Stochastic unit commitment is one of the most powerful methods to address uncertainty. However, the existingscenario clustering technique for stochastic unit commitment cannot accurately select representative scenario...Stochastic unit commitment is one of the most powerful methods to address uncertainty. However, the existingscenario clustering technique for stochastic unit commitment cannot accurately select representative scenarios,which threatens the robustness of stochastic unit commitment and hinders its application. This paper providesa stochastic unit commitment with dynamic scenario clustering based on multi-parametric programming andBenders decomposition. The stochastic unit commitment is solved via the Benders decomposition, which decouplesthe primal problem into the master problem and two types of subproblems. In the master problem, the committedgenerator is determined, while the feasibility and optimality of generator output are checked in these twosubproblems. Scenarios are dynamically clustered during the subproblem solution process through the multiparametric programming with respect to the solution of the master problem. In other words, multiple scenariosare clustered into several representative scenarios after the subproblem is solved, and the Benders cut obtainedby the representative scenario is generated for the master problem. Different from the conventional stochasticunit commitment, the proposed approach integrates scenario clustering into the Benders decomposition solutionprocess. Such a clustering approach could accurately cluster representative scenarios that have impacts on theunit commitment. The proposed method is tested on a 6-bus system and the modified IEEE 118-bus system.Numerical results illustrate the effectiveness of the proposed method in clustering scenarios. Compared withthe conventional clustering method, the proposed method can accurately select representative scenarios whilemitigating computational burden, thus guaranteeing the robustness of unit commitment.展开更多
The moisture content of subgrade soil in seasonally frozen regions is often higher than its optimum value,leading to a decline in mechanical properties and a reduction in subgrade bearing capacity.Electro-osmosis has ...The moisture content of subgrade soil in seasonally frozen regions is often higher than its optimum value,leading to a decline in mechanical properties and a reduction in subgrade bearing capacity.Electro-osmosis has shown promise as a technology for controlling subgrade moisture,but significant heterogeneity has also been observed in treated soil.This study investigates the impact of electro-osmosis on soil stiffness through a series of bender element tests of compacted clay.The effects of dry density and supply voltage on the performance of electroosmosis treatment and the layered structure and anisotropy of the soil were analyzed.The results show that electro-osmosis treatment increased the shear wave velocity of the soil by 140% compared to untreated saturated soil and by 70% compared to soil with optimum water content.It has also been found that layered compaction of soil resulted in a layered structure,with electro-osmosis having a more prominent impact on soil near the cathode,resulting in a more pronounced layered structure.Besides,electro-osmosis was found to enhance soil anisotropy,particularly near the anode.Increasing the dry density and voltage levels can help improve soil uniformity.These findings provide insights into the potential use of electro-osmosis in improving soil stiffness,which could benefit various engineering applications.展开更多
基金the Science and Technology Project of State Grid Corporation of China,Grant Number 5108-202304065A-1-1-ZN.
文摘Stochastic unit commitment is one of the most powerful methods to address uncertainty. However, the existingscenario clustering technique for stochastic unit commitment cannot accurately select representative scenarios,which threatens the robustness of stochastic unit commitment and hinders its application. This paper providesa stochastic unit commitment with dynamic scenario clustering based on multi-parametric programming andBenders decomposition. The stochastic unit commitment is solved via the Benders decomposition, which decouplesthe primal problem into the master problem and two types of subproblems. In the master problem, the committedgenerator is determined, while the feasibility and optimality of generator output are checked in these twosubproblems. Scenarios are dynamically clustered during the subproblem solution process through the multiparametric programming with respect to the solution of the master problem. In other words, multiple scenariosare clustered into several representative scenarios after the subproblem is solved, and the Benders cut obtainedby the representative scenario is generated for the master problem. Different from the conventional stochasticunit commitment, the proposed approach integrates scenario clustering into the Benders decomposition solutionprocess. Such a clustering approach could accurately cluster representative scenarios that have impacts on theunit commitment. The proposed method is tested on a 6-bus system and the modified IEEE 118-bus system.Numerical results illustrate the effectiveness of the proposed method in clustering scenarios. Compared withthe conventional clustering method, the proposed method can accurately select representative scenarios whilemitigating computational burden, thus guaranteeing the robustness of unit commitment.
基金supported by the National Natural Science Foundation of China(No.41971076,No.42171128)。
文摘The moisture content of subgrade soil in seasonally frozen regions is often higher than its optimum value,leading to a decline in mechanical properties and a reduction in subgrade bearing capacity.Electro-osmosis has shown promise as a technology for controlling subgrade moisture,but significant heterogeneity has also been observed in treated soil.This study investigates the impact of electro-osmosis on soil stiffness through a series of bender element tests of compacted clay.The effects of dry density and supply voltage on the performance of electroosmosis treatment and the layered structure and anisotropy of the soil were analyzed.The results show that electro-osmosis treatment increased the shear wave velocity of the soil by 140% compared to untreated saturated soil and by 70% compared to soil with optimum water content.It has also been found that layered compaction of soil resulted in a layered structure,with electro-osmosis having a more prominent impact on soil near the cathode,resulting in a more pronounced layered structure.Besides,electro-osmosis was found to enhance soil anisotropy,particularly near the anode.Increasing the dry density and voltage levels can help improve soil uniformity.These findings provide insights into the potential use of electro-osmosis in improving soil stiffness,which could benefit various engineering applications.
