Two stage decision making of technical virtual power plants in electricity market via Nash-SFE equilibrium

Considering the geographic location and the network constraints, technical virtual power plants (TVPPs) integrate distributed energy resources (DERs), including distributed generations (DGs) and demand response (DR) programs, into the distribution system. Therefore, TVPPs facilitate the active participation of DERs in the electricity markets and the optimal operation of them. In this paper, a two stage model for decision making of TVPP is proposed. In the first stage, TVPP minimize its cost with a non-linear programming (NLP). In this stage, DG and DR constraints (i.e. limitations of DG generation and maximum load curtailment) and distribution system constraints (i.e. AC power flows and voltage limits) are considered. In the second stage, the strategic behavior of each supplier is represented via a Supply Function Equilibrium (SFE) model. Therefore, the bidding strategy of TVPP is represented in an intraday electricity market via Nash-SFE. A uniform pricing mechanism is assumed for the market settlement and calculating the supplier profit from selling energy. A typical distribution test system is considered as a TVPP which is connected to the upstream network at a point of common coupling (PCC). Participation of TVPP is investigated in three different load levels of a day. It is demonstrated that the TVPP can get a greater share in electricity market with demand increasing.