We consider the problem of coordinating multiple Distributed Energy Resources (DERs) so as to supply energy to the grid while minimizing its variability around a reference profile that must also be optimized. We focus on the case when each DER is equipped with solar panels and a battery storage device, and jointly design the disturbance compensation strategies for charging and discharging the batteries on a one-day time horizon. To this purpose, we linearly parameterize the strategies and search for a solution minimizing the fluctuations of the energy exchange with the grid in steady-state, with a bound on their extent that holds in probability given the stochastic nature of the solar energy. Interestingly, the probability measure of the resulting chance-constrained optimization problem depends on the parameters of the disturbance compensation strategies, which makes the application of the scenario approach not standard. The proposed scenario-based solution is feasible for the original steady-state chance-constrained optimization problem and proves effective in numerical simulations.
A steady-state optimal coordination strategy for DERs systems with guaranteed probabilistic performance
Falsone, Alessandro;Prandini, Maria
2023-01-01
Abstract
We consider the problem of coordinating multiple Distributed Energy Resources (DERs) so as to supply energy to the grid while minimizing its variability around a reference profile that must also be optimized. We focus on the case when each DER is equipped with solar panels and a battery storage device, and jointly design the disturbance compensation strategies for charging and discharging the batteries on a one-day time horizon. To this purpose, we linearly parameterize the strategies and search for a solution minimizing the fluctuations of the energy exchange with the grid in steady-state, with a bound on their extent that holds in probability given the stochastic nature of the solar energy. Interestingly, the probability measure of the resulting chance-constrained optimization problem depends on the parameters of the disturbance compensation strategies, which makes the application of the scenario approach not standard. The proposed scenario-based solution is feasible for the original steady-state chance-constrained optimization problem and proves effective in numerical simulations.File | Dimensione | Formato | |
---|---|---|---|
DERs_OneShot_pub.pdf
accesso aperto
:
Publisher’s version
Dimensione
1.04 MB
Formato
Adobe PDF
|
1.04 MB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.