Leveraging heat accumulation of district heating network to improve performances of integrated energy system under source-load uncertainties. (1st August 2022)

• Record Type: Journal Article
• Authors: Wang, Jiangjiang; Huo, Shuojie; Yan, Rujing; Cui, Zhiheng
• Is Part Of: Energy. Volume 252(2022)
• Publication Date: 2022-08-01
• Subjects: Integrated energy system (IES) -- District heating network -- Heat accumulation -- Stochastic optimization -- Wasserstein distance; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2022.124002
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: The multiple uncertainties in renewable energy and loads and the thermoelectric coupling characteristic of the integrated energy system (IES) restrict the accommodation of renewable energy. The IES contains massive pipelines in its district heating network, which signifies the heat storage potential. This paper incorporates the dynamic performance of the district heating network into the multi-scenario optimization model to improve IES's operational performance. Herein, the graph theory and Kirchhoff law are employed to construct the dynamic model of district heating network from the single pipeline and network viewpoints, which characterizes the thermal accumulation performance. The stochastic scenarios are generated by combining Latin hypercube sampling for the initial scenarios and scenario curtailment 0–1 algorithm based on Wasserstein probability distance for the curtailment scenarios to capture the uncertainties. Then, a stochastic multi-scenario optimization method is proposed, which is implemented into a case study to analyze the influences of critical parameters and the performance improvement resulted from the network thermal accumulation. The results show that the scenario curtailment 0–1 algorithm can obtain stable and repeatable scenarios. Considering the heat accumulation characteristics of the district heating network can improve the economic performance by 2.41% and wind energy accommodation by 5.51%. Highlights: A dynamic model of the district heating network is built. An optimization of integrating network heat storage under uncertainties is proposed. The scenario curtailment 0–1 algorithm based on Wasserstein distance is established. The impact of network thermal storage on system performances is analyzed. The economic performance and wind power consumption are improved by 2.41% and 5.51%.