Optimal Grid – Distributed Energy Resource Coordination: Distribution Locational Marginal Costs and Hierarchical Decomposition

We consider radial distribution networks hosting Distributed Energy Resources (DERs), including Solar Photovoltaic (PV) and storage-like loads, such as Electric Vehicles (EVs). We employ short-run dynamic Distribution Locational Marginal Costs (DLMCs) of real and reactive power to co-optimize distribution network and DER schedules. Striking a balance between centralized control and distributed self-dispatch, we present a novel hierarchical decomposition approach that is based on centralized AC Optimal Power Flow (OPF) interacting with DER self-dispatch that adapts to real and reactive power DLMCs. The proposed approach is designed to be highly scalable for massive DER Grid integration with high model fidelity incorporating rigorous network component dynamics and costs and reflecting them in DLMCs. We illustrate the use of an Enhanced AC OPF to discover spatiotemporally varying DLMCs enabling optimal Grid-DER coordination incorporating congestion and asset (transformer) degradation. We employ an actual distribution feeder to exemplify the use of DLMCs as financial incentives conveying sufficient information to optimize Distribution Network and DER (PV and EV) operation, and we discuss the applicability and tractability of the proposed approach, while modeling the full complexity of spatiotemporal DER capabilities and preferences.

I. Introduction

With Distributed Energy Resources (DERs), including Solar Photovoltaic (PV) and storage-like loads such as Electric Vehicles (EVs) with Volt/VAR capabilities, emerging as a major user of distribution grid infrastructure, the grid is becoming increasingly active, distributed, dynamic, and challenging to plan and operate [1]. As such, DERs are bound to have a profound impact on the adequacy of T& D assets, efficient grid operation, reliability, and security of supply, and hence their scheduling will be crucial. We argue that optimal DER scheduling depends on dynamic Distribution Locational Marginal Costs (DLMCs) [2], [3], [4], [5], [6], whose accurate estimation is expected to bring about fundamental changes in distribution planning, operation, and eventually power markets.