A hybrid active-passive reconfigurable intelligent surface (RIS) transmitter is proposed for energy-efficient multi-user communications. The RIS serves as a transmitter antenna, with elements capable of switching between active and passive modes to deliver information to multiple users. The system energy efficiency (EE) is maximized by jointly optimizing RIS element scheduling, beamforming coefficients, and power allocation, subject to user rate requirements and RIS amplification power constraints. The original mixed-integer nonlinear programming problem is transformed into a non-fractional optimization problem using the Dinkelbach relaxation, which is solved via an alternating optimization approach. An exhaustive search method determines the optimal operating mode for each RIS element, while the RIS beamforming and power allocation coefficients are alternately designed. A joint RIS element mode and beamforming optimization scheme is developed using the Big-M formulation technique to reduce complexity. Numerical results show that the proposed hybrid RIS scheme outperforms baseline schemes in EE, with the latter achieving precise RIS element design with low complexity. For a fixed-size hybrid RIS, maximum EE is achieved by operating only a minority of elements in the active mode. The system model includes a hybrid RIS transmitter with active and passive elements, and the signal model is formulated to maximize EE while satisfying user rate requirements and power constraints. The problem is solved using an alternating optimization algorithm, with the RIS beamforming and power allocation coefficients alternately optimized. The algorithm is shown to converge to a suboptimal solution, with computational complexity analyzed for the proposed method. A low-complexity algorithm is also presented for joint RIS element mode and beamforming optimization.A hybrid active-passive reconfigurable intelligent surface (RIS) transmitter is proposed for energy-efficient multi-user communications. The RIS serves as a transmitter antenna, with elements capable of switching between active and passive modes to deliver information to multiple users. The system energy efficiency (EE) is maximized by jointly optimizing RIS element scheduling, beamforming coefficients, and power allocation, subject to user rate requirements and RIS amplification power constraints. The original mixed-integer nonlinear programming problem is transformed into a non-fractional optimization problem using the Dinkelbach relaxation, which is solved via an alternating optimization approach. An exhaustive search method determines the optimal operating mode for each RIS element, while the RIS beamforming and power allocation coefficients are alternately designed. A joint RIS element mode and beamforming optimization scheme is developed using the Big-M formulation technique to reduce complexity. Numerical results show that the proposed hybrid RIS scheme outperforms baseline schemes in EE, with the latter achieving precise RIS element design with low complexity. For a fixed-size hybrid RIS, maximum EE is achieved by operating only a minority of elements in the active mode. The system model includes a hybrid RIS transmitter with active and passive elements, and the signal model is formulated to maximize EE while satisfying user rate requirements and power constraints. The problem is solved using an alternating optimization algorithm, with the RIS beamforming and power allocation coefficients alternately optimized. The algorithm is shown to converge to a suboptimal solution, with computational complexity analyzed for the proposed method. A low-complexity algorithm is also presented for joint RIS element mode and beamforming optimization.