Widely distributed multiple-input multiple-output (MIMO) radar systems offer parameter estimation improvement for target localization, proportional to the product of the number of transmitting and receiving radars and the total transmitted power. Thus far, power allocation has been uniformly distributed between the system transmitters. For a large number of radars, the achievable localization mean-square error (MSE), with full resource allocation, may extend beyond the system predetermined performance goals, such as target localization accuracy (i.e., minimum estimation MSE) and total power radiation. In this study, power allocation schemes are developed, taking into account system constraints. The first is concerned with minimizing the total transmitted power such that a predefined estimation MSE objective is met, while keeping the transmitted power at each station within an acceptable range. The second, optimally distributes a given power budget among all transmitting radars to maximize performance, i.e., minimize the attainable localization MSE. As the Cramer-Rao bound (CRB) is known to be asymptotically tight to the maximum likelihood estimator (MLE) MSE at high SNR, it is used as a metric for the estimation MSE. The CRB is derived for a signal model that incorporates the propagation path loss, the target radar cross section (RCS), and the transmitters' powers. It is shown that uniform or equal power allocation is not in general optimal and that the proposed allocation algorithms result in a local optimum that provided either better localization MSE for the same power budget or requires less power to establish the same performance in terms of estimation MSE. A physical interpretation of these conclusions is offered.