Optimal planning of operations for power transmission systems under uncertainty

In this study, investigations with probabilistic methods are made to quantitatively evaluate the impacts of uncertain inputs on power system operation performances. Application of probabilistic analysis to power flow studies leads to the problem of probabilistic power flow (PPF). In the decision-making process for optimal dispatches, optimization approaches for optimal power flow (OPF) in the presence of uncertainty are required such that robust solutions can be derived. The chance constrained programming (CCP) approach is introduced to solve the OPF problem under uncertainty. With the help of chance constrained OPF, the expected value of the objective function will be minimized while requisite level of reliability to ensure constraints can be maintained at the same time. It provides an advisable risk-management tool in operation planning. Aspects of optimality and reliability of power system operations can be quantitatively balanced by carrying out chance constrained OPF.