Intelligent Scheduling Optimization of Seasonal CCHP System Using Rolling Horizon Hybrid Optimization Algorithm and Matrix Model Framework

被引：19

作者：

Wang Yanan ^{[1
]}

Wu Jiekang ^{[1
]}

Mao Xiaoming ^{[1
]}

机构：

[1] Guangdong Univ Technol, Sch Automat, Guangzhou, Guangdong, Peoples R China

来源：

IEEE ACCESS | 2018年 / 6卷

基金：

中国国家自然科学基金;

关键词：

CCHP system; rolling horizon; matrix model framework; intelligent scheduling; PARTICLE SWARM OPTIMIZATION; ENERGY MANAGEMENT; FUEL PRICE; SOLAR; GAS; PERFORMANCE; MICROGRIDS; ECONOMICS; STRATEGY; DESIGN;

D O I：

10.1109/ACCESS.2018.2878044

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The optimal operation of a combined cooling, heating and power (CCHP) system depends on its structure and adopted energy dispatch strategies. This paper proposes a matrix modeling method for the CCHP system structure, in which multi-energy supply is regarded as the input of system, and cooling, heating, electric load as the output of the system. The energy flow from the system input to output includes the scheduling matrix, the efficiency matrix, and the energy conversion matrix model. Adopt mixed rolling-horizon and particle swarm optimization algorithm to allocation the system scheduling factor to promote optimal operation of CCHP systems. According to the characteristics of input and output energy flow in different seasons of a certain area, the system is simulated and calculated. The results show that the adoption of rolling-horizon optimization for the thermal-electric load in winter can fully calculate the three scheduling strategies and select the optimal strategy in the rolling window. Compared to other methods, the optimization of scheduling factors in summer highlights the low-cost benefits.

引用

页码：75132 / 75142

页数：11