A probabilistic framework for the techno-economic assessment of smart energy hubs for electric vehicle charging

H. George-Williams, N. Wade and R.N. Carpenter

Renewable and Sustainable Energy Reviews, 2022, vol. 162, issue C

Abstract: Smart energy hubs (Smart Hubs) equipped with Vehicle-to-Grid (V2G) charging, photovoltaic (PV) energy generation, and hydrogen storage capabilities, are an emerging technology with potential to alleviate the impact of electric vehicles (EV) on the electricity grid. Their operation, however, is characterised by intermittent PV energy generation, as well as uncertainties in EV traffic and driver preference. These uncertainties, when combined with the need to maximise their financial return while guaranteeing driver satisfaction, yields a challenging decision-making problem. This paper presents a novel Monte-Carlo-based modelling and computational framework for simulating the operation of Smart Hubs — providing a means for a holistic assessment of their technical and financial viability. The framework utilises a compact and representative mathematical model, accounting for power losses, PV module degradation, variability in EV uptake, price inflation, driver preference, and diversity in charge points and EVs. It provides a comprehensive approach for dealing with uncertainties and dependencies in EV data while being built on an energy management algorithm that maximises revenue generation, ensures driver satisfaction, and preserves battery life. The energy management problem is formulated as a mixed-integer linear programming problem constituting a business case that includes an adequate V2G reward model for drivers. To demonstrate its applicability, the framework was used to assess the financial viability of a fleet management site, for various caps on vehicle stay at the site. From the assessment, controlled charging was found to be more financially rewarding in all cases, yielding between 1.7% and 3.1% more revenue than uncontrolled charging. The self-consumption of the site was found to be nearly 100%, due mainly to local load shifting and dispatchable hydrogen generation. V2G injection was, however, negligible — suggesting its unattractiveness for sites that do not participate in the demand side response market. Overall, the numerical results obtained validate the applicability of the proposed framework as a decision-support tool in the sustainable design and operation of Smart Hubs for EV charging.

Keywords: Electric vehicle; Smart charging; Hydrogen storage; Solar microgrid; Monte Carlo simulation; Vehicle-to-Grid (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1364032122002969
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:rensus:v:162:y:2022:i:c:s1364032122002969

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/600126/bibliographic
http://www.elsevier. ... 600126/bibliographic

DOI: 10.1016/j.rser.2022.112386

Access Statistics for this article

Renewable and Sustainable Energy Reviews is currently edited by L. Kazmerski

More articles in Renewable and Sustainable Energy Reviews from Elsevier
Bibliographic data for series maintained by Catherine Liu ().