# Novel Internet of Things Platform for In-Building Power Quality Submetering
## 1 Introduction
### Power Quality Literature Survey  
Automated PQ analysis entails the following stages: detection, segmentation, and characterization of the PQ event. There exists a very extensive body of knowledge related to these stages, where the most advanced techniques have been applied, from the area of signal processing to artificial intelligence. See for example the latest works presented in [13; 14; 15]. The most advanced PQ analyzer in the market today, which costs between \(\ell 4\),\(495\) and \(\ell 13\),\(460\)[16], provides three-phase high-performance PQ monitoring with built-in EN 50160 or IEEE Std. 1159 monitoring, statistics and reports. These analyzers can be divided between a portable solution for load studies and PQ audits, or to be fixed for \(24/7\) continuous long-term monitoring. As can be seen, most of these analyzers present good characteristics, but they are usually very expensive, consequently only considered to be connected at the entrance of the facility. While all major events can be captured, this could result in excessive data from non-critical events. Manual analysis methods are expensive, time-consuming, and error-prone. Thus, designing a system that can analyze, condensing and interpreting voluminous raw data so that levels can be assessed against limits, as well as can be easily expanded, would become the most significant challenge in the present PQ measurement arena. Besides the professional PQ meters, plug-in voltage quality (VQ) recorders that detect and record different disturbances are available at prices around \(\ell 900\). Consequently, a low-cost system able to observe PQ data on a continuous basis is needed. In recent years, different works have been published in energy metering fields at the customer level, and an excellent review can be found in [17], where the current state of the art of energy management through Intrusive Load Monitoring (ILM) and Non-intrusive Load Monitoring (NILM) is presented. Another interesting paper presents an advanced IoT-based system for intelligent energy management in buildings [18]. The proposed system extends existing approaches and integrates cross-domain data, such as building data, energy production, energy prices, weather data and end-user behavior, to develop daily and weekly action plans for end-users with actionable, customizedinformation. Considering both concepts, in [19] the residential energy scheduling optimization problem is solved using two-stage Mixed Integer Linear Programming (MILP) considering the customer preferences and appliances' specifications. Similarly, but applied in a particular case, in [20] a testbed is designed where each housing unit is equipped with sensors, actuators, smart plugs, smart meters, and Unified Home Gateway (UHG). The paper also shows results from implemented applications in Demand Response Management (DRM), energy management, home automation, dynamic pricing, and home security. However, no information regarding PQ is traditionally measured. Paper [21] describes a gamification framework that aims to achieve greater energy conservation in public buildings. The framework leverages IoT-enabled low-cost devices to improve energy disaggregation mechanisms, providing energy use and--consequently--wastage information at the device, area and end-user level. Another example is found in [22] where a smart-grid testbed at the Singapore University of Technology and Design (SUTD) is developed which is able to monitor, analyze, and evaluate smart-grid communication network design and control mechanisms, and test the suitability of various communications networks for both residential and commercial buildings. One of the main reasons behind these works is to make users aware of their electricity consumption to reduce their carbon footprint and eventually save money on their electricity bills. An interesting point to be added to the existing resources is recording information about PQ, as it is also a source of losses, meaning that energy consumption can also be achieved with an appropriated PQ within an installation.