Dissertation: Methodology (5 of 8) - Formulae (2)

  and otherwise (Equation 5)

In the case of simulating solar-powered electricity generation, there were two levels of potential obstruction (i.e. clouds and lack of daylight). In the model, the user is able to manipulate both of these by selecting the percentage of cloudiness and by adjusting sunset and sunrise. Initially, the model checks to see if a cloud is covering the solar farm. If so, zero electricity is generated. If not, the model is dependent upon the time of day as described below:

Before noon: , and after noon: .

Before sunrise:   and after sunrise: .

Before sunset: and after sunset: .

Essentially, this generates an equation where the solar farm generates electricity in a sinusoidal pattern – based on the time of day t_day compared to sunrise T_sunrise and the length of daylight L_daylight (as determined by the time difference between sunrise and sunset) – during the day and nothing at night.

Unlike intermittent renewable generation sources, traditional generation sources are operated in a manner designed to meet consumer demand for electricity. This greatly simplifies the equations required to simulate them. However, traditional generation sources can also be run in different modes, which can result in different levels of generation from different types of plants. The two primary modes of plant operation are ‘base load’ and ‘peak load’. As the name implies base load plants form the base of generation needs and run more or less constantly. Whereas, peak load plants are only called into operation during times of peak demand. Since the model is organized based on the fuel type of the generation capacity rather than on individual plants, a third mode of operation was created, which was called ‘mixed load’ and denoted that some plants of the fuel type were operating in base load while others were operating in peak load.

The user interface made use of drop-down field forms. Thus, the actual equations required a significant amount of logical coding in order to match each type of generation with the correct mode of operation. In summary: a generation type in base load constantly operated at its nominal capacity, a generation type in peak load only operated if all other generation options were exhausted, and a generation type operating in mixed load operated only to fill the gap between the base load generation and consumer demand. Also, if multiple types of generation were operating in mixed or peak load, the amount of generation required was distributed evenly among those types but did not exceed the nominal capacity of any particular type.

The user interface offered a choice between having traditional generation account for renewable generation or not. In BL traditional generation needed to take into consideration the electricity generated by renewable sources or else electricity generation did not match demand. In all other scenarios ES rather than traditional generation moderated the renewable generation.

Due to the distinction in GHG emissions, spinning reserve generation was delineated from normal operation. Only generation types operating in mixed load were called into service to operate in spinning reserve. Further, the total generation (i.e. the combination of normal and spinning reserve generation) of each type never exceeded the nominal capacity of that type. It should be noted that this did mean that at least one type of traditional generation needed to be in mixed load for the model to operate properly; however, this is not inconsistent with the real world.

The outputs of the model can be delineated into two groups. The first group of outputs is the diagnostic outputs, which were useful for comparing the model results to the real world and indicating potential errors in the model (see section III.3.d.). The second group of outputs is those highlighted in the results section (e.g. the net GHG emissions and the GHG emissions attributed to ES). The final paragraphs in this section will briefly describe the manner in which the second group of values was calculated.

GHG emissions were calculated in essentially two parts. First, the GHG emissions associated directly with electricity generation was calculated by attributing emissions to each MWh of electricity generation segregated by each type of generation based on the GHG emission rates indicated on the user interface. Also, any spinning reserve generation would have an increased emissions rate. The user interface allowed the proportionate increase in emissions created by fossil-fuel powered plants in spinning reserve to be chosen (non-fossil-fuel powered plants are exempt from this increase because their GHG emissions are associated with construction and decommissioning of the plant rather than plant operation; see section II.2.a. for further explanation). For all scenarios, the value of 0.5 (or a 50% increase in emissions) was applied to plants in spinning reserve mode. Finally, all of these values were summed over all generation types during all intervals to determine the ‘non-ES-related emissions’ and divided by the total electricity generation (measured in MWh) to determine the average rate of emissions for the electricity grid.

Second, the GHG emissions associated with the use of ES were determined by comparing the energy put into storage with the energy withdrawn from storage over the entire week. After accounting for energy losses from the roundtrip cycle efficiency, the model determined how much excess stored energy remained or how much additional energy needed to be produced to make use of the ES. Then, this value was multiplied by the average rate of emissions for the electricity grid as described in the previous paragraph. A positive value of ES-related emissions would indicate that additional emissions (and electricity generation) would be necessary to maintain the use of ES. On the other hand, a negative value would indicate either that electricity generation could have been reduced during the week or depending on the type of ES technology in use that the excess energy could be saved for use during a later time period. Thus, the net GHG emissions are simply the non-ES emissions plus the ES emissions.

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