The hosting capacity concept was initially referred only to the capacity of a given network to integrate distributed generation without jeopardising the reliability and security obtained so far. Nowadays, this concept can be extended to the capacity of integrating Electric Vehicles’ (EVs) charging stations that, if operated without any coordination, can negatively affect the operation of the distribution network. Following the most recent scenarios of the energy transition, which requires a drastic reduction of pollutant emissions from the transport sector, the electricity demand for transport is expected to increase by 11% from 2017 in the EU-27. Six million EVs are expected to circulate in Italy. Charging infrastructures, spread on the distribution network, at both MV and LV level (through fast and slow charging infrastructures, respectively), will be fundamental to foster the deployment of EVs. The latter kind of infrastructure will be the majority because EV drivers typically prefer to install their own charging stations in residential premises. Residential charging infrastructures are mostly single-phase and connected to the LV network. Thus, the impact of EV charging will be mainly on this side of the distribution network. The growth of energy demand by EV charging could cause transformers’ overloading, cables’ thermal stress, undervoltage, and imbalances. In Literature, many methods for evaluating the impact of EVs on the distribution networks have been proposed. They mainly differ for the used approach, which does not consider uncertainties (i.e., deterministic/worst case approach) or considers only some of them or, also, all of them (i.e., probabilistic approaches). Since the great variability in EVs and charging stations specifications, habits of the EV drivers, network data and load and generation profiles, a comprehensive evaluation and generalizable results can arise from a suitable approach only, able to account for all these sources of uncertainties. This paper is intended to compare different methods used for assessing the EV hosting capacity of LV networks by considering the relevant aforementioned uncertainties with the aim of evaluating the risk of technical constraint violations associated with a given penetration level of EVs. A probabilistic network calculation, based on the stochastic representation of the customers’ behaviour considering the uncertainties associated to renewable generation, load demand, EV drivers’ habits, etc., is essential for the risk assessment. DSOs could use such a risk-oriented calculation approach to become more confident in the EV hosting capacity forecasting of their networks. Moreover, the integration of the aforementioned evaluation method with an advanced distribution planning tool, could enable the DSOs to find planning solutions characterised by a risk level set below a predefined acceptable level, instead of looking for zero-risk solutions.
Risk-oriented assessment of LV distribution network Hosting Capacity for Electric Vehicles.
Conti, S.;
2024-01-01
Abstract
The hosting capacity concept was initially referred only to the capacity of a given network to integrate distributed generation without jeopardising the reliability and security obtained so far. Nowadays, this concept can be extended to the capacity of integrating Electric Vehicles’ (EVs) charging stations that, if operated without any coordination, can negatively affect the operation of the distribution network. Following the most recent scenarios of the energy transition, which requires a drastic reduction of pollutant emissions from the transport sector, the electricity demand for transport is expected to increase by 11% from 2017 in the EU-27. Six million EVs are expected to circulate in Italy. Charging infrastructures, spread on the distribution network, at both MV and LV level (through fast and slow charging infrastructures, respectively), will be fundamental to foster the deployment of EVs. The latter kind of infrastructure will be the majority because EV drivers typically prefer to install their own charging stations in residential premises. Residential charging infrastructures are mostly single-phase and connected to the LV network. Thus, the impact of EV charging will be mainly on this side of the distribution network. The growth of energy demand by EV charging could cause transformers’ overloading, cables’ thermal stress, undervoltage, and imbalances. In Literature, many methods for evaluating the impact of EVs on the distribution networks have been proposed. They mainly differ for the used approach, which does not consider uncertainties (i.e., deterministic/worst case approach) or considers only some of them or, also, all of them (i.e., probabilistic approaches). Since the great variability in EVs and charging stations specifications, habits of the EV drivers, network data and load and generation profiles, a comprehensive evaluation and generalizable results can arise from a suitable approach only, able to account for all these sources of uncertainties. This paper is intended to compare different methods used for assessing the EV hosting capacity of LV networks by considering the relevant aforementioned uncertainties with the aim of evaluating the risk of technical constraint violations associated with a given penetration level of EVs. A probabilistic network calculation, based on the stochastic representation of the customers’ behaviour considering the uncertainties associated to renewable generation, load demand, EV drivers’ habits, etc., is essential for the risk assessment. DSOs could use such a risk-oriented calculation approach to become more confident in the EV hosting capacity forecasting of their networks. Moreover, the integration of the aforementioned evaluation method with an advanced distribution planning tool, could enable the DSOs to find planning solutions characterised by a risk level set below a predefined acceptable level, instead of looking for zero-risk solutions.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
