy flows include direct energy flows and indirect flows such as materials, human labor or machinery.
One data source is the Global Emission Model for Integrated Systems (GEMIS). It is a free database which provides net energy consumption information on materials, processes and transportations.
2. Another method is to evaluate the energy flows based on the financial costs by using energy intensity indicators which are derived for each sector of a country’s economy. The energy intensity indicator is defined as the energy flows coming with monetary unit, as shown in equation 200.
_ _ _sec , _
_ _ _sec ,
energy req by tion i energy intensity
monetary req by tion i E
F
C
(200)
One advantage of this method is that the cost data has already been calculated in the financial model. Therefore if the corresponding energy intensity indicators are available, the required energy can be calculated. However, one disadvantage is that the result may be not very accurate since the energy intensity indicator has counted various energy sources besides solar energy. That indicates sole reliance on a general energy intensity indicator data may result in significant data
distortion when the research is only focused on solar energy.
The Green Design initiative in Carnegie Mellon University provides guidance on the relative impacts of different types of products, materials, services, or
industries with respect to resources and emissions throughout the supply chains [70, 71].
4.2 Risk Model