Brightspark Custom Web Application

An advanced management and forecasting platform for the energy sector.

Type
Web Application
Sectors
IoT, Electricity, Utility
Technologies
PHP, MySQL, JavaScript, Code Igniter

How we transformed raw data into an interactive Electricity Management Tool

Brightspark Online provide various services relating to electricity, with the main focus being reducing consumption costs, understanding consumption profile and improving operations.

Elemental Web Solutions was approached by Brightspark Online to develop an online web application, to allow their clients to get real-time access to various aspects relating to their power consumption and to provide these clients with various tools to allow them to understand their requirements and how they can become more energy efficient.

One of the requirements was to make the tool look really slick and present data in a user-friendly way through the use of various graphs and visual dashboards.

Brightspark would typically spend a lot of time doing manual reports, calculations and forecasts, which they wanted to be automated.

THE SOLUTION

Due to the complexity of electricity, how it is billed, how the various tariffs and rules relating to each tariff work, Elemental had to undertake a vast learning exercise. Once completed, the entire project was scoped out with the client.

The web application firstly allowed Brightspark to manage various things like tariffs, costs, clients, etc.

Brightspark’s clients would then be able to login to the system and firstly interact with a highly graphical dashboard allowing them to get an accurate summary of their power consumption profile.

They would then be able to view further graphs and reports allowing them to see their daily, monthly and yearly consumption and costs, tariff related information; their actual spend versus their budget / target.

A variety of tools were also provided to allow the client to forecast their costs based on increased tariffs and consumption, to manage various branches within their organisation, etc.

Another Successful project

The web application firstly reduces the time that Brightspark need to spend when manually create reports, forecasts, etc… as this is fully automated.

The online system allows their clients to get an accurate and powerful view of all the information related to their electricity consumption and profile, which they can use to make informed business decisions.

Powerful graphs and other tools allow them to forecast, plan and identify areas of improvement within their business. Therefore reducing costs and making them more efficient.

ANOTHER SUCCESSFUL PROJECT

Each Brightspark customer has a dedicated and interactive dashboard where they can view their consumption metrics and highly valuable data in an appealling way on a single screen..

Did you know though, that some of these dashboards summarise millions of data readings over a large period of time. That's right! Millions of data records.

With the dashboard needing to be quickly and easily accessible at all times, one thing we couldn't have was a slow loading dashboard (due to the enormity of data that was needed to aggregate the data for the graphs). To combat this we combined technical things such as database indexing, optimsed database queries and highly efficient code to get and load the data in a split second.

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CHALLENGES

One of the platform's most powerful features is its ability to forecast energy costs, including consumption costs across various tariffs. While this may seem straightforward in theory, it presents significant challenges in practice. Firstly, accurate forecasting requires a large dataset of consumption data, ideally spanning at least a year. This is essential because many businesses experience seasonal fluctuations, with periods of higher consumption than others.

Secondly, different electricity tariffs calculate monthly costs in diverse ways, making accurate forecasting even more complex. By incorporating parameters such as changes in consumption and potential tariff cost increases, we successfully developed a model that can predict future costs across multiple tariffs. This provides business owners with crucial information to make informed decisions about whether to switch tariffs.