In some power systems, the Jacobian matrix can be ill-conditioned, leading to difficulties in reaching a valid a power flow solution.
A matrix is considered to be ill-conditioned if it is very sensitive to small changes. The classic illustration of ill-conditioning is the following two linear systems of the form Ax = b:
- ... (1)
- ... (2)
The solution to system (1) is , , while the solution to system (2) is .
What this shows is that a tiny change in the 4th decimal place of the vector b in the system Ax = b can lead to relatively large changes in the solution vector x. As a result, inaccuracies in the data (such as rounding errors) can have large consequences when systems are ill-conditioned. The condition number of a matrix is often used to describe the degree of ill-conditioning.
Ill-Conditioned Power Flow Problems
In power systems, the power flow problem is said to be ill-conditioned if the Jacobian matrix is ill-conditioned. This is because in the Newton-Raphson algorithm, each iteration has the following linear form:
where is the power flow Jacobian matrix
- is the bus voltage (magnitude and angle) correction vector
- is the active and reactive power mismatch vector
Therefore, if the Jacobian matrix is ill-conditioned, the solution to the power flow iteration can become wildly unstable or divergent.
The most common characteristics that lead to ill-conditioned power flow problems are as follows:
- Heavily loaded power system (i.e. voltage stability problem where system has reached nose point of PV curve)
- Lines with high R/X ratios
- Large system with many radial lines
- Poor selection of the slack bus (e.g. in a weakly supported part of the network)