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Energy and reserve procurement in integrated electricity and heating system: A high-dimensional covariance matrix approach based on stochastic differential equations.

Authors :
Deng, Lirong
Fu, Yang
Guo, Qinglai
Li, Zhenkun
Xue, Yixun
Zhang, Zhiquan
Source :
Energy. Sep2024, Vol. 304, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

The integration of stochastic renewable energy sources into energy systems presents challenges due to flexibility insufficiency and uncertainty modeling inaccuracy. To address these challenges, this paper explores a high-dimensional covariance matrix approach based on stochastic differential equations (SDEs) for energy and reserve co-dispatch in integrated electricity and heating systems. By capturing the long-term correlation of wind power forecast errors, the SDE model simultaneously models point forecasts and high-dimensional positive-definite covariance matrices, resulting in a compact uncertainty set. To ensure computational efficiency, we employ duality theory to transform the stochastic co-dispatch problem with the high-dimensional uncertainty set into deterministic convex programming. Additionally, a virtual heat storage model is introduced for the district heating network, leveraging the thermal inertia of the network to enhance reserve capacity. Simulations validate the calibration and sharpness of the proposed high-dimensional uncertainty set. The results demonstrate that co-dispatch using the SDE-based uncertainty set reduces operational costs by 4.9% compared to a set that does not consider the long-term correlation of wind power, under a 95% coverage rate. Moreover, the storage capabilities of district heating pipelines and smart buildings provide cost-free reserves, saving the operational costs of the two test systems by 2.8% and 1.3%, respectively. [Display omitted] • Considering the long-term correlation of forecast errors in renewable energy is crucial in uncertainty modeling. • A high-dimensional uncertainty set is constructed based on stochastic differential equations. • Stochastic energy and reserve co-dispatch with the high-dimensional set is transformed into a convex program. • A virtual heat storage model of the heating pipeline is proposed to enhance reserve capacity. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03605442
Volume :
304
Database :
Academic Search Index
Journal :
Energy
Publication Type :
Academic Journal
Accession number :
178335857
Full Text :
https://doi.org/10.1016/j.energy.2024.132042