an optimal interaction model of reconfigurable smart distribution system and parking lot operators

By leveraging the capabilities of internet of things (iot) technology in conjunction with the smart grid concept and cloud-based data sharing, distribution system operators (dsos) and parking lot operators (plos) can coordinate collaboratively to optimize techno-economic interactions. the integration of smart devices for data acquisition, monitoring, and control, along with cloud-based platforms for data storage, analysis, and collaboration, facilitates more efficient energy management, cost-effectiveness, and overall performance improvements. building on these technological advancements, this study examines the daily operational planning of a smart distribution system in collaboration with plos, utilizing the equilibrium optimizer (eo) algorithm. considering the potential of parking lots, the dso aims to optimize both economic objectives and load leveling goals simultaneously, benefiting from structural reconfiguration for additional technical and financial gains. the model effectively incorporates constraints related to the expected and reliable operation of parking lots, as well as the security and radiality of the distribution system. by analyzing various objective functions and perspectives, the technique for order of preference by similarity to ideal solution (topsis) method is used to determine the optimal state across all scenarios, achieving 60.3$, 5306.6 kw, and 716.8 kw for the first, second, and third objective functions, respectively. numerical studies and simulation validations are conducted to evaluate the proposed model’s performance, with results discussed in detail.