4.6 Article

Optimal Scheduling of Thermoelectric Coupling Energy System Considering Thermal Characteristics of DHN

期刊

SUSTAINABILITY
卷 14, 期 15, 页码 -

出版社

MDPI
DOI: 10.3390/su14159764

关键词

thermoelectric coupling energy system; optimal scheduling; renewable energy

资金

  1. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources [LAPS21007]
  2. Guangdong Basic and Applied Basic Research Foundation [2021A1515110778]
  3. Fundamental Research Funds for the Central Universities [N2104014]

向作者/读者索取更多资源

In this paper, a new approach is proposed to improve the flexibility of a thermoelectric coupling energy system by utilizing the district heating network, and a probabilistic model is established for the spinning reserves capacity related to confidence level. The study found that there is a linkage between system costs, flexibility, and thermal characteristic index, and the optimal result can achieve overall system balance.
In a thermoelectric coupling energy system, renewable energy is often curtailed by the uncertainty of the power generation. Besides, the integration of renewable energy is restricted by the inflexible operation of combined heat and power units due to the strong coupling relationship between power generation and heating supply, especially in winter. Utilization of the district heating network, a heat storage feature, is a cost-effective measure to improve the overall system operational flexibility. In this paper, a new heat characteristic index is proposed in a district heating system, which is applied to measure the impact of the flexibility of combined heat and power units' output. Furthermore, in order to increase the reliability of an electric power system, a probabilistic model of combined heat and power units' spinning reserves capacity related to confidence level K is established. What is more, the two indexes K and thermal characteristic index have a coupled relationship. In addition, for model solving methodology, the discretized step transformation and constant mass flow and variables temperature method is adopted to transform the non-linear system model into linear programming form. Case studies are carried out to show the linkage between system costs, K and thermal characteristic index. The optimal result can achieve balance among the system reliability, flexibility and economy.

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