Flexibilization of industrial customers through real time pricing based on multi-agent modeling

In 2019, 42 % of the gross electricity consumption in Germany was provided by renewable energies, with the aim of increasing this share to over 80 % till 2050. For the efficient integration of fluctuating feed-in (e. g. wind or solar energy), transmission and distribution network infrastructure must be expanded, but also additional flexibility in supply and consumption is needed. Dynamic electricity prices can create incentives for final consumers to adjust their consumption. In the presented paper, a real time pricing model for the German electricity market is developed based on a multi agent approach. In order to limit the price risk, the supplier calculates a specific surcharge added to the customer prices. The customers then calculate their order quantities in an internal optimization problem based on the prices. The bundled customers’ quantities are traded on the energy markets. An analysis of market data of 2019 was conducted. Compared to a standard tariff the industrial customers reduce their energy costs by around 6 % to 8 % while the supplier achieves a revenue of 9 %.