The Art of Accurate Electricity Load Forecasting Services
Energy Load Forecasting is fundamental for the energy planning sector since a time-ahead power market requires demand-scheduling for power generation, transmission, distribution etc.
Forecasting can be performed with different methods; the selection of each method relies on several factors including the quality and the relevance of the available historical data. Also, the method used is strictly correlated with the forecast horizon and the level of accuracy of the historical data.
The time horizon is chosen based on the specific application in power system planning; i.e. the time horizon is specified according to each participant’s needs.
Distribution and transmission planning need a short-term horizon while financial or power supply planning require a more long-term horizon. Energy market participants, depending on the market structure they participate in, might require a very short time horizon and lastly, end consumers require a mid-term time-horizon. Based on the time-horizon and the level of data aggregation the adequate method is used.
At NET2GRID we provide, on an aggregated basis, varying load forecasting services depending on the needs of different stakeholders. What makes our solution unique is that we are able to address divergent load forecasting spectra, i.e. the long-term for next weeks, months or years and the day-ahead, while maintaining very high accuracy standards.
Our services accuracy of the forecasting procedure based on the Mean Absolute Percentage Error (MAPE) metric can be as good as 1.9% based on the integrity and the availability of past data. At NET2GRID we are utilising the latest Artificial Intelligence (AI) neural networks and Machine Learning (ML) techniques to continuously improve our forecasting services.
In the white paper we describe the following topics in more detail with accompanying pictures:
Definition of Electricity Load Forecasting
Supply – demand Equilibrium
Different Load Forecasting Services from NET2GRID
How it works
Forecasting of Peaks and “Consumption Spikes”
Moving to the Real-Time world
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