energies Article A Probabilistic Conductor Size Selection Framework for Active Distribution Networks Lewis Waswa *, Munyaradzi Justice Chihota and Bernard Bekker   Citation: Waswa, L.; Chihota, M.J.; Bekker, B. A Probabilistic Conductor Size Selection Framework for Active Distribution Networks. Energies 2021, 14, 6387. https://doi.org/10.3390/ en14196387 Academic Editors: Pavlos S. Georgilakis and Habib M. Kammoun Received: 31 July 2021 Accepted: 20 September 2021 Published: 6 October 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). Department of Electrical & Electronic Engineering, Stellenbosch University, X1, Stellenbosch 7602, South Africa; justicechihota@sun.ac.za (M.J.C.); bbekker@sun.ac.za (B.B.) * Correspondence: waswa@sun.ac.za; Tel.: +27-21-808-3605 Abstract: With the increasing adoption of distributed energy resources (DERs) such as wind and solar photovoltaics (PV), many distribution networks have changed from passive to active. In turn, this has led to increased technical and operational challenges such as voltage issues and thermal loading in high DER penetration scenarios. These challenges have been further increased by the uncertainties arising from DER allocation. The implication of DER allocation uncertainty in the planning process is far-reaching as it affects critical planning processes, including conductor size selection (CSS). Most reported CSS methods in the literature do not include DER allocation uncertainty modeling as they are mostly deterministic and are set out as optimization problems. The methods, therefore, lack foresight on future loading conditions and cannot be used in a CSS process for feeders with high DER penetration. This paper proposes a novel input–process–output stochastic– probabilistic CSS framework for distribution feeders with DERs. The efficacy of the proposed framework is demonstrated using a low voltage feeder design case study with varying PV penetration targets, and the performance compared to deterministic–active-based estimates from our earlier work. The proposed CSS method is well-suited to the sizing of conductors for future loading conditions considering DER allocation uncertainty and will therefore be useful to planners working on new electrification projects. Keywords: distributed energy resources; distributed generation; hosting capacity; Monte Carlo simulation; after diversity maximum demand; probabilistic methods 1. Introduction The increasing adoption of distributed energy resources (DERs) such as solar pho- tovoltaics (PV), electric vehicles (EVs), and energy storage systems (ESS) on distribution networks has changed distribution network operations from passive to active [1]. The re- sulting networks are termed active distribution networks (ADNs) to denote the unique operating dynamics associated with bi-directional power flow and the integration of DERs. While DERs have several potential benefits to the power system, including climate change mitigation (for renewable energy-based DERs) and ancillary services provision, the in- creased connection of DERs is likely to increase the technical challenges that distribution network operators (DNOs) face [2]. The severity of the problems depends on various factors, including network electrical and loading properties as well as the location and capacity of the DERs. Reported chal- lenges in the literature include violation of voltage limits [3–6], transformer and conductor overloading, voltage unbalance, and protection issues [5,7,8]. These challenges have moti- vated research focused on determining the hosting capacity (HC) [9], which defines the maximum DER penetration that existing feeders can host while maintaining acceptable performance [3]. DNOs mostly use the HC as a basis for the formulation of regulations and standards for DER integration and control. However, this usually leads to the restrictive utilization of DERs due to the design characteristics of passive distribution systems. Energies 2021, 14, 6387. https://doi.org/10.3390/en14196387 https://www.mdpi.com/journal/energies