Robust multi-objective short-term planning of a completely renewable multi-carrier system incorporating the Internet of Things application and green hydrogen

This paper presents a mixed-integer linear model incorporating profit and pollution functions to optimize the short-term planning of a renewable multi-carrier system connected to integrated parking lots for electric and hydrogen vehicles and smart homes. Since the required hydrogen must be supplied locally, a green power-to-hydrogen infrastructure, comprising electrolyzers and storage tanks, is established to convert renewable energy into hydrogen. This study emphasizes consumer participation in energy management and employs the Internet of Things concept to facilitate two-way communication between the generation and demand sides, enabling effective energy management. A p-robust approach is also applied to control robustness against input data uncertainties. Simulations indicate that the risk-averse strategy leads to conservative decisions, enhancing robustness and reducing expected profit and risk in profit by 8.49 % and 100 %, respectively. Parking lots of electric vehicles serve as a bulk energy storage system for the local grid, and smart homes can be managed efficiently to improve operational flexibility and handle fluctuations. A sensitivity analysis of critical parameters validates the influence of initial conditions and the necessity of restrictive policies, including incentives and penalties, to achieve optimal technical, economic, and environmental outcomes.