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Discover 5 Top Predictive Analytics Solutions impacting Energy Companies

Curious about new technological advancements in the energy industry? Explore our analysis of 727 global startups & scaleups and learn how their predictive analytics solutions impact energy companies!

Staying ahead of the technology curve means strengthening your competitive advantage. That is why we give you data-driven innovation insights into the energy industry. This time, you get to discover 5 hand-picked predictive analytics solutions impacting energy companies.

Out of 727, the Global Startup Heat Map highlights 5 Top Predictive Analytics Solutions impacting Energy Companies

The insights of this data-driven analysis are derived from the Big Data & Artificial Intelligence-powered StartUs Insights Discovery Platform, covering 2 093 000+ startups & scaleups globally. The platform gives you an exhaustive overview of emerging technologies & relevant startups within a specific field in just a few clicks.

The Global Startup Heat Map below reveals the distribution of the 727 exemplary startups & scaleups we analyzed for this research. Further, it highlights 5 startups that we hand-picked based on criteria such as founding year, location, funding raised, and more. You get to explore the solutions of these 5 startups & scaleups in this report. For insights on the other 722 predictive analytics solutions for the energy industry, get in touch.

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Interested in exploring all 700+ predictive analytics solutions for the energy sector?

 

Myst AI provides Energy Demand Prediction

In modern homes and offices, there is a wide range of systems that consume energy at large scales, such as heating and lighting. The load on energy grids caused by these are not always constant and change with time of day, day of the week, etc. This irregular energy consumption cycle creates a challenge for the energy industry which is transitioning to clean energy sources. To this end, startups are offering analytical software for forecasting energy demand.

US-based startup Myst AI develops a machine learning solution to create accurate energy demand forecasts. The startup’s forecasting solution mines data from untapped, curated datasets related to weather, energy markets, and human behavior to improve model performance. This allows utility operators, retail energy providers, and renewable energy generators to reduce pricing volatility and lower costs through electricity load prediction.

Samawatt offers Power Generation Forecasts

The energy industry is increasingly decarbonizing energy generation through the implementation of wind, solar and hydroelectric power. However, energy production from renewable energy is inconsistent compared to fossil fuels as they are largely subject to weather conditions. To make renewable energy more reliable, startups are creating algorithms that predict the production capability of renewable energy generators.

Swiss startup Samawatt creates machine learning algorithms to predict wind and solar energy production. Their algorithms use deep learning and optimization to provide forecasts on hourly granularity for a 72-hour horizon while maintaining a very low daily mean average percentage error (MAPE). The insights gained through their software-as-a-service (SaaS) platform allows renewable park managers to perform dispatch analysis to control the grid imbalance costs.

PowerMarket develops a Solar Energy Mapping Software

Governments and companies across the globe are developing solar farms to generate large-scale clean energy at large scales. Energy grid operators rely on these solar farms and their data to distribute and balance energy load while reducing the overall cost of electricity. Hence, incomplete or inaccurate data significantly affects transmission and power generation costs, which is why startups are developing solutions that map solar installations.

UK-based startup PowerMarket provides solar analytics and insights powered by satellite and weather data. Their solar monitoring solution maps all solar installations around the world along with their power generation capabilities. This enables energy companies, traders, and financial institutions to query, aggregate, and visualize the data to monitor the impact of distributed solar energy and reduce the monetary volatility of solar energy.

Delfosim provides an Asset Failure Prediction Platform

The generation of oil and gas (O&G) requires high levels of monitoring and control to prevent blowouts or spills. This could not only harm workers but also cause extensive damage to facilities and the surrounding environment. For this reason, startups provide solutions to monitor the condition of critical equipment and offer predictive alerts for preemptive measures.

Brazilian startup Delfosim develops a platform for real-time monitoring and analysis of energy utilities. The Delfos I.M. platform leverages all available operational data within organizations to optimize asset performance. It uses the unstructured data recorded by event loggers, thus requiring no additional hardware to monitor operating conditions.  The solution also offers failure prediction alerts for blowout preventers (BOP) critical components which enables O&G operators and maintenance teams to optimize maintenance planning.

The Predictive Company offers Energy Efficiency Analytics

A significant amount of energy consumption is caused by the inefficient use of constantly running heating, lighting, and ventilation inside large offices and buildings. In addition, energy waste in under-occupied buildings has increased due to more employees working from home. Most offices typically monitor their energy consumption based on the total energy used by the building as a whole rather than on the individual sources of power consumption. This results in poor energy management policies, which is why startups are creating artificial intelligence (AI)-based solutions that analyze all systems that consume energy in a building.

Spanish startup The Predictive Company develops a software-as-a-service (SaaS) solution for energy efficiency analytics. The startup’s software uses AI and digital twins to provide a precise and personalized prediction of a building’s energy needs. Additionally, their AI controls heating and ventilation (HVAC) machinery for optimal energy consumption. This provides building managers a convenient method to reduce their expenditure on electricity while improving their corporate social responsibility (CSR).

Discover more Energy Startups

Energy startups such as the examples highlighted in this report focus on demand-side management, predictive maintenance, and wide area monitoring. While all of these technologies play a major role in advancing the energy industry, they only represent the tip of the iceberg. To explore more energy technologies, simply get in touch to let us look into your areas of interest. For a more general overview, you can download our free Energy Innovation Report to save your time and improve strategic decision-making.

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