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Period start | Region ID | Region | Average region price ($/MWh) | Average reference price ($/MWh) | Average LF | Minimum LF | Lower quartile LF | Median LF | Upper quartile LF | Maximum LF |
---|---|---|---|---|---|---|---|---|---|---|
01/07/2009 | HAY2201 | HAY2201 - Haywards | 60.6554 | 60.5039 | 1.0025 | 0.8873 | 0.9841 | 1.0061 | 1.0373 | 1.7260 |
01/07/2010 | HAY2201 | HAY2201 - Haywards | 79.8268 | 79.5646 | 1.0033 | 0.8666 | 0.9687 | 1.0115 | 1.0423 | 1.1515 |
01/07/2011 | HAY2201 | HAY2201 - Haywards | 50.9853 | 52.0102 | 0.9803 | 0.8936 | 0.9462 | 0.9791 | 1.0059 | 1.0974 |
01/07/2012 | HAY2201 | HAY2201 - Haywards | 80.3524 | 79.5879 | 1.0096 | 0.8751 | 0.9485 | 1.0019 | 1.0540 | 1.1690 |
01/07/2013 | HAY2201 | HAY2201 - Haywards | 53.1134 | 57.3275 | 0.9265 | 0.7980 | 0.9154 | 0.9226 | 0.9316 | 1.0061 |
01/07/2014 | HAY2201 | HAY2201 - Haywards | 57.5466 | 61.6427 | 0.9336 | 0.7975 | 0.9095 | 0.9310 | 0.9582 | 1.0487 |
01/07/2015 | HAY2201 | HAY2201 - Haywards | 51.8917 | 53.7282 | 0.9658 | 0.8736 | 0.9382 | 0.9634 | 0.9984 | 1.5480 |
01/07/2016 | HAY2201 | HAY2201 - Haywards | 58.9493 | 67.5761 | 0.8723 | 0.6397 | 0.8474 | 0.8704 | 0.9029 | 0.9723 |
01/07/2017 | HAY2201 | HAY2201 - Haywards | 142.9437 | 135.3104 | 1.0564 | 0.9409 | 1.0261 | 1.0577 | 1.0847 | 1.1562 |
01/07/2018 | HAY2201 | HAY2201 - Haywards | 73.8257 | 81.9286 | 0.9011 | 0.8343 | 0.8844 | 0.8990 | 0.9289 | 0.9902 |
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This report calculates historical location factors for a region or node relative to a selected basis node. A location factor is simply the ratio energy prices at two different locations. They are commonly used to adjust prices from one node to what it might be at another node or in another region.
A location factor (LF) is simply the ratio of two prices – the price at one node or location relative to the price at a basis node. Spatial price differences arise because of transmission losses and may be exacerbated if transmission constraints are present or traders are able to exploit a pivotal position in the market. Nodal pricing (or locational marginal pricing) in electricity markets is a key driver of the price signals that lead to efficient investment over the long term and the optimal utilisation of available resources in the short term. Historical location factors can be used to adjust pricing at one node to what it might be at another node or in another region. This type of information and understanding is useful when contemplating forward positions or when seeking to manage locational price risk. For example, an integrated generator-retailer might own generation at one location and simultaneously need to satisfy a customer load base at several other locations. Alternatively, a buyer of electricity at a specific location who is seeking to hedge that load would want to compare with the price at the location at which the forward contract is settled. Forward contracts are used by participants to manage risk. Such contracts may include bespoke over-the-counter contracts between two parties, exchange-traded standardised contacts settled at Otahuhu and Benmore where the counter-party is the exchange, and financial transmission rights (FTRs) between points on the grid at Otahuhu, Benmore, Haywards, Islington, Invercargill, Whakamaru, Kikiwa, and Redclyffe. Location factors are required in the context of the hedge arrangement disclosure regime – see subpart 5 of part 13 of the Code
The location factors in this report are derived across all trading periods equally; they are not weighted by demand or filtered by peak periods. In other words, they share a design aspect with base load futures contracts traded on ASX. Location factors for regions other than nodes are derived from the simple average price of all nodes comprising the region. The data report (data tab) includes some additional information not shown in the graphical report, i.e. the proportion of time that a node is connected to the grid or, equivalently, has a price during the selected period. Relative to a basis node, the report allows comparisons across both time and space. For example, the location factor for two different regions can be compared, e.g. Upper North Island vs Central North Island. Alternatively, the location factor of a single node, e.g. Whakamaru (to Otahuhu) covering the first quarter of the year can be compared for, say, the last five years. A box and whisker plot provides information on the distribution of the location factor. A very large maximum location factor will impact the average location factor for the period, so care is needed when interpreting what information is being conveyed by the location factor, especially if the event leading to the high value is a low probability event or is unlikely to occur in the future. Large location factors can be due to extremely low pricing at the basis node. Note that a box and whisker plot will be shown for the current incomplete period, if the selected date range spans more time than the selected period. This feature allows users to track a location factor and its distribution as the current period, e.g. a quarter or a month, progresses, relative to historic instances of that period. The nodal prices used to compute location factors are available from the wholesale price report or in files able to be downloaded from wholesale datasets
Duration of month, quarter, and year denotes the time scale over which the location factors are derived. These align with the available exchange-traded instruments. For quarters and months, an additional parameter appears that allows the same quarter or month within the date range to be considered. For example, all Q2 location factors since 2010. Some care is needed to ensure you have selected a period that is within your chosen date range.
The basis node defines the denominator in the derivation of the location factor for the node or region in the series filter. For example, an average location factor of 0.93 for the Lower North Island covering the 2018 calendar year using Otahuhu as the basis node tells us that on average, the nodal price in 2018 across all nodes in the Lower North Island, was 0.93 times the price at Otahuhu.
Region types are either network-based or derived from standard statistical boundaries. The current network-based regions are nodes and zones. Mappings are provided in the NSP table which is available as a wholesale report.
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