In this paper,a combined optimization of a coupled electricity and gas system is presented.For the electricity network a unit commitment problem with optimization of energy and reserves under a power pool,considering ...In this paper,a combined optimization of a coupled electricity and gas system is presented.For the electricity network a unit commitment problem with optimization of energy and reserves under a power pool,considering all system operational and unit technical constraints is solved.The gas network subproblem is a medium-scale mixed-integer nonconvex and nonlinear programming problem.The coupling constraints between the two networks are nonlinear as well.The resulting mixed-integer nonlinear program is linearized with the extended incremental method and an outer approximation technique.The resulting model is evaluated using the Greek power and gas system comprising fourteen gas-fired units under four different approximation accuracy levels.The results indicate the efficiency of the proposed mixed-integer linear program model and the interplay between computational requirements and accuracy.展开更多
基金funding through the DFG SFB/Transregio 154, Subprojects A05 and Z01
文摘In this paper,a combined optimization of a coupled electricity and gas system is presented.For the electricity network a unit commitment problem with optimization of energy and reserves under a power pool,considering all system operational and unit technical constraints is solved.The gas network subproblem is a medium-scale mixed-integer nonconvex and nonlinear programming problem.The coupling constraints between the two networks are nonlinear as well.The resulting mixed-integer nonlinear program is linearized with the extended incremental method and an outer approximation technique.The resulting model is evaluated using the Greek power and gas system comprising fourteen gas-fired units under four different approximation accuracy levels.The results indicate the efficiency of the proposed mixed-integer linear program model and the interplay between computational requirements and accuracy.
