Bilevel Aggregator-Prosumers' Optimization Problem in Real-Time: A Convex Optimization Approach

TL;DR

This paper introduces a convex optimization approach for real-time bilevel energy market problems involving aggregators and prosumers, addressing computational challenges of existing methods for large-scale applications.

Contribution

It develops a convex optimization model that approximates the bilevel problem, enabling faster solutions suitable for real-time energy market operations.

Findings

Convex model captures a subset of global optima of the bilevel problem.

Proposed approach reduces computation time significantly.

Applicable to real-time energy market scenarios with many prosumers.

Abstract

This paper proposes a Real-Time Market (RTM) platform for an aggregator and its corresponding prosumers to participate in the electricity wholesale market. The proposed energy market platform is modeled as a bilevel optimization problem where the aggregator and the prosumers are considered as self-interest agents. The current state-of-the-art Mathematical Programming with Equilibrium Constraints (MPEC) and Mixed-Integer Programming (MIP) based approaches to solve bilevel optimization problems are not satisfactory for real-time applications. The computation time for such approaches grows exponentially as the number of prosumers and decision variables increase. This paper presents a convex optimization problem which can capture a subset of the set of global optima of the bilevel problem as its optimal solution.