# NFV-Enabled Efficient Renewable and Non-Renewable Energy Management: Requirements and Algorithms
## 1 Introduction  
In recent years, the increasing energy consumption and CO\({}_{2}\) emissions caused by the deployment of new services and the proliferation of the Internet of Things (IoT) concept are becoming critical concerns driving the adoption of new solutions for energy production and management [1]. According to [2], the development of the Information and Communication Technology (ICT) industry could use up to 50% of the world's electricity in 2030 and up to 23% of CO\({}_{2}\) emissions. Consequently, the ICT and energy sectors have encouraged the use of renewable energy sources and deployment of adaptive energy management schemes with active customer-side participation. The purpose of these actions is to ensure sustainability and the long-term development of human society. Renewable energy sources, such as solar and wind, are envisioned as an environmentally friendly and sustainable alternative to meet current and future energy demands [3]. However, the sporadic nature of green energy may cause instability when integrated into conventional energy sources [3]. This issue, along with the inefficient use of the generated energy (from renewable and non-renewable sources), have led to the development of Demand Response (DR) schemes, in which the consumption is adapted to generation dynamically using requests and actions exchanged between the Energy supplier (ES) and Energy Consumers (ECs) [4]. An essential component for deploying DR schemes is the ICT infrastructure that is needed for both the data exchange (i.e., notifications and instructions) between the ES and the ECs and the execution of management mechanisms (e.g., workload scheduling) [5]. In this regard, existing ICT solutions, such as cloud computing infrastructures and IoT technologies, can be used as key enablers for delivering feasible smart and programable management approaches for adaptive consumption of available supply. Specifically, the Network Functions Virtualization (NFV) technology can be used to deploy management mechanisms (carried out through algorithmic solutions) as software components, named Virtual Network Functions (VNFs), which can be used or modified on-demand [6], according to the dynamic requirements of the energy demands. The VNFs executed on Data Centers (DCs) (i.e., on cloud computing infrastructures) can dispose of a scalable computational capacity (mainly in terms of processing power and memory) needed to carry out adaptive energy management, as shown in [5]. Likewise, the massive connectivity available to end-users due to the proliferation of IoT technologies and development of network systems, such as 5G, makes it possible for potential energy consumers to participate in the energy management process [7]. It is expected that the number of devices connected to the Internet will increase considerably in the coming years (e.g., Cisco estimates that there will be 28.5 billion networked devices by 2022 [8]). Thus, eventually, all energy consumers (i.e., devices, appliances, or, in general, IoT infrastructures) will be able to be managed, for example, in terms of their consumption. This condition facilitates a true customer-side, the complete interaction between the ECs and the ES, the improvement in control, monitoring and management tasks, as well as the applicability to small scenarios, such as Home Energy Management Systems (HEMS) or environments as big as cities or countries. In this regard, an adaptive energy management proposal that is enabled by IoT and NFV technologies is a feasible, promising proposal that represents the evolution of smart grids, and it is aligned with the vision of future energy systems currently referred to as the Internet of Energy (IoE) [9]. This paper analyzes the adaptive energy management conditioned on the available supply of renewable and non-renewable sources from the point of view of communications systems.