## 1 Introduction  
Partial discharge (PD) measurement is a fundamental tool for quality evaluation and diagnostic assessment of insulation systems [1, 2]. Indeed, PD is, at the same time, one of the most harmful accelerated degradation causes for organic insulation and a fundamental diagnostic property for condition maintenance planning [3, 4, 5, 6].  
Since incoming electrical asset technologies are going to subject insulation systems to extreme stress conditions (particularly due to the progressive replacement of conventional energy transformation with power electronics with higher voltage [7] and specific power [8, 9]), care shall be taken to keep under control the acceleration of both intrinsic and extrinsic aging mechanisms [10, 11]. As partially discussed in [4] and generally defined in [10], intrinsic aging is related to the effect of maximum stress (e.g., peak electric field) on bulk degradation processes. It is modeled by resorting to typical laws such as the inverse power model for electrical and mechanical stress and the Arrhenius model for thermal stress [4, 12, 13]. Extrinsic aging has to do with local phenomena, such as hot spots and partial discharges. Even if local, this aging can be the prevailing cause of premature failure because, in general, an insulation system should be seen, from a reliability point of view, as a parallel of infinite microcomponents: failure of one of those causes the failure of the whole system (indeed, the extreme values of failure distributions, such as the Weibull one, stem from this reasoning [14]).  
Based on the common consideration that PD is the prevailing cause of premature electrical failure of insulation systems, care should be taken in the design of insulation to ensure that PD is not incepted both at time zero (quality control and commissioning) and during the whole specified life. A fundamental tool should then be made available to insulation designers, that is, partial discharge inception models. A simple, deterministic, but experimentally proven approach to PD inception modeling was provided by [PERSON] [15], and a generalization of his work to cover heuristically both PD inception in internal defects and surface discharges has been recently presented in [16]. Validation of these models is of utmost importance, whether their broad use at the design stage of an insulation system is foreseen.  
This paper deals with a key potential issue, that is, the influence of electrode shape and the relevant electric field calculation on discharge model application and on PD phenomenology, i.e., PD source typology identification. The main purpose is to show, through field simulations, the PD inception model, and experimental tests, how inaccurate modeling of the electrode geometry could lead to wrong/misleading predictions in terms of the PD inception threshold and PD identification. In Section 2, PD inception model results and electric field simulations applied to the test object chosen for this assessment are presented. This section also recalls the \"three-leg\" approach, i.e., a methodology exploited in this paper, which has been recently proposed to achieve PD-free design of insulation systems. Section 3 shows how geometrical variations of electrode shape impact the inception field and partial discharge inception voltage (PDIV) estimation. This is made by considering two typologies of electrodes, namely electrode A and electrode B, triggering PD on the same dielectric specimens. Eventually, Section 4 validates the forecasts made in Section 3 by means of experimental tests using Electrodes A and B.