Holistic Day-Ahead Scheduling Approach for inhomogeneous Pools considering common German Compensation and Cost Structures

Abstract

In this paper a mixed-integer linear programming optimization approach is introduced, which allows a detailed modelling of various Virtual Power Plants (VPP) consisting of different generation, storage and demand assets with specific operating costs, incentive tariffs, sales channels and usual operation restrictions such as minimum and maximum demand and generation power, load gradients, etc. The assets can thereby be considered as independent units with an own grid access, but can also be assigned to complex grid connection points (GCP) where the units are then utilized to meet local heat and electricity demand, maximize profit and comply to local restrictions. In addition to that it is possible to define soft and hard feed-in and acquisition constraints for the overall VPP energy schedule. To enable the VPP optimization and take into account these three different optimization levels, an accounting method which considers all internal and external usages of energy for each asset is introduced. The simulation results show that the optimization model can effectively find the economically best schedule by varying trading volumes, energy self-sufficiency of single users or exchange of energy within the VPP.