A Low-Carbon and Economic Optimal Dispatching Strategy for Virtual Power Plants Considering the Aggregation of Diverse Flexible and Adjustable Resources with the Integration of Wind and Solar Power
Under the dual-carbon goals, with the rapid increase in the proportion of fluctuating power sources such as wind and solar energy, the regulatory capacity of traditional thermal power generation can no longer meet the demand for intra-day fluctuations. There is an urgent need to tap into the potential of flexible load-side regulatory resources. To this end, this paper proposes a low-carbon economic optimal dispatching strategy for virtual power plants (VPPs), considering the aggregation of diverse flexible and adjustable resources with the integration of wind and solar power. Firstly, the method establishes mathematical models by analyzing the dynamic response characteristics and flexibility regulation boundaries of adjustable resources such as photovoltaic (PV) systems, wind power, energy storage, charging piles, interruptible loads, and air conditioners. Subsequently, considering the aforementioned diverse adjustable resources and aggregating them into a VPP, a low-carbon economic optimal dispatching model for the VPP is constructed with the objective of minimizing the total system operating costs and carbon costs. To address the issue of slow convergence rates in solving high-dimensional state variable optimization problems with the traditional plant growth simulation algorithm, this paper proposes an improved plant growth simulation algorithm through elite selection strategies for growth points and multi-base point parallel optimization strategies. The improved algorithm is then utilized to solve the proposed low-carbon economic optimal dispatching model for the VPP, aggregating diverse adjustable resources. Simulations conducted on an actual VPP platform demonstrate that the proposed method can effectively coordinate diverse load-side adjustable resources and achieve economically low-carbon dispatching, providing theoretical support for the optimal aggregation of diverse flexible resources in new power systems.
Authors
- Q. Jane Wang (ORCID: https://orcid.org/0000-0003-3057-5094)
- Di Chen (ORCID: https://orcid.org/0000-0003-3109-4321)
- Xiaoqing Cao
- Li He (ORCID: https://orcid.org/0000-0003-2761-9404)
- Qingrui Yang
- Hongbo Zou (ORCID: https://orcid.org/0000-0002-5880-8163)
Institutions
- China Three Gorges University (CN)
- State Grid Corporation of China (China) (CN)
- Wuhan Municipal Engineering Design & Research Institute (CN)
- Shanghai Electric (China) (CN)
Publication Details
- Journal
- Processes
- Published
- 2025-07-24
- DOI
- https://doi.org/10.3390/pr13082361
- Citations
- 1
- Primary Topic
- Smart Grid Energy Management
- Type
- article
- Field-Weighted Citation Impact
- 0.73