Planning of the Lausanne low voltage grid via probabilistic load flow analysis

Planning the low voltage power grid to accommodate the hosting of Heat Pumps (HP), Electric Vehicle Charging Stations (EVCS), and PhotoVoltaic (PV) production poses significant challenges for Distribution System Operators (DSOs). These new loads and power generation assets are altering the dynamics of electricity consumption and generation requiring a re-evaluation of traditional grid planning approaches. In this work we propose a planning framework to model the impact of HP, EVCS, PV and base load on the low voltage grid and assess grid reinforcement strategies. Historical time series from Smart Meters (SMs) are used to create normalized power profiles for the different loads/producers. Then, a Probabilistic Load Flow (PLF) is solved based on Monte Carlo resampling of the established profiles. The PLF enables the verification of nodal voltage violation risks and line congestions. This base-case is then extended to consider future expected/planned installations through scenarios of HP, EVCS and PV adoption. The optimal grid reinforcement strategies are then determined by following a decision tree, guided by the results of the simulation, while considering operational, capital, and labor costs. The planning framework is applied to several feeders of the low voltage grid in Lausanne, Switzerland and the results show that the framework can accurately represent grid constraints and suggest optimal reinforcement strategies.