Collaborative dispatch of hydro-wind-photovoltaic-hydrogen joint system based on ecological value accounting
Year: 2025
Type: article
Abstract: To achieve efficient utilization of renewable energy and address the issue of synergistic optimization between ecological benefits and economic benefits, this paper constructs an integrated framework that integrates ecological value accounting and system dispatch, and proposes a collaborative dispatch model for hydro-wind-photovoltaic-hydrogen joint system based on ecological value accounting. Firstly, for each energy entity, a respective ecological service value assessment model based on ecological flow protection or carbon emission reduction, a specific ecological footprint model using land occupation area and resource consumption as quantitative indicators, and a separate ecological carrying capacity assessment model integrating regional resources and environmental capacity are established, thereby providing a quantitative basis for the ecological constraints of each energy entity within the system. Secondly, a bi-level dispatch model for the joint system is constructed under ecological constraints, with the upper level aiming to maximize ecological benefits and the lower level focusing on maximizing power generation benefits. Finally, the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) is employed to solve the bi-level optimization problem, yielding the optimal Pareto solutions for the objective functions. The case study results show that, compared with the traditional weighted sum method for integrating economic and ecological objectives, the proposed framework increases the system’s comprehensive benefits by 10.83 % under short-term operation and 8.36 % under long-term operation, which is conducive to the coordinated development of low-carbon transformation and ecological protection of regional energy systems.
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,610
OpenAlex ID: W4416396384
