This work presents a Mixed Integer Linear Programming formulation to optimize the design of microgrids and aggregated energy systems, including all the required constraints to guarantee N-1 reliability. In comparison to previous studies, the proposed model accounts for not only the optimal redundancy of generators but also the necessary power reserves (spinning and upward) during the start-up period of spare generators, considering also potential fluctuations in renewable energy production and electric demand. Previous studies have not taken these reserve requirements into account, leading to overoptimistic cost estimates. The methodology is applied to the optimization of two real-world off-grid case studies of industrial relevance: (i) a remote natural gas liquefaction plant and (ii) an off-grid airport. The proposed N-1 reliability approach yields optimal solutions with a lower renewable capacity compared to classic methods. Additionally, it requires a larger storage size as the battery is not only operated jointly with renewables, but it is also used as a power bank to provide spinning and upward reserves. The increase in total annual costs due to the reliability requirements is estimated at 2.8 % and 10.4 % for the two case studies, resulting from higher investment and operating costs. Compared to conventional N-1 reliability approaches, which do not include reserves for the start-up time of spare generators, the cost increase ranges from 2 to 5 %.
An effective MILP model for the optimal design of microgrids with high-reliability requirements
Zelaschi, Andrea;Martelli, Emanuele
2025-01-01
Abstract
This work presents a Mixed Integer Linear Programming formulation to optimize the design of microgrids and aggregated energy systems, including all the required constraints to guarantee N-1 reliability. In comparison to previous studies, the proposed model accounts for not only the optimal redundancy of generators but also the necessary power reserves (spinning and upward) during the start-up period of spare generators, considering also potential fluctuations in renewable energy production and electric demand. Previous studies have not taken these reserve requirements into account, leading to overoptimistic cost estimates. The methodology is applied to the optimization of two real-world off-grid case studies of industrial relevance: (i) a remote natural gas liquefaction plant and (ii) an off-grid airport. The proposed N-1 reliability approach yields optimal solutions with a lower renewable capacity compared to classic methods. Additionally, it requires a larger storage size as the battery is not only operated jointly with renewables, but it is also used as a power bank to provide spinning and upward reserves. The increase in total annual costs due to the reliability requirements is estimated at 2.8 % and 10.4 % for the two case studies, resulting from higher investment and operating costs. Compared to conventional N-1 reliability approaches, which do not include reserves for the start-up time of spare generators, the cost increase ranges from 2 to 5 %.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


