Reducing environmental pollution and fuel consumption using optimization algorithm to develop combined cooling heating and power system operation strategies

被引:42
|
作者
Li, Ling-Ling [1 ,2 ]
Liu, Yu-Wei [1 ,2 ]
Tseng, Ming-Lang [3 ,4 ]
Lin, Guo-Qian [1 ]
Ali, Mohd Helmi [5 ]
机构
[1] Hebei Univ Technol, State Key Lab Reliabil & Intelligence Elect Equip, Tianjin 300130, Peoples R China
[2] Hebei Univ Technol, Key Lab Electromagnet Field & Elect Apparat Relia, Tianjin 300130, Peoples R China
[3] Asia Univ, Inst Innovat & Circular Econ, Taichung, Taiwan
[4] China Med Univ, China Med Univ Hosp, Dept Med Res, Taichung, Taiwan
[5] Natl Univ Malaysia, Fac Econ & Management, Bangi, Malaysia
关键词
Combined cooling heating and power system; Photovoltaic generation unit; Hybrid operation strategy; System optimization; Chaos-mutation-whale optimization algorithm; PARTICLE SWARM OPTIMIZATION; CCHP SYSTEM; PARAMETER-ESTIMATION; LOCAL SEARCH; ENERGY; DESIGN; MODEL; DISPATCH; TRIGENERATION; MANAGEMENT;
D O I
10.1016/j.jclepro.2019.119082
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
A combined cooling heating and power model with photovoltaic generation unit, thermal storage tank and battery is established to improve energy efficiency and reduce carbon emissions in combined cooling heating and power model for achieving cleaner production and environmental pollution reduction, and the hybrid following the electric load strategy and hybrid following the thermal load strategy are proposed based on the following the electric load strategy and following the thermal load strategy. Besides, the chaos-mutation-whale optimization algorithm is proposed to solve the models by using chaotic initialization and mutation rules into the original whale optimization algorithm. A large hotel case is used to analyze the feasibility of the proposed method. The result demonstrates the electricity import saving ratio, primary energy saving ratio and fuel consumption to cost ratio are 62.07%, 35.75% and 1.47% under the hybrid following the thermal load strategy, and the chaos-mutation-whale optimization algorithm achieves optimization in a shorter number of iterations. The performance indicators are better than the following the electric load, following the thermal load and hybrid following the thermal load strategies, indicating that environmental pollution and fuel consumption are greatly reduced by using the proposed method, which is of great significance to the realization of cleaner production and environmental sustainability. This study is carried out under ideal circumstances. (C) 2019 Elsevier Ltd. All rights reserved.
引用
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页数:13
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