ENERGY CONSUMPTION FORECAST & PURCHASE OPTIMIZATION FOR TOMORROW
By putting Precog-IP on the market, we solved something that had seemed to be unforeseeable. We involved actors of the energy market into our R&D activity of several years and as a result, we harmonized energy consumption with its production and purchase.
Although the need for electricity, natural gas and district heating is influenced by numerous factors, our solution helps to decrease the risks stemming from different sources of energy market.
Precog-IP forecasts the expected energy consumption and makes recommendation as to the purchase and the selling of wholesale energy products meanwhile it helps keeping the financial risk of the portfolio at a minimum level. Due to its numerous functionalities, it supports consumer segmentation and internal pricing. Moreover, it easily analyses the current (ATC), the future (flow-based) and the transitional (hybrid) EU regulation of interconnected national electricity markets.
It is crucial for the actors of the energy market to generate very reliable forecasts of expected market changes from past data. Precog-IP is able to deliver this prediction and its forecasting skills provide significant competitive advantages to its users.
Precog-IP helps to define homogeneous consumer groups if approximate information is not available about the nature of consumption. Risk-based purchase and consumer pricing may be carried out in (sub)portfolios, as well.
The solution can be integrated into existing systems.
Precog-IP consist of several modules which are able to work separately, or they may be combined depending on the needs of the user. Precog-IP is customizable; we may extend or fine-tune the background solution with unique developments, which may help you to gain business advantages.
Precog-IP offers a flexible choice of input data and parameters during the analysis.
Generating an hourly forward price curve, mainly for forecasting day-ahead prices and analysing future open positions.
Modelling and forecasting hourly and daily (consumption) volumes by mainly considering the complex effects of weather variables.
This is an algorithm which supports wholesale decision-making by enabling the optimal hedging of open positions – it happens through calculating with risks as well as considering the limits of market liquidity.
Creation of homogeneous consumer groups based on consumption and non-consumption-based features.
It provides an opportunity to analyse the international electricity flow deriving from day-ahead auctions and the consequent prices, as well as to carry out sensitivity analysis.
Generating the internal price (so-called transfer price) for the support of the selling process by the enforcement of the so-called portfolio effect which is the advantageous situation caused by consumers of different profiles listed in one portfolio.