Home Energy platform upgrade – new Widget graphs

Home Energy platform upgrade lets users create their own dashboards

We have upgraded the Meniscus Calculation Engine (MCE) on our free-to-use Home Energy monitoring platform. We are phasing out of the existing Silverlight dashboard as it only runs on Internet Explorer over the next couple of months.

Example of an MCE real-time widget

This graph will update every 2 minutes.

New Widget graphs and getting your API key

The widgets let you easily create your own dashboards that you can configure yourselves.

To use the widgets you will need your API key which is the first 16 characters of the email address that you used to create your account with us. Please note a couple of things.

  • THE API key is READ ONLY
  • if you make these widgets publicly available then your API key will be visible
  • If you would like to change your API key please send a mail to [email protected] and quote the e-mail address you use for your Home Energy account

    To create the widgets

    1. Go to the widget page
    2. In the “Create Widget – Enter API key” tab enter your API key
    3. Click Connect to Server
    4. In the “Create Widget – Meter Options” tab select the Items you want to display
      • For the Real time data use Electricity use – channel 1. This is the RAW data type with units of W
      • For the Half hour aggregated data for the three main channels then use Electricity use – channel 1 – HH. This is the CALC aggregated W data converted into kW
      • You can add any other Item that you want to display
    5. Select the Output type – I.e. line graph
    6. Add Item to the List
    7. In the “Create Widget – Date and Time options” tab select the time option you want. Don’t use too long a period as it will take a long long time to upload!
    8. In the “Create Widget – Update Options” tab select how often you want the widget updated – so for a two minute update enter 120 seconds

    When you are ready – select the Output HTML. This will generate the iframe code that is can be pasted into any HTML web page to generate the graph displayed.

    Create the Dashboard

    Follow these steps to create an HTML dashboard with the widgets you have created. This will give you a lot more visibility for the Home Energy platform.

  • When you have created the Output HTML that you want click the “Create Dashboard” tab
  • Click on “Add Widget” and copy the HTML iframe. This will create a new widget and you can add up to 4 different widgets on the one page and move them as you want
  • Click on “Add Header” to add a simple header to the page
  • Click on Copy HTML to create a copy of the dashboard as an HTML page. If you open this page then you can view the widgets you have created
  • For more information on the MCE widgets click here

    See an example of the MCE widget dashboard

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    Multiple Regression Analysis Lowers Fleet Costs

    Do you have a fleet management system? Does this calculate how much fuel is being consumed by each vehicle and by whom? This is very important information and very often nothing, or not enough, is being done with your information.

    With the constant fluctuation in fuel prices, it can be difficult for transport companies to budget their fuel costs as accurately as possible. Many factors contribute to the total fuel cost.

     

    lower fleet fuel

    Multiple Regression Analytics lower fleet fuel

    Lowers Fleet Costs

    Meniscus has used these factors to model the cost of fuel for transport companies. Through Multiple Regression Analysis, an 11% reduction in total fuel costs could be achieved, by reducing the number of idling hours of drivers and their harsh driving scores by 20%.

    Multiple Regression Analysis allows a correlation between a dependent variable and many independent variables. The analysis provides the coefficients for each variable giving an equation in the format of y = β0+ β1X1+ β2X2 +…+βnXn. From the established regression equation, it is then possible to use the independent variables to estimate the dependent variable, in this case, fuel cost. Multiple Regression Analysis also allows us to determine the contribution each individual independent variable makes to the dependent variable value. We are in the early stages of analysing transport data and believe it is a sector that would see real benefit from our MCE (Meniscus Calculation Engine).

    We are not saying you shouldn’t use the system you have. All we are saying is that maybe we can do more with data and help you become even more cost efficient. In other words, get more from your system and by analysing the data produced to reduce costs, giving you more time to focus on other pertinent areas of your business.

    Watch this space for new amazing on developments.

     

    The Unspoken, Gaps in Data

    Over the years we have come across a number of problems when it comes to receiving data. One of the common problems is where there is are gaps in data. This can cause problems for the energy management system that you may be using, and make your job even more difficult and time-consuming than it already is.

    When there is no data. What do you do?

    The most used and straight forward method is to carry forward values. Meaning you’re taking a previous value and bringing it forward to fill the gap. This can work when you have a single value missing and it may be sufficient depending on the scope of your needs.

    Unfortunately, there is no right or wrong method of filling gaps, as it is always a compromise. The method you choose is dictated by the quality of the data you require versus the effect to attain it and the importance of the impact that the choice of the method makes to your results.

    Using the MCE (Meniscus Calculation Engine) we have come up with a system that allows us to extract the data from your Energy Management System (or any other system that you may use) and pull it into MCE. This is where we set up calculations that automatically identify the data gaps.

    There are various different methods filling gaps in data and there is no right or wrong method of filling gaps, as it is always a compromise. The following methods are just some of the ways you could fill the gaps in data:

    • Carry values forward. Meaning you’re taking the previous value and bringing it forward to fill the gap.
    • You could use data that was received at the same time. Data from a day, week or year before, and use that to fill the gap.

    Other more complicated methods involve the following:

    • Taking averages of points in previous years for the same point. Or doing more with season + day type averages. Each day has an associated day type (weekend + weekday for a simple example) and season of the year. This allows averages to be built that are more reflective of seasonal variations and usage and are less prone to suffering from the impact of more extreme individual values.
    • Back-filling data by Interpolation using incrementing data sets. For example, if your incremental counter ended on 100 units at the start of the gap and started on 180 units at the end of the gap that means we used 80 units. And, 80 units is over a 4-day period, so therefore it’s 20 units per day. This we feel to be the most accurate method as the data is there and is accurate as it is actually what has been utilised.

    Using MCE (Meniscus Calculation Engine), we extract the data into our systems where the calculations are set up to automatically identify the data. E-mailed Management reports are generated by MCE and the information is sent to you or directly to the Data Collector to ensure that the gaps are filled with the correct data.

    Mind the Gap

    Mind the Gap

    Process Based Energy Management for the Water Industry

    This White Paper sets out a methodology for using the Meniscus Calculation Engine (MCE) as a bottom up process centric Energy Monitoring and Targeting based application for use in the Water Industry.

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