<p>The development of wireless transmission technology has led to the conceptualization of energy transmission as a service, giving rise to the abstract concept of "Energy as a Service". However, a single energy service is increasingly inadequate to meet the growing energy demand, making the selection of multiple energy services for collaborative operation a pressing challenge. Existing service selection algorithms often face challenges such as high computational complexity and insufficient adaptability when addressing large-scale, complex problems. To address this, this paper proposes the integration of deep reinforcement learning with energy service selection, employing the Proximal Policy Optimization algorithm to solve the energy service selection problem. Additionally, to address the shortcomings of current research in ensuring the reliability of energy services, this paper introduces a blockchain-based smart contract approach for energy service selection, utilizing blockchain to prevent tampering with service information and ensuring service reliability. Experimental results demonstrate that the proposed method exhibits significant advantages in preventing service information tampering and in addressing the energy service selection problem. </p>