This paper investigates the use of Reconfigurable Intelligent Surfaces (RIS) for energy efficiency (EE) in downlink multi-user communication from a multi-antenna base station. The authors develop energy-efficient designs for transmit power allocation and phase shifts of the RIS reflecting elements, subject to individual link budget guarantees for mobile users. They propose two computationally efficient approaches to tackle the non-convex design optimization problems: alternating maximization, gradient descent search, and sequential fractional programming. The first algorithm uses gradient descent for phase coefficient optimization and fractional programming for transmit power allocation, while the second algorithm employs sequential fractional programming for phase shift optimization. A realistic power consumption model for RIS-based systems is presented, and the performance of the proposed methods is analyzed in a realistic outdoor environment. The results show that the proposed RIS-based resource allocation methods can achieve up to 300% higher EE compared to traditional multi-antenna amplify-and-forward relaying.This paper investigates the use of Reconfigurable Intelligent Surfaces (RIS) for energy efficiency (EE) in downlink multi-user communication from a multi-antenna base station. The authors develop energy-efficient designs for transmit power allocation and phase shifts of the RIS reflecting elements, subject to individual link budget guarantees for mobile users. They propose two computationally efficient approaches to tackle the non-convex design optimization problems: alternating maximization, gradient descent search, and sequential fractional programming. The first algorithm uses gradient descent for phase coefficient optimization and fractional programming for transmit power allocation, while the second algorithm employs sequential fractional programming for phase shift optimization. A realistic power consumption model for RIS-based systems is presented, and the performance of the proposed methods is analyzed in a realistic outdoor environment. The results show that the proposed RIS-based resource allocation methods can achieve up to 300% higher EE compared to traditional multi-antenna amplify-and-forward relaying.