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
Series compensation has proven to increase stability in transmission of electric power. On the other hand insertion of series capacitor results in severe subsynchronous torques. The subsynchronous torque leads to gene...Series compensation has proven to increase stability in transmission of electric power. On the other hand insertion of series capacitor results in severe subsynchronous torques. The subsynchronous torque leads to generator-turbine shaft damage. Mitigation of subsynchronous transient torques is achieved through resistor bank connected to generator terminals. The insertion of resistor bank is controlled by fuzzy logic controller. The proposed controller has been tested on IEEE First Benchmark Model and it proved to have good damping for the torsional torques.展开更多
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.
文摘Series compensation has proven to increase stability in transmission of electric power. On the other hand insertion of series capacitor results in severe subsynchronous torques. The subsynchronous torque leads to generator-turbine shaft damage. Mitigation of subsynchronous transient torques is achieved through resistor bank connected to generator terminals. The insertion of resistor bank is controlled by fuzzy logic controller. The proposed controller has been tested on IEEE First Benchmark Model and it proved to have good damping for the torsional torques.
