Flexibility index for a distributed energy system design optimization

Flexibility plays a critical role in the design of distributed energy systems (DESs) as it encompasses various aspects related to demand, storage, and supply. To optimize the capacity configuration of DESs effectively, a novel flexibility index (FI) is proposed in this study. The FI is constructed based on the fuzzy best-worst method with considerations for economy, autonomy, energy efficiency, and environmental friendliness, aligning with the characteristics of the DES. Considering FI, particle swarm optimization is employed to determine the optimal design scheme for the DES. A case study involving a swimming pool in Changsha City is conducted to demonstrate the reliability of the proposed optimization scheme. Furthermore, a multi-objective optimization model based on non-dominated sorting genetic algorithm-II and technique of ordering preferences for ideal solution similarity algorithms is developed with different objective functions. The results show that the system optimized considering flexibility maintains better performance, with system flexibility, renewable energy penetration, and off-grid degree indices of 0.824, 0.780, and 0.757 respectively. In addition, the optimization of system configuration considering flexibility can dynamically respond to diverse energy demands, maintaining lower operation and maintenance costs ($11223.75 per year), and lower CO2 emissions (91800kgCO2 per year). The quantified FI presented in this study provides a user-friendly and reliable optimization index for the design of DESs.