The integration of energy storage systems (ESSs) co-located with distributed PV units in LV networks allows increasing self-consumption of energy and supporting DSO for grid management. In fact, ESSs may help the distribution network in reducing the mismatch between demand and PV generation making such power source dispatchable. Here, we perform a Monte Carlo analysis to assess the impact that two different control strategies have on the grid: a classical consumer strategy and a control that allows providing an ancillary service to DSO for improving voltage quality. In the last, we propose a control strategy based on the limitation of the charging/discharging periods of the ESSs in two time periods. We implement Monte Carlo simulations to assess the charge/discharge time intervals of ESSs. Unbalanced power flow simulations take into account the variation of power demand, penetration and locations of PV/ESSs for a summer day on a LV Italian network. © 2016 IEEE.

Assessing the performances of residential ESSs control by means of a Monte Carlo analysis

Graditi, G.
2017

Abstract

The integration of energy storage systems (ESSs) co-located with distributed PV units in LV networks allows increasing self-consumption of energy and supporting DSO for grid management. In fact, ESSs may help the distribution network in reducing the mismatch between demand and PV generation making such power source dispatchable. Here, we perform a Monte Carlo analysis to assess the impact that two different control strategies have on the grid: a classical consumer strategy and a control that allows providing an ancillary service to DSO for improving voltage quality. In the last, we propose a control strategy based on the limitation of the charging/discharging periods of the ESSs in two time periods. We implement Monte Carlo simulations to assess the charge/discharge time intervals of ESSs. Unbalanced power flow simulations take into account the variation of power demand, penetration and locations of PV/ESSs for a summer day on a LV Italian network. © 2016 IEEE.
9781509033584
Storage systems;Monte Carlo analysis;LV network
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12079/3830
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