Robust optimization of renewable-based multi -energy micro-grid integrated with flexible energy conversion and storage devices

This paper presents a new model for optimal scheduling of renewable-based multi-energy microgrid (MEM) systems incorporated with emerging high-efficient technologies such as electric vehicle (EVs) parking lots, power-to-gas (P2G) facility, and demand response programs. The proposed MEM is equipped with wind energy, multi-carrier energy storage technologies, boiler, combined heat and power unit, P2G, EVs, and demand response with the aim of total operational cost minimization. Meanwhile, the system operator can participate in three electricity, heat, and gas market to meet local demands as well as achieve desired profits through energy exchanges. The proposed MEM is exposed to high-level uncertainties due to wind energy, demand, the initial and final state of charge of EVs, arrival and departure times of EVs, as well as power price. A hybrid robust/stochastic framework is used to capture all random variables and distinguishes between the level of conservatism in the decision-making procedure. The electricity price uncertainty is addressed by a robust approach, while a stochastic framework models other uncertainties of the system. Simulations are provided for different cases, which results revealed that the integrated scheduling of MEM in the presence of emerging technologies, incorporated with vehicle-to-grid (V2G) capability, reduces the total operational cost by 14.2 %.

Automated summary

This paper introduces a new model for optimizing the scheduling of renewable-based multi-energy microgrid systems, incorporating emerging high-efficient technologies to reduce total operational costs. The model allows participation in three energy markets for profit maximization and uses a hybrid robust/stochastic framework to address uncertainties. Simulations show that integrated scheduling of multi-energy microgrids with emerging technologies and V2G capability can reduce total operational costs by 14.2%.