This paper investigates the use of Reconfigurable Intelligent Surfaces (RIS) in downlink multi-user communication systems to improve energy efficiency. The authors propose two computationally efficient algorithms for optimizing the phase shifts of the RIS and the transmit power allocation, subject to individual link budget constraints. The first algorithm uses gradient descent for phase shifts and fractional programming for power allocation, while the second uses sequential fractional programming for phase shifts. A realistic power consumption model for RIS-based systems is also presented. The results show that the proposed RIS-based methods can achieve up to 300% higher energy efficiency compared to traditional multi-antenna amplify-and-forward relaying. The algorithms are evaluated in a realistic outdoor environment, demonstrating their effectiveness in improving energy efficiency in wireless communication systems. The paper also discusses the system model, including the signal model and total power consumption, and presents the design problem formulation for maximizing energy efficiency. The proposed algorithms are shown to converge to optimal solutions, with the first algorithm using gradient descent and the second using sequential fractional programming. The results indicate that the proposed methods outperform traditional relay-based systems in terms of energy efficiency.This paper investigates the use of Reconfigurable Intelligent Surfaces (RIS) in downlink multi-user communication systems to improve energy efficiency. The authors propose two computationally efficient algorithms for optimizing the phase shifts of the RIS and the transmit power allocation, subject to individual link budget constraints. The first algorithm uses gradient descent for phase shifts and fractional programming for power allocation, while the second uses sequential fractional programming for phase shifts. A realistic power consumption model for RIS-based systems is also presented. The results show that the proposed RIS-based methods can achieve up to 300% higher energy efficiency compared to traditional multi-antenna amplify-and-forward relaying. The algorithms are evaluated in a realistic outdoor environment, demonstrating their effectiveness in improving energy efficiency in wireless communication systems. The paper also discusses the system model, including the signal model and total power consumption, and presents the design problem formulation for maximizing energy efficiency. The proposed algorithms are shown to converge to optimal solutions, with the first algorithm using gradient descent and the second using sequential fractional programming. The results indicate that the proposed methods outperform traditional relay-based systems in terms of energy efficiency.