Open-Source Energy Monitoring Hardware

OpenEnergyMonitor hardware: raspberry pi, emonTX
 and emonGLCD

In our smart microgrid laboratory at the Alpen-Adria-Universität Klagenfurt we need to be able to measure energy flows at different places in the network. Our criteria had been to be able to measure power, current, and voltage with adjustable measurement time intervals. The meters should be networked wirelessly with a visualisation possibility via an embedded device or a web page. In order to implement appropriate measurement strategies (for example measuring with a time-triggered architecture) the system should be fully programmable, in other words open-source. 

emonCMS web-app visualization tool

To meet this requirements we decided to use the OpenEnergyMonitor. It provides a metering board emonTx, which is based on Arduino and communicates to some base station. This can be either a own-built base station emonBase from OpenEnergyMonitor or the nowadays trendy Raspberry Pi. All necessary software is provided and easy to use. The OpenEnergyMonitor also provides an energy visualisation tool called emonCMS, which can be installed on the Raspberry Pi. It can be used for processing, logging and visualizing energy. Like the other software also the emonCMS is open source.

Links:

• Raspberry Pi, a credit-card-sized embedded computer running Linux
• OpenEnergyMonitor, open-source energy monitoring tools
• A. Monacchi, D. Egarter, W. Elmenreich. Integrating Households into the Smart Grid. Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, Berkeley, CA, May 2013.
• W. Elmenreich, G. Bauer, and H. Kopetz. The time-triggered paradigm. In Proceedings of the Workshop on Time-Triggered and Real-Time Communication Systems, 2003.

Evolving Non-Intrusive Load Monitoring

Our paper Evolving Non-Intrusive Load Monitoring by Dominik Egarter, Anita Sobe and Wilfried Elmenreich has been accepted for the conference track EvoEnergy (Evolutionary Algorithms in Energy Applications) of the EvoApplication (16th European Conference on the Applications of Evolutionary Computation) 2013, taking place in Vienna form 3rd to 5th of April.

Basic principle of the ON/OFF time genome appliance
detection. Given is the total power consumption over
time. The goal is to deduce the on/off times of devices
(colored blocks) that add up to the measured power profile.

Non-intrusive load monitoring (NILM) identifies used appliances in a total power load according to their individual load characteristics. In this paper we propose an evolutionary optimization algorithm to identify appliances, which are modeled as on/off appliances. We evaluate our proposed evolutionary optimization by simulation with Matlab, where we use a random total load and randomly generated power profiles to make a statement of the applicability of the evolutionary algorithm as optimization technique for NILM. Our results shows that the evolutionary approach is feasible to be used in NILM systems and can reach satisfying detection probabilities.



Dominik Egarter, Anita Sobe, Wilfried Elmenreich,   Evolving Non-Intrusive Load Monitoring,   EvoApplication 2013,   16th European Conference on the Applications of Evolutionary Computation, April, 2013

Keeping an eye on my Photovoltaic System

Guest Post by Benjamin Steinwender

At my home place we have recently installed two photovoltaic systems with a total peak power production of 15 kW. From the first moment my dad confronted me with this idea, I wanted to record time series data of any measurement signal I could obtain from the system. Most promising was the fact of an included web server on the power converter.

Storage

Storing time series data over long periods can lead to high disk usage. Fortunately, I came across RRDtool (round-robin-database tool) - http://oss.oetiker.ch/rrdtool/ when I installed a monitoring solution for a FEM simulation server cluster and its UPS some time ago.

RRDtool stores data in a circular buffer so that its file size remains constant over time. However, older data will be overwritten after some time. The idea is to store the data in so-called round-robin archives with a consolidation function applied in order to keep the interesting properties. In my special application, the following archive sizes are used:

•     10080 x 1 minute samples for 7 days
•     11760 x 5 minute maximum & average values for 40 days, 20 hours
•     4704 x 30 minute maximum & average values for 98 days
•     2604 x 2 hour maximum & average values for ~ 7.2 months
•     2678 x 1 day maximum & average values for ~ 7.3 years

This gives plenty of storage with a reasonable file size of roughly 420 kB per data series.

Presentation

To ease the data presentation and acquisition, cacti http://www.cacti.net/ is used. This web-based application (favorable a Linux web server + PHP and MySQL required) is based on the RRDtool and provides Data Input Methods and Graph Templates as well as a nice graphical user interface to view the recorded data. Cacti primarily supports data acquisition via SNMP queries, but the power converter does not provide such interface. However, custom scripts can also be used.

Acquisition

Therefore, a PHP script has been written to fetch the current web page of the power converter and a simple HTML DOM (document-object-model) parser http://sourceforge.net/projects/simplehtmldom was used to extract the required field values. The tools run on a 24/7 NAS server where a cron job invokes the cacti poller (and thus the script) once every minute.

Results

Data acquisition is now successfully running since about 1 month. The total power production from last week can be seen in the following figure. The light-blue area represents the power output of the smaller (5 kW) system and the stacked dark-blue area is the power output of the larger (9.8 kW) system. From the data series we can even infer on the weather – the figure indicates that is was sunny at the weekend, cloudy on Monday, Tuesday and Friday and rainy on Wednesday and Thursday.

Need motivation to save energy? - Go for social media competition!

There is a large potential by closely monitoring the energy consumption of your appliances in a comprehensive overview. Being aware of the largest energy consumers and the general energy demand over the day, one can optimize his/her household to reduce power consumption or to shift consumption to a daytime where the demand/supply situation is better.
However, what is the motivation to do so?
As it can be seen in other situations (like riding a bike vs. taking the car, etc.), saving a few bucks might not be enough motivation to effectively change the consumers' behavior.
Austin Montgomery, University of Waterloo gives a possible solution to this problem in his video "Making the Smart Grid Smarter with Social Media": make it a competition on social networks!



By the way, this is my favorite video from the IEEE SmartGridComm 2011 video contest. Check http://www.ieee-smartgridcomm.org/video.html for the other nominated clips.

Google and Microsoft back away from online power metering

Google PowerMeter and Microsoft Hohm are online web applications that enable consumers to analyze their energy usage and provide energy saving recommendations. The basic idea is to have an  application in the cloud that is using predictions, smart meters, and energy monitoring devices in order to provide you with information and recommendations about your home's power usage.

While Google's application came for free, Microsoft's tool was planned as a product to create revenue. Now, both projects are discontinued. PowerMeter was retired by Google in September 2011, joining the club of Google Wave and Google Health. In Google's official blog, the reason is only briefly stated as "efforts have not scaled as quickly as we would like", which leaves room to some interpretation. Microsoft's Hohm will be discontinued on May 31, 2012 due to a lack of consumer uptake.

This is sad, since a comprehensive user interface with web integration is a major asset in comparison to existing powermeters with their limited LCD displays and gray buttons. Remember, we are talking about an appliance that is basically planned to enter every household, not just being a tool for geeks. We certainly need a convenient user interface here.
With the bailout out of Google and Microsoft, two important drivers of innovation will be missing, on the other hand this might open the market for new developments. Apple, having filed a patent on a smart-home energy management dashboard system seems to be planning something, but it's still unclear what we will get.

Video on Google's PowerMeter when they were still enthusiastic