381
Views
37
CrossRef citations to date
0
Altmetric
Articles

Optimal operation of microgrid with multi-energy complementary based on moth flame optimization algorithm

, , , , , & show all
Pages 785-806 | Received 28 Aug 2018, Accepted 08 Jan 2019, Published online: 14 Mar 2019
 

ABSTRACT

Recently, hybrid distributed generation system has become a popular energy supply mode. It is obvious that the integrated system could improve energy efficiency and reduce costs. However, the system scheduling is a problem that would determine the operation cost. In this paper, a hybrid energy system including wind power, photovoltaics, gas turbines, and energy storage was introduced. In order to obtain the minimum operation cost, an operation optimization model was built. The schedule plan of each unit was optimized by moth flame optimization algorithm. Finally, through empirical research on a microgrid project, the optimization results in three configuration case of wind power, photovoltaics, and storage indicated that the operation optimization model in this paper could effectively reduce system operation cost, and the optimal output plan of each unit was obtained. And it is proved that the model proposed in this paper has a certain guiding role on economically dispatch of hybrid energy system.

Parameters

Additional information

Funding

This paper is supported by the 2018 Key Projects of Philosophy and Social Sciences Research, Ministry of Education, China (18JZD032); the Project of Beijing Social Science Fund (18GL042); the Fundamental Research Funds for the Central Universities (2018ZD13).

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.