Title :
Stochastic Wind-Thermal Generation Scheduling Considering Emission Reduction: A Multiobjective Mathematical Programming Approach
Author :
Khorsand, M.A. ; Zakariazadeh, A. ; Jadid, S.
Author_Institution :
Electr. Eng. Dept., Iran Univ. of Sci. & Technol. (IUST), Tehran, Iran
Abstract :
To regard environmental protection renewable energy sources especially wind, has been applied to achieve emission reduction goals. While wind generation does not directly produce air pollutants emission, it causes some changes on thermal power generation scheduling which may lead them to produce more air pollutants emission especially during low and medium energy demand periods. So it seems necessary to consider air pollutants emission level in wind-thermal scheduling problems. This paper proposes a methodology for wind-thermal scheduling in a power system with high penetration of wind power subject to consider air pollutants emission reduction. Because of simultaneous minimizing total operating cost and air pollutants emission, a Multiobjective Mathematical Programming (MMP) is introduced. The computation of the required reserve levels and their costs is attained through a stochastic programming market clearing model. Also, the network constraints and the costs of both the load shedding and the wind spillage are considered. The usefulness of the proposed approach was tested through an IEEE 30-bus test system.
Keywords :
air pollution control; load shedding; power generation scheduling; power markets; renewable energy sources; stochastic programming; thermal power stations; wind power plants; IEEE 30-bus test system; air pollutant emission reduction; electricity markets; energy demand; environmental protection renewable energy source; load shedding; multiobjective mathematical programming approach; stochastic programming market clearing model; stochastic wind-thermal generation scheduling; thermal power generation scheduling; wind power; wind spillage; Air pollution; Atmospheric modeling; Generators; Power systems; Programming; Stochastic processes; Wind power generation;
Conference_Titel :
Power and Energy Engineering Conference (APPEEC), 2011 Asia-Pacific
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-6253-7
DOI :
10.1109/APPEEC.2011.5748964