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contributor authorJavad Kasaei, Mohammad
contributor authorGandomkar, Majid
contributor authorNikoukar, Javad
date accessioned2017-11-25T07:21:16Z
date available2017-11-25T07:21:16Z
date copyright2017/16/8
date issued2017
identifier issn0195-0738
identifier otherjert_139_06_062003.pdf
identifier urihttp://138.201.223.254:8080/yetl1/handle/yetl/4236996
description abstractIn recent years, a large number of renewable energy sources (RESs) have been added into modern distribution systems because of their clean and renewable property. Nevertheless, the high penetration of RESs and intermittent nature of some resources such as wind power and photovoltaic (PV) cause the variable generation and uncertainty of power system. In this condition, one idea to solve problems due to the variable output of these resources is to aggregate them together. A collection of distributed generations (DGs) such as wind turbine (WT), PV panel, fuel cell (FC), and any other sources of power, energy storage systems, and controllable loads that are aggregated together and are managed by an energy management system (EMS) are called a virtual power plant (VPP). The objective of the VPP in this paper is to minimize the total operating cost for a 24-h period. To solve the problem, a metaheuristic optimization algorithm, teaching–learning based optimization (TLBO), is proposed to determine optimal management of RESs, storage battery, and load control in a real case study.
publisherThe American Society of Mechanical Engineers (ASME)
titleOptimal Operational Scheduling of Renewable Energy Sources Using Teaching–Learning Based Optimization Algorithm by Virtual Power Plant
typeJournal Paper
journal volume139
journal issue6
journal titleJournal of Energy Resources Technology
identifier doi10.1115/1.4037371
journal fristpage62003
journal lastpage062003-8
treeJournal of Energy Resources Technology:;2017:;volume( 139 ):;issue: 006
contenttypeFulltext


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