Researchers from the School of Electrical Engineering at Wuhan University, including Wenhao Gao, Yongheng Wang, Wei Chen, and Xinwei Shen, have developed a new approach to optimize the planning of coastal urban distribution networks that incorporate renewable energy sources, electric vehicle charging stations, and energy storage systems.
The team’s work focuses on addressing the challenges posed by the increasing integration of renewable energy resources, such as tidal and photovoltaic power, and the growing deployment of electric vehicle charging infrastructure. Their research presents a tri-layer distributionally robust optimization framework designed to jointly optimize the placement of photovoltaic-storage-electric vehicle stations (PSES) and the configuration of coastal distribution networks (DN). This approach aims to minimize total investment and operational costs while addressing uncertainties related to power load, PV generation, and EV charging demands.
At the upper layer of the framework, optimal decisions are made regarding the siting of PSES and network topology. The middle layer tackles worst-case uncertainty scenarios through an optimal power flow model, utilizing ambiguity sets to capture correlated uncertainties. To handle non-convexities introduced by binary variables for energy storage systems, the researchers propose a novel relaxation approach, which they rigorously prove to be exact. The lower layer focuses on operational decisions, including electricity procurement and carbon emissions, driven by dynamic pricing influenced by tidal energy fluctuations.
The researchers developed an inexact column-and-constraint generation (i-CCG) algorithm to efficiently solve the complex optimization problem. Numerical results from a realistic 47-node coastal DN in China demonstrate that the proposed method effectively reduces costs and ensures robust, low-carbon planning under substantial uncertainties.
This research, published in the journal Applied Energy, offers practical applications for the energy sector by providing a robust planning framework that can enhance the integration of renewable energy sources and electric vehicle charging infrastructure in coastal urban distribution networks. The proposed approach can help energy companies and planners make informed decisions that minimize costs and reduce carbon emissions, contributing to a more sustainable energy future.
Source: Gao, W., Wang, Y., Chen, W., & Shen, X. (2023). Distributionally Robust Joint Planning of Coastal Distribution Network and PV-Storage-EV Stations. Applied Energy, 335, 120904.
This article is based on research available at arXiv.