Title :
Emission reduction in a micro grid including PV considering voltage profile improvement
Author :
Rahbarimagham, H. ; Sanjari, M.J. ; Tavakoli, A. ; Gharehpetian, G.B. ; Jafari, Roozbeh
Author_Institution :
Electr. Eng. Dept., Amirkabir Univ. of Technol., Tehran, Iran
Abstract :
Air pollution and increasing cost of conventional fuel leads to use renewable energy more and more. Renewable energy which is known as green power has no pollution and does not use any fuel. DGs are setup near customer to reduce the cost of transmission. Generated power of renewable resources such as photovoltaic, wind power and etc. are highly affected by weather condition, so if renewable resources are use in power grid because of aforementioned problem voltage of nodes of the grid may influence by change in generated power of DGs. Therefore conventional control method is not suitable to use in this kind of power grid. In this paper a new control technique has been proposed to reduce emission and reach an optimal control of nodes voltage in grid that contains renewable resources and equipment to keep nodes voltages in desire margin such as, step voltage regulator, shunt reactor/capacitor and static VAR compensator. Also in this grid it is assumed that communication link is widespread. Genetic algorithm has been used to find the best condition of operation of these equipment. In order to show the advantages of this method, simulations have been applied to a test network with DGs. In this study, DGs are photovoltaic and fuel cell. Fuel cell has been used to keep surplus power of PV in day and inject its power in night when needed.
Keywords :
distributed power generation; fuel cell power plants; genetic algorithms; optimal control; photovoltaic power systems; power generation control; power grids; static VAr compensators; voltage control; voltage regulators; DG; PV; air pollution; communication link; conventional control method; conventional fuel cost; distributed generation; emission reduction; fuel cell; genetic algorithm; microgrid; optimal control; photovoltaic; power grid; renewable energy; shunt capacitor; shunt reactor; static VAR compensator; step voltage regulator; test network; transmission cost; voltage profile improvement; wind power; Distributed power generation; Fuel cells; Genetic algorithms; Mathematical model; Sociology; Static VAr compensators; Voltage control; distributed generation; fuel cell; genetic algorithm; photovoltaic; renewable resources;
Conference_Titel :
Smart Grid Conference (SGC), 2013
Conference_Location :
Tehran
Print_ISBN :
978-1-4799-3039-5
DOI :
10.1109/SGC.2013.6733811