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Lancelot - Model FMS - Rich Collection of Tools for Calculating Predictions
Lancelot brings a rich collection of tools for calculating predictions in time series, models of weather and calendar effects on electricity and gas generation and consumption or models of different renewable energy sources. Moreover, Lancelot allows to create your own predictions combining all these ready tools.
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Examples of available predictions
Basic load forecasting
Basic load forecast predicts the behaviour of a general time series with an unlimited horizon. The prediction step is unlimited, ranging usually from one minute to one day. In combination with weather models, Lancelot is able to use historical data and forecasts of temperature, solar radiation, cloudiness, wind speed and humidity. The resulting accuracy mostly depends on the portfolio structure and the quality of the meteorological data. For a sufficiently large portfolio, the MAPE of resulting forecast reaches accuracy below 2% in electricity and 4% in gas.
Regional consumption forecast
The forecast of regional energy consumption is particularly suitable for dispatch centers of transmission and distribution operators or for local networks. It is based on the basic load forecast in combination with the weather model and calendar for the specific region. The horizon of the forecast is unlimited and the resulting accuracy of the regional forecast is very high.
Portfolio generation and load forecast
A trader`s portfolio includes his own or third-party generating resources as well as the consumption of his own customers.
The prediction system is designed to respect all past and future changes in the portfolio and to provide the forecast over an unlimited time horizon. All data is loaded on-line and the results are updated immediately. The used computation method is called "temporal balance" and allows to obtain the top-down prediction of generation and load of the entire portfolio in a single time series.
RES production forecast
The RES generation is predicted either separately or as a part of trader`s portfolio. For each type of renewable source, specific models describing its behaviour have been developed. Such models have only a minimum of parameters and they are learning and self-correcting over time to reflect the seasonal parameter changes as well as changes in the resource structure, for example aging of photovoltaic panels. All data for these models are loaded on-line and the results are updated immediately.
Day-ahead and intraday market price
The input data for this prediction are the past prices on day-ahead and intraday market, weather in relevant countries and possibly also the offer structure on the given market. All data is loaded on-line and the results are updated immediately. The result is the price of electricity on the day-ahead market for each hour of the next day and for subsequent days. In the intraday market, the price for the current hour of the day and for all subsequent days is predicted. The input data is the same as the day-ahead price prediction and its accuracy is similar.
Consumption of non-metered delivery points
A typical trader`s portfolio at least partly includes the aggregated consumption of supply points with non-continuous metering. There is no metering available for these delivery points. Instead, the load profiles provided by Market Operator are used but only for the past. For the future data, the trader has to use his own prediction. For each month, we guarantee a higher accuracy of predicted load profiles than are the results correcponding to the residual balance coefficient.
System imbalance prediction
The intraday market typically closes one hour before real time. If you want to speculate on the imbalance, it is necessary to predict the system imbalance. This prediction is updated every minute according to the data from the TSO and other sources. Our solution takes the expected direction of system imbalance, day-ahead and intraday market prices, the prediction of trader`s imbalance price, and uses them to recommend to take either a long or a short position and the resulting risk. The solution works similarly for day-ahead market as well.
Our solution benefits
- Short-term, medium-term and long-term prediction
- High prediction accuracy including self-learning mechanisms
- Advanced analytics tools and user-definable reports and views
- Integration with Lancelot Hub as a source of various data sources
- Automatic correction of low-quality or missing input data
