9. Methodology
In section 8 we considered the case of the lowest demand in the year and took a "top down" approach to wind energy integration, starting with the potential for 100% penetration at that time. The top down approach differs from the approach typically found in overseas studies which starts with existing wind farms and works up. Not all countries have sufficient wind resources to provide in excess of 100% of their total energy requirements, as we appear to in New Zealand, so taking a different approach is not inconsistent with our particular situation.
A top down approach encourages the industry to think further ahead, anticipating problems and investigating solutions instead of reacting to each new wind farm proposal.
On the other hand, a top down approach should not be oversold as there are many challenges ahead for wind energy, and a high level of penetration is by no means assured, not least because wind competes with other equally viable types of more conventional generation.
The methodology recommended in this study follows, in part, the method employed in the low demand case study, although it could be applied to any level of generation.
The methodology can be applied at different levels of detail and accuracy. For example, the level of detail applied in this study primarily uses information from overseas studies and other information readily available, without the need for a comprehensive national wind dataset or resorting to detailed modelling studies.
A significantly higher level of detail and accuracy will require access to a wind dataset and the use of appropriate analytical tools and models, and would allow for more accurate assessments over a wide range of demand and conditions on the grid.
The methodology is illustrated diagrammatically in Figure 13 and Figure 14 and described in more detail below. The method follows through a series of steps but may require repeating steps in some cases, for example in calculating instantaneous reserve requirements.
- Choose island
The North and South Islands must be treated separately for the purposes of calculating the regulating and instantaneous reserves requirements. - Set total generation
Set the demand level and add losses to obtain total generation, or start with a generation value. - Regulation allowance
From the generation starting value, subtract an allowance for the regulating station, made up of the total of the minimum control output plus the control band. Note that a second regulating station can be added if required. - Wind planning margin
Subtract the minimum output of any stations that may be required to start or operate now, in anticipation of being required at a later time past the end of the current half hour. - Voltage support
Stations constrained to provide voltage support close to large load centres; - Marginal station
Subtract the minimum output for at least one marginal (load following) station, or more stations if required. The range of variation potentially required of the marginal station is equal to the largest expected variation of all wind farms in aggregate, though this variation value does not get subtracted. - Fault ride-through and grid stability
Check the remaining wind farms can ride through faults and achieve a stable grid during normal operations and immediately after any contingency. If not, then subtract an appropriate amount to allow for additional conventional generation. - Reserves risk
Calculate the largest contingency, which could be a conventional station or even a wind farm or potentially all wind farms in a small geographical region. - Reserve adjustments
Calculate the risk offset adjustments based on the balance of the generation being supplied by wind farms. - Instantaneous reserves
Check the adjusted FIR and SIR. Though some of this risk may be covered by ILR, assume some will be covered by PLSR so subtract the PLSR station's minimum output at which it can provide PLSR. For larger IR requirements, subtract an allowance for another PLSR provider. - Wind energy
The MW value remaining is the maximum amount of wind energy that can be safely supported given the demand conditions assumed prevailing for the assessment.
The methodology is intended to be applied to a half hour period,68 but ideally not just a single half hour. It should be applied, in the limit, to each and every half hour in a hypothetical test year, using the output from appropriate modelling and analytical studies. A suitable wind speed dataset was not available to this study so it was not possible to investigate a large range of scenarios for realistic wind speeds and wind speed variations, for a dispersed collection of wind farms, with any degree of confidence.
The analysis in section 8 therefore is a "single point" analysis. With the benefit of a wind speed dataset and the appropriate analytical tools, the methodology would be applied to all periods of interest and steps 3 - 10 above would be worked though in detail using appropriate tools.
For example, step 3 should include an analysis of the deviations in frequency created by, or along with, the wind farms actually being modelled, to allow a more accurate assessment of the amount of regulation required.
Similarly, step 4 should ideally be undertaken using a wind dataset representative of New Zealand conditions and based on tests of real wind forecasting models.
Step 7 should ideally be based on rigorous analysis using tools designed to analyse conditions on the grid and using a realistic wind dataset.
Steps 8 through 10 should ideally involve analysis with a model like Transpower's RMT69 using the generation plant that would actually be dispatched during each period being considered.
9.1 Wind Planning Margin
The wind planning margin is particularly difficult to estimate without the benefit of a wind dataset. It is a function, to a very large extent, of where wind farms are built and how the output of many wind farms correlate with each other. It requires the answer to basic questions such as: How likely is it during the period of interest that all wind farms will have zero output? How likely is it that any given wind farm will have a large change in output, either up or down? How likely is it that large swings in output will coincide? How well can the output of individual wind farms be forecast up to 36 hours in advance under New Zealand conditions?
If wind farm output can be forecast with a high degree of accuracy, or if there is sufficient and flexible plant available of a conventional nature, then the wind planning margin could conceivably be relatively small on average even with very high levels of wind integration. On the other hand, if forecasts have a high degree of uncertainty and plant must often be started hours in advance to cover for wind farm variability, then the wind planning margin could be substantial on average.
9.2 Applying the Methodology
In section 8 we applied the methodology to the lowest demand expected in 2005. In this study, the relative economics of wind was not a factor to consider in assessing the potential for wind integration, unless there was reasonable doubt that wind energy would be viable or acceptable under more extreme scenarios. Applying the methodology as in section 8 to a half hour with higher generation would most likely indicate an even higher level of penetration, given our assumptions, than obtained in section 8. Such additional analysis would lead to scenarios with unrealistically high levels of wind generation penetration, possibly in excess of 50%.
Under these scenarios, for example, any excess wind farm output over and above what can be dispatched during the lowest demand periods will be at least partially spilled. This spilling of wind could significantly reduce the economic viability of wind farms under these scenarios and potentially threaten the viability of other, existing generating plant.
In view of this potential, and also keeping in mind that reaching market share of 20% would take at least several years to achieve, over which WTG technology is likely to make further advances and be a significant challenge to the industry, the methodology has not been applied to any periods with higher demand.
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