Low Carbon Scheduling Optimization of Flexible Integrated Energy System Considering CVaR and Energy Efficiency

被引:12
|
作者
Liu, Hang [1 ]
Nie, Shilin [2 ]
机构
[1] Zhengzhou Univ Aeronaut, Sch Management Engn, Zhengzhou 450000, Henan, Peoples R China
[2] North China Elect Power Univ, Sch Econ & Management, Beijing 102206, Peoples R China
关键词
flexible integrated energy system; energy efficiency; CVaR-stochastic optimization; low carbon scheduling; scenario clustering; RENEWABLE ENERGY; MODEL; MANAGEMENT; MICROGRIDS; ALGORITHM; CAPACITY; STORAGE; GAS; CHP;
D O I
10.3390/su11195375
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
With the rapid transformation of energy structures, the Integrated Energy System (IES) has developed rapidly. It can meet the complementary needs of various energy sources such as cold, thermal, and electricity in industrial parks; can realize multi-energy complements and centralized energy supplies; and can further improve the use efficiency of energy. However, with the extensive access of renewable energy, the uncertainty and intermittentness of renewable energy power generation will greatly reduce the use efficiency of renewable energy and the supply flexibility of IES so as to increase the operational risk of the system operator. With the goal of minimum sum of the system-operating cost and the carbon-emission penalty cost, this paper analyzes the combined supply of cooling, heating, and power (CCHP) influence on system efficiency, compared with the traditional IES. The flexible modified IES realizes the decoupling of cooling, thermal, and electricity; enhances the flexibility of the IES in a variety of energy supply; at the same time, improves the use efficiency of multi-energy; and reasonably avoids the occurrence of energy loss and resource waste. With the aim of reducing the risk that the access of renewable energy may bring to the IES, this paper introduces the fuzzy c-mean-clustering comprehensive quality (FCM-CCQ) algorithm, which is a novel method superior to the general clustering method and performs cluster analysis on the output scenarios of wind power and photovoltaic. Meanwhile, conditional value at risk (CVaR) theory is added to control the system operation risk, which is rarely applied in the field of IES optimization. The model is simulated in a numerical example, and the results demonstrate that the availability and applicability of the presented model are verified. In addition, the carbon dioxide emission of the traditional operation mode; thermoelectric decoupling operation mode; and cooling, thermal, and electricity decoupling operation mode of the IES decrease successively. The system flexibility is greatly enhanced, and the energy-use rate of the system is improved as a whole. Finally, IES, after its flexible transformation, significantly achieve energy conservation, emission reduction, and environmental protection.
引用
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页数:27
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