A Mixed Epistemic-Aleatory Stochastic Framework for the Optimal Operation of Hybrid Fuel Stations

Abstract

The fast development of technologies in the smart grids provides new opportunities such as co-optimization of multi-energy systems. One of the new concepts that can utilize multiple energy sources is a hybrid fuel station (HFS). For instance, an HFS can benefit from energy hubs, renewable energies, and natural gas sources to supply electric vehicles along with natural gas vehicles. However, the optimal operation of an HFS deals with uncertainties from different sources that do not have similar natures. Some may lack in term of historical data, and some may have very random and unpredictable behavior. In this study, we present a stochastic mathematical framework to address both types of these uncertainties according to the innate nature of each uncertain variable, namely: epistemic uncertainty variables (EUVs) and aleatory uncertainty variables (AUVs). Also, the imprecise probability approach is introduced for EUVs utilizing the copula theory in the process, and a scenario-based approach combining Monte Carlo simulation with Latin Hypercube sampling is applied for AUVs. The proposed framework is employed to address the daily operation of a novel HFS, leading to a two-stage mixed-integer linear programming problem. The proposed approach and its applicability are verified using various numerical simulations.

Optimal sizing of hybrid renewable energy systems by considering power sharing and electric vehicles

“…However, they tend to experience a number of issues. One major problem is the uncertainty of power generation due to the variable nature of climatic conditions 43‐46 . As a result, this tends to reduce system reliability and efficiency.…”

“…One major problem is the uncertainty of power generation due to the variable nature of climatic conditions. [43][44][45][46] As a result, this tends to reduce system reliability and efficiency. Therefore, cost and reliability are important factors to be considered for designing effective renewable hybrid systems.…”

Optimal stochastic scheduling of plug-in electric vehicles as mobile energy storage systems for resilience enhancement of multi-agent multi-energy networked microgrids

“…In recent years, the resilience enhancement strategies have been studied in the literature, but the MESSs have not been investigated in a MAS with networked MEMGs. In [26,27], a stochastic nonlinear framework is presented for the optimal energy management of the unbalanced three-phase AC microgrids. Furthermore, the suggested model aims to provide resilient energy management solutions via contingency constraints.…”

Smart peer-to-peer and transactive energy sharing architecture considering incentive-based demand response programming under joint uncertainty and line outage contingency

“…In addition, after optimizing the revenue of prosumer, maximum utility function of consumer has been obtained considering game theory approach which fair willingness of participation is achieved via availability of real time price of upstream grid (UG). Therefore, response of consumer to the behavior of UG's price has been inserted into the methodology as the willingness factor [28][29][30]. In other work [6], P2P potential of renewable energy-based market has been examined taking into account of economic feasibility of decisions.…”