Stochastic demand side management in European zonal price market

In this paper, demand-side management (DSM) is performed through demand response aggregators (DRAs) in an uncertain environment within zonal price market framework. The proposed scheme aims to allow cross-border electricity trading and optimize interconnections usage as well as to obtain optimum DR volume from the perspective of the Market Coupling Operator (MCO). The market consists of several zonal price markets as Nominated Electricity Market Operators (NEMO) who run their day-ahead and balancing market internally and communicate the information to the MCO to provide the cooperation with other NEMOs. To this end, a stochastic two-stage model is formulated in which the total operation cost from MCO's viewpoint is minimized. Accordingly, the model aims to consider day-ahead decisions in the first stage and balancing decisions in the second stage. Furthermore, the intermittent nature of renewable sources generation is handled by scenario generation with Monte-Carlo Simulation (MCS) method. NEMOs are physically connected as radial network. Therefore, all relative network constraints are taken into account as a linear power flow for radial networks. The results of the implementation of the proposed model demonstrate the effectiveness of various DR biddings on hourly DR volume, hourly DR cost and power exchange between different NEMOS.