Cost-Effective Remote Energy Monitoring using the ESP8266 NodeMCU
Arthur James Swart
Arthur James Swart, Central University of Technology, South Africa.
Manuscript received on 28 March 2019 | Revised Manuscript received on 09 April 2019 | Manuscript Published on 18 April 2019 | PP: 974-979 | Volume-7 Issue-6S March 2019 | Retrieval Number: F03990376S19/2019©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Energy monitoring is critical to ensure the sustainability of a renewable energy system. It further makes possible the introduction of energy conservation, reduction and optimization. To achieve this for an off-grid system, or for numerous research sites, requires the use of remote energy monitoring where various parameters may be visually reviewed from anywhere and anytime using an operational internet connection. Various commercial products exist to fulfil this need that may prove expensive and cumbersome to use. The purpose of this paper is to present a cost-effective remote energy monitoring system using the ESP8266 NodeMCU. The research site was the city of Cape Town that is known for its Mediterranean climate. Results indicate that a simple data logging interface circuit, a ESP8266 NodeMCU, an ADC, a 3.3 V regulator, a LED lamp and a reliable WiFi network is all that is required to monitor the energy yield of a pico-solar system along with the ambient temperature. Watt Hours per day produced over a 6-month period by a 10 W PV module is shown along with the cloud cover percentage. Average Watt hours per day for July and August was 39,3 Wh/day and for October and November it was 51,8 Wh/day. It is recommended that more of these cost-effective remote energy monitoring systems be deployed across a number of research sites to enable the collection of reliable empirical data that can be used to optimize the design of off-grid solar energy systems.
Keywords: Cloud Storage; Data Logging; PV; Renewable.
Scope of the Article: Remote Sensing