| by QBI Solutions

Industrial Energy Management Software

Energy is the driver of human development: from the original provision of heat and light for the first human beings to the enablement of our cutting-edge transportation, manufacturing, computing and communication devices. While energy is instrumental in our lives, it poses serious concerns about the impact of its growing demand both in our environment and our economy. 

The energy industry is responding to this challenge with renewable sources and with the efficient use of the available resources. Citizens, governments, energy providers, technologists, investors and academia are engaged in the quest for producing energy at marginal cost with minimum environmental disruption. 

  • The development of cheaper sources of energy requires lots of innovation, industrial application of this innovation and eventually scale to achieve breakthrough improvements. Wind, solar, marine, gas, hydrogen and battery technologies leverage massive information and analytical power to learn and develop solutions to improve month-by-month the cost of energy.
  • Energy efficiency also rests in the right use of our resources and is benefiting significantly from highly analytical optimization models. 

The proliferation of technologies at different stages of maturity is not free of economical risks that are getting growing attention form all relevant players in this development. The tight management of the economics, the environmental expectations and the customer service is the essence of the renewable generation industry with projected rates of 20% per annum in the mid-term. The risks and opportunities in this growth trajectory cannot be managed with manual approaches anymore. It is the time for big data analytics supporting fast and comprehensive decision-making in complex value chains with multiple stakeholders. 

Is your organization benefiting from the full potential of big data for energy management and energy efficiency? Learn a bit more about why this is a must. 

Big Data and Energy evolve “hand in hand”

Big data approaches and technologies provide the capability to merge and scrutinize large amounts of data from different sources. It presents the energy sector a huge opportunity to not only solve emissions and energy inefficiency issues, but also improve management strategies in all fronts (engineering, procurement, logistics, operation and maintenance, commercialization, administration). 

Household, industrial and commercial users consume energy differently. Many factors are in play ranging from number of loads to sources of energy. Deciphering energy use patterns is the foremost relevant step towards energy efficiency and energy management. 

The following graph depicts the different value fronts of big data in the Energy industry: 

Fig 1: Advantages of Big Data in the Energy Sector - Source 

Digital solution based on advanced analytics bring lots of optimization opportunities and risk mitigation in the management of energy assets. Any area benefiting from data integrity, learning from modeling of root-causes, fast visualization of problems to be solved, or process automation is subject to being improved through advanced analytics. Just a few examples:

  • Seamless and efficient accounting and invoicing based on data integrity
  • Central and visual management dashboards for remote operations
  • Digitally enabled and fully automated on-site management processes
  • Procurement processes based on actual performance vs. just on features
  • Deep learning in the maintenance and operation of assets
  • Real-time balancing of distribution networks

Impact in Renewable Energy Segment

The strong link between Energy and Analytics is particularly strong in the case of renewable generation. Experts still find it difficult to tell the amount of power that a solar module will contribute on a particular day. Wind and solar energy are intermittent and unpredictable by nature and this can result in a big liability to the grid. 

The wind may not blow as expected during some days. Clouds may cover the sky. If renewable energy is to be more meaningful to the grid, there must be a way of quantifying and timing the energy output from these sources. Big data plays an irreplaceable role here. 

Renewable energy is now a worthy contributor to the grid thanks to a combination of data analytics, weather data, machine learning, and satellite data. Acceptance of solar energy on a wider scale is now on the horizon because of this technology. Consider the following examples of what big data has meant in the development of the entire renewable generation industry: 

Weather Forecast

Prediction of weather conditions is one remarkable application area for big data. Do you remember a few years ago when Google announced plans to operate solely on solar? Well, they spearheaded the industry by creating a detailed interactive map for all states in the US aiming at pursuing peak efficiency, balancing between conventional sources and renewables, and designing infrastructure accordingly. 

Maintenance 

Maintenance of physical infrastructure of solar and other renewables has perpetually been a challenge because of their dispersed and scattered locations. Some farms hold thousands of modules over a large area, making maintenance a treacherous and expensive undertaking.  Monitoring based on data analysis can be instrumental in detecting anomalies in real-time for continued operation. Big data can help monitor the condition of turbines, solar modules and other components through their digital twins. As long as there are data loggers and sensors in the field, the energy firm doesn’t need to have a large maintenance team to monitor obscured areas, dirt, and wear of motor among other anomalies. 

Site Selection 

Big data also plays a critical role in choosing a site for a solar farm or wind energy site. It is normal for an investor to sit back and decide whether to continue or decommission after a few decades. This is a big investment, so any decision must be backed by credible data. Big data covering historical performance, maintenance costs, expected costs and so forth helps investors make this important decision. 

Virtual Power Plants 

Energy management took an interesting twist after the entry of big data. It used to be a dream –that one could control the energy from a renewable source using a computer and software-, but it has now become reality. The concept of a virtual power plant is simply the use of software to manage several energy generating sources. The virtual power plant is an excellent energy-saving method because it manages energy demand from different customers collectively and helps handle possible network failures. 

Conclusion 

Across the energy sector, big data is causing a kind of disruption never witnessed before. Business models have a chance to adapt to new ways of handling energy, from generation to consumption. Organizations that are using the available techniques are enjoying lower installation and operational costs. With the widespread adoption of big data in energy tools, these costs are likely to down even further and make renewables more acceptable.

Reach us to learn how we can actualize big data for energy management and energy efficiency aspirations of your firm.

Data & Optimization