Work

Medium-to-Long-Term Electricity Load Forecasting for Newly Constructed Canals Based on Navigation Traffic Volume Cascade Mapping

Year: 2025

Type: article

Abstract: Addressing the data scarcity and complex consumption characteristics in mid-to-long-term electricity load forecasting for new canals, this study proposes a novel model based on navigation traffic volume cascade mapping. A multidimensional feature matrix integrating economic indicators, meteorological factors, and facility constraints is established, with canal similarity quantified via integrated constraint optimization weighting to derive multisource fusion weights. These enable freight volume prediction through feature migration using comprehensive transportation sharing. The “freight volume–lockage volume–electricity consumption” cascade then applies tonnage-based mapping to capture vessel evolution trends, generating lockage volume forecasts. Core consumption components are predicted through a mechanistic-data hybrid model for ship lock operations and a three-layer “Node–Behavior–Energy” framework for shore power system characterization, integrated with auxiliary consumption to produce the operational mid-to-long-term load forecast. Case analysis of the Pinglu Canal (2027–2050) reveals an overall “rapid-growth-then-stabilization” electricity consumption trend, where shore power’s proportion surges from 24.1% (2027) to 67.8% (2050)—confirming its decarbonization centrality—while lock system consumption declines from 28.6% to 17.2% reflecting efficiency gains from vessel upsizing and strict adherence to navigation intensity constraints.The model provides foundations for green canal energy deployment, proving essential for establishing eco-friendly waterborne logistics.

Source: Sustainability

DOI: 10.3390/su18010109

Authors: Jing Fu, Li Gong, Xiang Li, Biyun Chen, Min Lai, Ni Wang

Institution: Guangxi University

Language: English

Topic: Energy Load and Power Forecasting

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Climate action, Affordable and clean energy, Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $2,896