Optimal capacity configuration model of power-to-gas equipment in wind-solar sustainable energy systems based on a novel spatiotemporal clustering algorithm: A pathway towards sustainable development. (December 2022)

• Record Type: Journal Article
• Authors: Lv, Shuaishuai; Wang, Hui; Meng, Xiangping; Yang, Chengdong; Wang, Mingyue
• Is Part Of: Renewable energy. Volume 201(2022)Part 1
• Page Start: 240
• Page End: 255
• Publication Date: 2022-12
• Subjects: Wind-solar sustainable energy system -- Multi-source-load spatiotemporal clustering algorithm -- Scenario reduction -- Typical day -- Power-to-gas capacity configuration; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2022.10.079
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: For wind-solar sustainable energy systems with a large amount of abandoned wind and solar energy and carbon dioxide emissions, a power-to-gas equipment can be introduced to synthesize methane together, which is an effective way to alleviate the greenhouse effect, improve the utilization rate of new energy, and promote sustainable development. Focusing on how to perform the optimal capacity configuration of the newly introduced power-to-gas equipment more accurately and simply, this paper make progress through a more similar scenario reduction and a more accurate power-to-gas capacity configuration model. First, in view of the problem that the existing scenario reduction methods are difficult to take into account the coherent temporal characteristics and spatial amplitude characteristics, a novel multi-source-load double-layer spatiotemporal clustering algorithm is proposed. Second, in view of the problem that the power-to-gas equipment can only capture the actual carbon dioxide, a more comprehensive model considering the coupling relationship of multi-energy flows such as electricity-natural gas-hydrogen-oxygen-actual carbon dioxide-virtual carbon dioxide is proposed. The example analysis shows that the proposed strategies can reduce the error rate of the power-to-gas capacity configuration with a similar calculation amount. Highlights: Aim to reduce the error rate of power-to-gas capacity configuration. Modeling novel multi-source-load two-layer spatio-temporal clustering algorithm. Exploit the potential of carbon emission and electric hydrogen production. Using typical daily scenario to simplify the calculation of capacity configuration. Distinguish between actual and virtual carbon dioxide to refine constraints.