Digital predistortion (DPD) is essential for mitigating nonlinearity in RF power amplifiers, particularly for wideband applications. This paper presents TCN-DPD, a parameter-efficient architecture based on temporal convolutional networks, integrating noncausal dilated convolutions with optimized activation functions. Evaluated on the OpenDPD framework with the DPA_200 MHz dataset, TCN-DPD achieves simulated ACPRs of -51.58 /-49.26dBc (L/R), EVM of -47.52 dB, and NMSE of -44.61 dB with 500 parameters and maintain superior linearization than prior models down to 200 parameters, making it promising for efficient wideband PA linearization.