This paper addresses the problem of reducing CO<sub>2</sub> emissions by applying convex optimal power flow model to the combined economic and emission dispatch problem. The large amount of CO<sub>2&...This paper addresses the problem of reducing CO<sub>2</sub> emissions by applying convex optimal power flow model to the combined economic and emission dispatch problem. The large amount of CO<sub>2</sub> emissions in the power industry is a major source of global warming effect. An efficient and economic approach to reduce CO<sub>2</sub> emissions is to formulate the emission reduction problem as emission dispatch problem and combined with power system economic dispatch (ED). Because the traditional optimal power flow (OPF) model used by the economic dispatch is nonlinear and nonconvex, current nonlinear solvers are not able to find the global optimal solutions. In this paper, we use the convex optimal power flow model to formulate the combined economic and emission dispatch problem. The advantage of using convex power flow model is that global optimal solutions can be obtained by using mature industrial strength nonlinear solvers such as MOSEK. Numerical results of various IEEE power network test cases confirm the feasibility and advantage of convex combined economic and emission dispatch (CCEED).展开更多
Optimal power flow(OPF) is the fundamental mathematical model to optimize power system operations.Based on conic relaxation, Taylor series expansion and McCormick envelope, we propose three convex OPF models to improv...Optimal power flow(OPF) is the fundamental mathematical model to optimize power system operations.Based on conic relaxation, Taylor series expansion and McCormick envelope, we propose three convex OPF models to improve the performance of the second-order cone alternating current OPF(SOC-ACOPF) model. The underlying idea of the proposed SOC-ACOPF models is to drop assumptions of the original SOC-ACOPF model by convex relaxation and approximation methods.A heuristic algorithm to recover feasible ACOPF solution from the relaxed solution of the proposed SOC-ACOPF models is developed. The proposed SOC-ACOPF models are examined through IEEE case studies under various load scenarios and power network congestions. The quality of solutions from the proposed SOC-ACOPF models is evaluated using MATPOWER(local optimality) and LINDOGLOBAL(global optimality). We also compare numerically the proposed SOC-ACOPF models with other two convex ACOPF models in the literature.The numerical results show robust performance of the proposed SOCACOPF models and the feasible solution recovery algorithm.展开更多
文摘This paper addresses the problem of reducing CO<sub>2</sub> emissions by applying convex optimal power flow model to the combined economic and emission dispatch problem. The large amount of CO<sub>2</sub> emissions in the power industry is a major source of global warming effect. An efficient and economic approach to reduce CO<sub>2</sub> emissions is to formulate the emission reduction problem as emission dispatch problem and combined with power system economic dispatch (ED). Because the traditional optimal power flow (OPF) model used by the economic dispatch is nonlinear and nonconvex, current nonlinear solvers are not able to find the global optimal solutions. In this paper, we use the convex optimal power flow model to formulate the combined economic and emission dispatch problem. The advantage of using convex power flow model is that global optimal solutions can be obtained by using mature industrial strength nonlinear solvers such as MOSEK. Numerical results of various IEEE power network test cases confirm the feasibility and advantage of convex combined economic and emission dispatch (CCEED).
文摘Optimal power flow(OPF) is the fundamental mathematical model to optimize power system operations.Based on conic relaxation, Taylor series expansion and McCormick envelope, we propose three convex OPF models to improve the performance of the second-order cone alternating current OPF(SOC-ACOPF) model. The underlying idea of the proposed SOC-ACOPF models is to drop assumptions of the original SOC-ACOPF model by convex relaxation and approximation methods.A heuristic algorithm to recover feasible ACOPF solution from the relaxed solution of the proposed SOC-ACOPF models is developed. The proposed SOC-ACOPF models are examined through IEEE case studies under various load scenarios and power network congestions. The quality of solutions from the proposed SOC-ACOPF models is evaluated using MATPOWER(local optimality) and LINDOGLOBAL(global optimality). We also compare numerically the proposed SOC-ACOPF models with other two convex ACOPF models in the literature.The numerical results show robust performance of the proposed SOCACOPF models and the feasible solution recovery algorithm.
