Energy consumption can account for up to 50% of production costs in some industries^[1]; therefore, BigDa Solutions' mission is to improve energy efficiency in the industrial sector. With a team of energy technology experts, BigDa Solutions has a no-code philosophy that can be customised to the specific needs of each project.

The main objective is to support industries in designing and implementing the best technological solution to reduce their carbon footprint, optimise their consumption and make better energy decisions based on the objectivity of their own data.

To that end, BigDa Solutions has designed its own four-stage workflow methodology:

• Study and energy consulting of the situation of each company.
• Consumption digitalisation to gather energy data from meters and sensors.
• Data quality filtering and energy variable analysis.
• Consumption forecasting for past and future scenarios to improve energy performance.

Not every company has the same data, exact needs, or level of digitisation, which is why implementing these phases is customised and adapted to the needs of each client. BigDa Solutions' methodology is carried out through custom-made projects to improve energy efficiency according to the needs of each industry.

Thus, energy technology is at the core of all projects: BigDa Solutions masters in offering the best solution for each case, but how do we use technology to help companies save energy?

Firstly, we cooperate with the companies to determine their needs, objectives and production processes. In this initial study and consultancy stage, we analyse the quantity and quality of the data available to the company to define a plan for digitisation, monitoring and prediction of energy consumption that meets its energy objectives.

Nobody knows their needs and operation better than the companies themselves. BigDa Solutions works hand in hand with each business to move towards a model based on Industry 4.0, in which sustainability and productivity are improved through the efficient use of energy resources.

For the predictive monitoring and management of energy usage, BigDa Solutions has developed BEMP: an adaptive power platform that does not require specific knowledge of big data, coding or artificial intelligence. This is a technological solution designed so that any company worker can make energy decisions in an agile, straightforward way based on their real data.

Getting started on the digitalisation of energy data

The second stage is to assess the company's digitisation situation, i.e. the availability of energy data, where several scenarios can be found:

1. Suppose the company starts from scratch in terms of data automation. In that case, the first step is to deploy a digitisation network based on machine-to-machine communication with technologies such as LoRaWAN. Before this, the digitisation capacity of its energy meters is analysed.
2. If the company has data, its quality must be analysed. A large volume of data is not synonymous with usefulness. Feeding artificial intelligence models with erroneous or incorrectly filtered data will be bound to be inaccurate and misleading. In such a case, a diagnosis of energy data quality and state is carried out to see if any adjustments are needed to capture and digitise the data. This information can be integrated and centralised in ways such as via an API or connection to the SCADA.
3. The company has advanced digitisation but needs to deepen or refine energy data acquisition.

Industry-specific technology Solutions

At this point, a proof of concept (PoC) is developed, i.e. a project roadmap is defined to analyse if and how much the company can improve its energy efficiency through BEMP. Each project starts step by step, with different stages, strategies and technology combinations depending on the objectives.

For example, if a specific production line consumes the most energy, it could be the priority starting point. BigDa Solutions' solutions allow consumption to be disaggregated to address key priority areas. It is also possible to start from a specific energy variable, which can be scaled to other consumption. It is recommended not to go from a degree of 0 digitisation to 10 but to work in phases and parts to achieve the most optimal energy efficiency scenario.

The path to forecasting for a smart energy management

Digitalisation, monitoring and data filtering allow BEMP to implement a predictive energy management system. Thus, the next step is developing predictions based on energy variables in artificial intelligence predictive models (forecasting) that allow us to simulate scenarios both in the past and in the future. This enables energy efficiency improvement studies and financial provisions for energy costs.

For the development of predictive models, the target variable to be predicted (forecast target) is first defined, and then the variables (attributes) that affect the target are specified. BEMP makes it possible to create multiple variables for the same target by combining different attributes and thus be able to analyse how each of the variables affects and interferes with each other. This way, predictive models are built based on genetic algorithms designed by BigDa Solutions so that users can create and use their own predictive models without programming, thus complying with BEMP's no-code philosophy.

Energy management is centralised in BEMP, which combines all the relevant energy information in a single platform. This product offers reports generation and alarm settings to know what is happening at all times regarding energy within the company. It can also integrate the information with other software or business process management tools to provide energy decisions based on data. For example, all the information BEMP collects can be visualised in Business Intelligence tools such as Power BI.

How do I know if BigDa Solutions is for my company?

BigDa Solutions and its energy platform BEMP target energy-intensive industries and energy consultants.

As a scalable and customisable service, BEMP offers multiple possibilities, regardless of the energy needs of an industry, to achieve an intelligent energy consumption that boosts its efficiency and competitiveness through forecasting. Find out now how to start forecasting your company's energy consumption.

Talk to one of our energy experts

^{[1] Source: Asociación de Empresas con Gran Consumo de Energía}