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 energy startups developing load forecasting solutions.
Global Startup Heat Map: 5 Top Load Forecasting Solutions
The 5 energy startups you will explore below are chosen based on our data-driven startup scouting approach, taking into account factors such as location, founding year, and relevance of technology, among others. This analysis is based on the Big Data & Artificial Intelligence (AI)-powered StartUs Insights Discovery Platform, covering over 1.3 million startups & scaleups globally.
The Global Startup Heat Map below highlights the 5 load forecasting solutions our Innovation Researchers curated for this report. Moreover, you get insights into regions that observe a high startup activity and the global geographic distribution of the 227 companies we analyzed for this specific topic.
Sensewaves – Energy Management
Load forecasting is an important tool in any energy management system (EMS). Forecasting energy demand takes into account the energy usage of individual customers and weather forecasts to calculate separate predictions for residential, commercial, and industrial customers. Such forecasting enables utilities and energy suppliers to serve their customers better. To this end, energy startups are working on artificial intelligence (AI)-based solutions that offer load forecasting to optimize operations.
Sensewaves is a French startup that provides analytics intelligence for the energy sector. The startup’s Adaptix Grid platform forecasts loads and localized production at high spatial and temporal resolution. The solution integrates field chronological data and weather forecasts to enable multi-scenario predictions of load, voltage congestion, and other grid parameters. The platform also detects electricity theft and estimates the lifespan of grid assets for predictive maintenance.
Hive Power – Smart Grid Software-as-a-Service (SaaS)
Smart grids allow two-way energy transactions, enabling customers to sell energy generated by onsite renewables to the grid. This makes the system robust to demand fluctuations and leads to cost savings for the customers. Accurate load forecasting further helps grid operators determine when and how much electricity to source from renewables. Energy startups are working on solutions that combine demand-side management (DSM) and renewable energy source integration.
Hive Power is a Swiss startup that offers a SaaS platform for smart grid analytics. The solution uses AI to monitor resource distribution and analyze the usage behavior of consumers. This enables utilities and suppliers to forecast energy data for power loads and energy production. Moreover, the solution offers tools to optimize energy trading and prevent grid violations.
Amperon – Smart Meter AI
Predicting load forecasts at the level of individual households is challenging because of a large number of unknown factors that shape a household’s energy consumption. Smart meters record granular details of energy consumption to provide energy-saving insights to customers and data on consumer behavior to electricity suppliers. This enables short-term load forecasting (STLF) solutions at the level of individual buildings. By forecasting load for the next hour to the next week, energy providers make better decisions and can guarantee reliability.
The US-based startup Amperon provides smart meter AI for utilities. AmpGrid, the startup’s forecasting platform, uses machine learning to provide 15-day market-wide load forecasts. The platform’s coincident peak model enables grid operators to improve the deployment of demand response capacities. The startup also offers forecasting solutions for weather and retail.
Nectaware – Electricity Demand Prediction
Predicting electricity demand at a fine resolution is a complex task and, in addition to energy supply and price, meteorological and socio-economic factors also contribute to demand. The decentralization of energy brings new opportunities for finer electricity demand prediction. Energy startups combine consumption data from smart meters and predictive algorithms to provide energy-saving inputs for consumers and resellers alike.
Italian startup Nectaware provides an electricity demand prediction solution. E4SIGHT, the startup’s cloud-based platform, predicts energy consumption for each meter on the grid based on real-time consumption data, weather inputs, and social media sentiment analysis. The solution improves energy demand forecasting for resellers, minimizing the difference between declared and real energy consumption. E4SIGHT also provides real-time alerts related to the consumption threshold.
Dexter – Load Forecasting-as-a-Service
In energy trading, the power imbalance is the gap between the amount of energy a company is contracted to generate or consume and what it actually generates or consumes. Failing to match these two parameters requires utilities to pay imbalance penalties in a process that repeats every trading period. However, energy startups are working on AI-based load forecasting-as-a-service solutions to help utilities make better predictions and avoid penalties.
Dexter is a Dutch startup that offers solutions to help energy retailers reduce power imbalances. The startup employs machine learning in short-term trading to offer load forecasting-as-a-service. The solution helps large scale energy customers avoid imbalance penalties and save time via automation. Dexter’s forecasting solutions also extend to energy asset and energy portfolio optimization.
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