Optimal operation of active distribution networks hosting hybrid hydrogen‐electricity refuelling stations considering water demand under a stochastic‐IGDT approach

Author:

Pezhmani Yasin1,Oskouei Morteza Zare2ORCID,Rezaei Navid1ORCID,Mehrjerdi Hasan3

Affiliation:

1. Department of Electrical Engineering University of Kurdistan Sanandaj Iran

2. Faculty of Electrical Engineering Sahand University of Technology Tabriz Iran

3. Department of Electrical and Computer Engineering Royal Military College of Canada Kingston Canada

Abstract

AbstractThis paper deals with the real‐time optimal operation of active distribution networks (ADNs) hosting hybrid hydrogen‐electricity refuelling stations by benefiting from renewable energy sources (RESs), conversion facilities, and energy storage systems. The hybrid refuelling stations, which are controlled by ADN operator, supply electricity and hydrogen for electric vehicles (EVs) and hydrogen vehicles (HVs), respectively. In addition, the deployment of water equipment technologies in the ADNs, is considered by utilizing water well pumps in the hybrid stations to serve water demand. The principal aim is to minimize the expected operation cost, including the cost of purchasing power from the upstream grid and maintenance and operation costs of each hybrid refuelling station. Various technical and physical constraints are considered to ensure the reliable operation and realistic scheduling of ADNs in the presence of hybrid refuelling stations. This study employs a hybrid information gap decision theory (IGDT)‐stochastic approach to address the uncertain behaviour of wholesale market price, electricity demand of EVs in refuelling stations, RESs output power and nodal demand of ADN to reach a risk‐averse strategy. The developed approach is coded under GAMS software and the effectiveness of the approach is validated by testing on the modified IEEE 33‐bus test system.

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology,Control and Systems Engineering

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