This article deals with the following topics: - What are data point strategies?
- A list of all strategies
- Example: calculating the summ of child facilities
1. What are data point strategies?Every facility data point has a strategy that collects data from various external and internal sources series to process them. A data point receives its data , depending on the strategy, either from external time series, another data point or more than one data point, depending on the strategy. ThereforeTherefor, a facility data point always needs a strategy to find data and process it according to its specific requirements.
2. A list of all strategiesVarious strategies are available for you in QBRX, which . They are all grouped up by their respective source time series. At the left side The first two columns of the table, you can see the source and the its matching strategystrategies. The following columns deal with the possible configurations of the targeted time series. The Description gives additional information about the strategy. | Source | Startegy | Numeric | Boolean | Enum | Not periodic | Periodic | Linear interpolated | Keep-last-Value | Description |
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| External | Reference to external data | | | | | | | | External data is converted to internal data and will be normalized and interpolated depending on the targeted time series. Example: meter readings, temperatures, switching states |
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| Derivation of external data | |
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| | The derivation calculates the course growth of a source time series. Derivated, external data will be normalized and interpolated according to Keep-last-Value. Example: calculation of the load profile from active energy | Reference
| Data point reference | | | | | | | | Data is copied from one data point to another and interpolated depending on the targeted time series. Example: using the same value at different facilities (e.g. the outdoor temperature of a site for all corresponding buildings) |
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Data point reference with differentiationderivation | |
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| | The derivation calculates the course growth of a linear interpolated source time series. Derivated data will be normalized and interpolated according to Keep-last-Value. Example: calculation of the load profile from active energy | | Data point reference with derivation(only positive values) | |
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| | The derivation calculates the course growth of a linear interpolated source time series. Derivated data will be normalized and interpolated according to Keep-last-Value. Negative values, that stem from a descending course of the source time series, are filtered out. This avoids distortions of results that could, for example, occur by meter exchanges. Example: calculation of the load profile from meter readings. that can be resetted | | Data point reference with integration | |
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| The integral calculates the area beneath a graph. In this case, data of a referenced Keep-Last-Value data points are integrated and and result in a linear interpolated time series. Example: calculation of active energy from the load profile | | Child facilities | Average | |
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| | | | With the help of this strategy, the data point receives values from ata points of subordinate facilities with the same meaning. The interpolation depends on the meaning and therefore stays the same. The average and sum are calculated with these values. In contrast to other strategies, sources are determined automatically and don't have to be chosen. Newly added, matching data points will be included immediately. Example: evaluating all load profiles of a site |
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| Sum | |
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| | | | | Script | Custom | | | |
| | | | Custom calculations can be created in QUDE with respective source time series. Those source time series stem from internal data points and properties. More information can be found here. |
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| Value from logic class | Value from logic class | | | | | | | | This strategy was designed for special use cases. The values come from the facility itself. Their source depends on the respective case. Example: site facilities get outdoor temperature values from a meteorological service that uses the geo-coordinates |
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| Manual value input | Manual value input | | | | | | | | Data points with this strategy make it possible to enter values manually at the facility. The added data will be saved at an external time series and can be interpolated and normalized depending on the meaning. Example: manual meters |
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3. Example: calculating the sum of child facilitiesThe strategy "Sum of child facilities" gives the data point two kinds of information: - He'll get his data from all data points of child facilities with the same meaning, that are one layer beneath itself
- and this will be processed depending on the source data.
Like this, a load profile data point would collect all load profiles from subordinate facilities and add them up. 
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