A Two-stage Stochastic Programming DSO Framework for Comprehensive Market Participation of DER Aggregators under Uncertainty

TL;DR

This paper introduces a two-stage stochastic programming framework for distribution system operators to enable diverse DER aggregators to participate in markets under uncertainty, considering network constraints and various DER types.

Contribution

It develops a comprehensive MILP-based model that incorporates multiple DER aggregator types and network constraints for market participation under uncertainty.

Findings

Effective modeling of diverse DER aggregators

Successful case studies demonstrating framework performance

Enhanced market participation under uncertainty

Abstract

In this paper, a distribution system operator (DSO) framework is proposed for comprehensive retail and wholesale markets participation of distributed energy resource (DER) aggregators under uncertainty based on two-stage stochastic programming. Different kinds of DER aggregators including energy storage aggregators (ESAGs), demand response aggregators (DRAGs), electric vehicle (EV) aggregating charging stations (EVCSs), dispatchable distributed generation (DDG) aggregators (DDGAGs), and renewable energy aggregators (REAGs) are modeled. Distribution network operation constraints are considered using a linearized power flow. The problem is modeled using mixed-integer linear programming (MILP) which can be solved by using commercial solvers. Case studies are conducted to investigate the performance of the proposed DSO framework.