Open AccessMulti-objective optimal operation of renewable energy hybrid CCHP system using SSO
Author(s) -
Wei-Chang Yeh,
Chyh-Ming Lai,
Yi-Fan Peng
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1411/1/012016
Subject(s) - renewable energy , environmental science , hybrid system , computer science , process engineering , environmental economics , engineering , electrical engineering , economics , machine learning
In recent years, the amalgamation of renewable energies into combined cooling, heating and power system (CCHP) become a popular research in energy field. In order to improve the energy utilization of renewable energies integrated the CCHP (RECCHP) system, it is necessary to optimize the operation and component capacity in the RECCHP system. A multi-objective optimization model characterizing the system daily operation cost, daily carbon dioxide emission, and primary energy saving rate is established. Considering each objective function, Simplified Swarm Optimization (SSO) is applied as a single objective optimization problem to find the best capacity of components and operation of the system. Further, normalize three objective respectively and use Analytic Hierarchy Process to get weight for each objective. Transform the multi-objective optimization problem into a single objective optimization problem. Finally, taking a historical weather data in winter of Kinmen Island, Taiwan, as a case study, solve the problem with SSO, and the experiment results are compared with traditional energy systems. The results show that the RECCHP system is better than traditional energy systems among economic, environmental and energy aspect.