This paper presents an effective Energy Management System (EMS) that allows Microgrids and polynegative plants to estimate the possible incomes deriving from the participation to the Ancillary Service Market (ASM) and Day Ahead Market (DAM). Since the electricity market requests strongly depends on real-time contingencies, and hence on the Transmission System Operator (TSO) requirements, a statistically based method is implemented. Specifically, the optimization is split into two steps. In the first step, the optimal power dispatch of the involved units is computed, and the possible DAM and proposals are identified. Then, a Monte Carlo approach is implemented to extract TSO decisions based on a user selected success percentage. Hence, for every extraction, the second step dispatches the units and computes the costs/revenues. The outcome is a Probability Density Function (PDF) of expenditure/incomes, whose analysis enables to evaluate the incomes deriving from ASM participation. To assess the effectiveness of the EMS implemented, two tests are performed on a real microgrid. Precisely, the comparison of the optimization outcomes when ASM participation is enabled or not is performed. The obtained results highlight that ASM participation definitely increases the incomes with respect to the case in which ASMs are not allowed.
An Effective Energy Management System to Assess the Convenience of Participating in Electricity Markets
Martino, M.;Invernizzi, M.
2025-01-01
Abstract
This paper presents an effective Energy Management System (EMS) that allows Microgrids and polynegative plants to estimate the possible incomes deriving from the participation to the Ancillary Service Market (ASM) and Day Ahead Market (DAM). Since the electricity market requests strongly depends on real-time contingencies, and hence on the Transmission System Operator (TSO) requirements, a statistically based method is implemented. Specifically, the optimization is split into two steps. In the first step, the optimal power dispatch of the involved units is computed, and the possible DAM and proposals are identified. Then, a Monte Carlo approach is implemented to extract TSO decisions based on a user selected success percentage. Hence, for every extraction, the second step dispatches the units and computes the costs/revenues. The outcome is a Probability Density Function (PDF) of expenditure/incomes, whose analysis enables to evaluate the incomes deriving from ASM participation. To assess the effectiveness of the EMS implemented, two tests are performed on a real microgrid. Precisely, the comparison of the optimization outcomes when ASM participation is enabled or not is performed. The obtained results highlight that ASM participation definitely increases the incomes with respect to the case in which ASMs are not allowed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.



