An Equality Set Projection Approach for TSO-DSO Coordination Dispatch

TL;DR

This paper introduces an accelerated non-iterative projection method for TSO-DSO coordinated dispatch, improving computational efficiency and scalability in high-dimensional feasible region projections for power system optimization.

Contribution

It proposes an accelerated equality set projection algorithm with regularization to efficiently handle high-dimensional feasible regions in TSO-DSO coordination dispatch.

Findings

Demonstrates improved computational efficiency in case studies

Effectively constructs high-dimensional feasible region projections

Outperforms traditional iterative methods in convergence speed

Abstract

Coordinated optimization dispatch (COD) of transmission system operator (TSO) and distribution system operator (DSO) can effectively ensure system security and efficiency under high-penetration distributed energy resource (DER) integration. Researches of large-scale COD problem can be categorized into iterative approaches that allow DSO to dispatch independently, and non-iterative methods based on projections of feasible regions (FR). However, the iterative methods suffer from low computational convergence and efficiency, while non-iterative methods struggle to solve equivalent projections with high-dimensional FR. To address these issues, this paper proposes a TSO-DSO coordinated dispatch approach based on an accelerated non-iterative Equality Set Projection (ESP) algorithm. First, ESP algorithm is employed to overcome the bottleneck of high-dimensional FR construction. Second, an regularization-based accelerated method is proposed to reduce computational burden when degeneracy occurs. Accelerated ESP algorithm constructs projection of FR via adjacent facet searching. Therefore, it is less sensitive to the increase of vertices and could efficiently construct the projection of high-dimensional FR. Case studies on a polyhedron dataset, IEEE 33-Bus System and T118D10 TSO-DSO system demonstrate the effectiveness and computational efficiency of the proposed COD approach.