Ways of interaction between providers and consumers of forecasts of electrical power consumption based on neural network information system
Forecasting is required for effective control of the processes of electric power transmission and consumption, load estimation, and reduction of technical and commercial losses. The methods based on artificial neural networks are the most universal. However, practical application of those methods is limited by the complexity and the cost of software and by high requirements to the personnel who create and operate such systems. We propose two ways of the interaction between providers and consumers of forecasts of electric power consumption that solve those problems. The first way implements "model as a service" conception and the second way implements "forecast as a service" conception.