Distribution Network Marginal Costs: Enhanced AC OPF Including Transformer Degradation

Abstract

This paper considers the day-ahead operational planning problem of radial distribution networks hosting Distributed Energy Resources, such as Solar Photovoltaic (PV) and Electric Vehicles (EVs). We present an enhanced AC Optimal Power Flow (OPF) model that estimates dynamic Distribution nodal Location Marginal Costs (DLMCs) encompassing transformer degradation as a short-run network variable cost. We decompose real/reactive power DLMCs into additive marginal cost components representing respectively the costs of real/reactive power transactions at the T\&D interface, real/reactive power marginal losses, voltage and ampacity congestion, and transformer degradation, capturing intertemporal coupling. Decomposition is useful in identifying sources of marginal costs and facilitating the employment of distributed AC OPF algorithms. DLMCs convey sufficient information to represent the benefit of shifting real/reactive power across time and achieve optimal Distribution Network and DER operation. We present and analyze actual distribution feeder based numerical results involving a wealth of future EV/PV adoption scenarios and illustrate the superiority of our approach relative to reasonable conventional scheduling alternatives. Overwhelming evidence from extensive numerical results supports the significant benefits of internalizing short-run marginal asset - primarily transformer - degradation.