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Smart home devices currently available on the market can be used for remote monitoring and control. Energy management systems can take advantage of this and deploy solutions that can be implemented in our homes. One of the big enablers is smart plugs that allow the control of electrical resources while providing a retrofitting solution, hence avoid...
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The key advantage of power utility-owned smart meters over rotating-disc meters is the ability of transmitting electrical energy consumption data to power utilities’ remote data centers. Besides enabling the automated collection of consumers’ electrical energy consumption data for billing purposes, data gathered by smart meters and analyzed through...
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... Thus, DR can be defined as end users intentionally changing their consumption pattern (period of the day, instantaneous demand or total consumption). Based on that, the traditional passive consumer can turn into an active and empowered one based on generation ability and demand flexibility if adequately supported by adequate information and communication and technologies (Fernandes et al., 2014;Gomes et al., 2019;Gomes et al., 2018;Santos et al., 2020). ...
... Significant advancements have been made regarding energy resource management at the consumer and community levels (Fernandes et al., 2014), load and consumer profiling, demand flexibility and demand response (Faria and Vale, 2011;Ghazvini et al., 2017b), aggregation (Correa-Florez, et al., 2020;Pinto et al., 2011), microgrids (Morais et al., 2010), peer-to-peer transactions , transactive energy (Abrishambaf et al., 2019;Lezama et al., 2019;, electricity markets models and simulation (Pinto et al., 2014;Praça et al., 2003;Santos et al., 2015;Santos et al., 2016;, and strategic market negotiation (Morais et al., 2012;Pinto et al., 2013;Pinto et al., 2016a;Pinto et al., 2016b) in the past years. There have also been advancements in several technologic aspects such as smart metering, the Internet of Things (IoT), different devices enabling the supervision and control of energy loads and assets, such as smart plugs (Gomes et al., 2019;Gomes et al., 2018) and home assistants, and distributed processing using light single-board computers . ...
Europe and, more particularly, the European Union (EU) has been pursuing ambitious goals in terms of energy, with pioneering energy policy pushing for more clean and affordable energy and highly competitive electricity markets. Electricity market design proved to be a challenge since the first models intended for further competition in the sector have been launched. With the increasing use of distributed and renewable-based electricity generation, electricity models became increasingly challenging. Other distributed energy resources, namely demand flexibility, distributed storage, and electric vehicles, are also bringing new requirements for electricity markets and open the way for local electricity markets. Although still an emerging concept, local electricity markets have huge potential, namely regarding increased gathering of the demand flexibility potential and to bring significant benefits to consumers. This chapter addresses the EU vision for electricity markets in the new context and discusses its benefits, risks, and future perspectives, highlighting the most important legislation, and some practical advances and implementations.
... The first version of EnaPlug was proposed in 2017, with application in a refrigerator, according to reference [4], containing an Arduino Mega, an Ethernet Shield, a MAX 485, a power analyzer (CVM-1D), a door opening sensor, external and internal temperature sensors, an internal humidity sensor, and a relay. References [4][5][6][7] highlight the use of the Environmental Awareness smart Plug (EnAPlug) as a solution for application in a research and study centers to enable the study, testing, and validation of methodologies and models for energy management inside buildings. In [6], a new update is proposed that allows access to the operating system, enabling the processing and storage of data with a focus on the possibilities of learning in the consumption profiles and habits of users, in addition to the sharing of information between the different EnAPlugs. ...
... This article proposes the presentation of the EnAPlug hardware with the aim of motivating and stimulating the development of new models and versions for energy management applications and contributing to the improvements of EnAPlug, as this is not a commercial product [7]. Fig. 1 shows the architecture proposed of EnAPlug [4], where: ...
... For RS-485 serial communication [12] between the power analyzer (CVM-1D) and the microcontroller, the MAX485 serial interface was used, which is a low-power transceiver for RS-485 [13]. The microcontroller reads data from the power analyzer, using the MODBUS/RTU protocol [6], and sends it to the MQTT BROKER [7]. EnAPlug sends and receives data, through Publish and Subscribe, using the MQTT protocol [8]. ...
Given the growth of domotics and home automation, there is a need to use smart devices that integrate energy management systems and enable the automation of the environment. Considering the need to study the relationship between the environmental parameters in which the equipment is located and the energy parameters, an Environmental Awareness smart Plug (EnAPlug) is proposed with the application of machine learning (Tiny ML).This article presents a demonstration of EnAPlug applied to a refrigerator for predictions on internal humidity and activation motor for 5 min-ahead prediction on its operation, i.e., turning on or off. The two models for forecasting humidity presented Root Mean Squared Error (RMSE) results of 0.055 and 0.058 and a Coefficient of determination (r2 score) of 0.97 and 0.99, respectively. For the motor activation prediction, the results obtained were an accuracy of 94.74% and 94.84%, an F1 score of 0.97 for OFF, 0.94 for ON for Forecast 1 and 0.97 for OFF and 0.93 for ON for Forecast 2. Although the prototype does not have commercial purposes, what differs from existing smart plugs is the option to store data locally. The results are promising, as it allows for better energy management with implementation of machine learning.
The availability of low-cost smart plugs that measure and control loads has encouraged their use as a research tool to disaggregate end-user loads. While there has been extensive research on the cybersecurity implications, and demand response capabilities, of smart plugs, there has been little investigation of their primary function: Measuring loads. In this study, we analyze the accuracy of power and energy measurements reported by 5 smart plugs from different manufacturers, with a specific focus on the accuracy of the meters when load levels change rapidly, as is often the case with power electronic loads. The study included Belkin, TP-Link, Etekcity, Emporia, and Sonoff smart plugs, with loads switching at frequencies of 0.01Hz to 2Hz, in addition to the steady-state loads often used for testing these devices. Data indicate significant errors in both energy and power measurement when used to monitor highly variable loads. While maximum energy measurement error for the Belkin product never exceeded 1.7%, maximum energy measurement errors were 54–100% for the other 4 brands. Power measurement accuracy was highly dependent on load variability, with all units exhibiting substantial errors when loads varied, even at rates as low as 0.01-0.05 Hz. All units also exhibited reporting delays of 3–6 seconds, with some delays as high as 20 seconds. The large, load-dependent, errors, call into question the use of these devices for research data acquisition, particularly for monitoring highly variable power electronic loads.
At present, the construction market of apartment buildings in the Moscow region is in an active transformation phase. The use of modern technologies has increased the volume of housing construction and reduced the time of commissioning new facilities. With the growing number of proposals in the real estate market, the demand for new buildings remains high. At the same time, buyers’ requirements for the quality of housing have changed significantly. Today’s potential apartment buyer pays attention not only to its basic characteristics and price per one square meter. One of the modern selection criteria is the availability of modern engineering systems, high-tech equipment in residential complexes, allowing to make living in such houses more comfortable and safe, as well as save energy when forming utility bills. The author conducted a study of the complex equipment of apartment buildings with “smart home” (SH) system, showed the main advantages of using various subsystems of SH, formulated proposals that can make more affordable SH technology for ordinary residents. These activities will also allow developers to adjust the approaches to the planning and implementation of their projects for the next 5-7 years to meet modern market requirements.
