Risk-based medium-term trading strategy for a virtual power plant with first-order stochastic dominance constraints

Distribution systems of the future will definitely encompass numerous distributed energy resources, and thereby, the physical connection and commercial contribution among virtual power plants (VPPs) will be inevitable. Accordingly, this study proposes a methodology to address the trading strategies of a VPP in cooperation with its neighbouring VPPs. This cooperation is modelled based on some available cross-regional contracts and the problem faced by the VPP is how to determine its bilateral contracting portfolio. To this end, a decision-making framework for medium-term self-scheduling of a VPP with the aim of exercising arbitrage between two different trading floors, i.e. bilateral contracts and the electricity market, is presented. Moreover, an efficient risk management approach based on the concept of first-order stochastic dominance constraints is used to enable informed decision making under different levels of uncertainty. The resulting model is formulated as a mixed-integer linear programming problem that can be solved using off-the-shelf software packages. The efficiency of the proposed model is analysed through a detailed case study, and finally relevant conclusions are duly drawn.