## 1 Introduction  
While existing electricity grids work unidirectionally from producer to consumer, intelligent electricity grids, otherwise known as smart grids [1], offer new possibilities for energy use, particularly in integrating decentralized energy generation facilities. Smart grids scale through networking among each other and are subject to constant dynamics. For example, electric and hybrid vehicles can be included in grids as consumers or storage devices to avoid peak loads and reduce carbon emissions [2]. The smallest unit of smart grids, which comprises unidirectional energy flow from power generators to consumers and networked intelligence, is referred to as a smart microgrid [1]. Smart microgrids offer a communication interface for data and services and a virtual representation of the energy components they contain. This follows the general concept of cyber-physical systems (CPS) [3] and is grouped under cyber-physical energy systems (CPES) in the energy context. The survey in [4] highlights the concepts and challenges surrounding CPES. The high dynamics and intense networking between smart grids require standards in practical implementation to make numerous heterogeneous infrastructures interoperable. These standards must meet CPES requirements, which include reliability, security, robustness against unexpected states, and adaptability, should there be subsystem failure. The emergence of smart grids from the networking of several microgrids is inhibited by two factors. The first is the legal framework and charges in some countries, which reduces the economic attractiveness of decentralized electricity supply. In Germany, for example, reduced grid fees and the introduction of net metering [5] could make the use of public electricity grids more appealing for smart grids. The second challenge is insufficient standardization. Without CPES standards, smart microgrids will remain isolated solutions. The significance of standards is clear when considering the forecast of 50 billion devices in the Internet of Things (IoT) by 2020 [6], while being cognizant that CPS and CPES also make up these \"things\". The addition of CPS functionality to existing systems and devices is also known as retrofit. These procedures are often used to turn buildings into so-called smart buildings, which are less energy-intensive, with the ideal goal of realizing zero-energy buildings [7]. Improved energy efficiency is achieved by saving, redistributing, and storing energy, as well as by intelligent building use; for example, by occupancy detection using CPES sensors [8] or Wi-Fi probe-based detection [9]. The components of a smart building are [10] sensors, actuators, controllers, a central unit, an interface network, and a smart meter for communicating with the utility company. If the smart building also has components for generating and storing energy, the result will be a smart microgrid. According to [4], the four main research areas surrounding CPES are modeling energy systems, energy efficiency, energy resource management, and energy control. The use cases of this work relate to energy efficiency. An energy management system (EMS) helps organizations reduce energy costs, act more sustainably, reduce carbon emissions, and implement a well-structured energy policy [11]. In addition, non-energy benefits, such as better working conditions and lower costs of raw materials, maintenance, and repairs can be gained [12]. An EMS often includes energy monitoring software, which acquires energy data from meters, sensors, and other sources, and presents it in a visualization software system. Realized as CPES, these sensors and meters can also be used for other purposes and non-energy benefits in smart grids. Our work deals with such networked energy sensors. By examining CPES standards, we aim to contribute to overcoming a common challenge in planning submetering: the more measuring points the submetering includes and the shorter the measuring intervals, the more information can be obtained from the data.