If you do not change the size of the layers and just add more layers, capacity should increase, so you could be overfitting. However, you should check whether training error increases or decreases. If it increases (which is also very plausible), it means that adding the layer made the optimization harder, with the optimization methods and initialization that you are using.  That could also explain your problem. However, if training error decreases and test error increases, you are overfitting.