One of the most significant advantages of IoT technology is its ability to predict energy consumption. Energy providers can measure and compare power consumption with weather conditions, time of day, and other data using a cloud-based monitoring platform to determine usage trends across a region.
FREMONT, CA: Energy providers are turning to IoT-enabled energy storage systems to improve renewable energy stability. Excess renewable energy, such as solar energy on a clear day, is processed for later use when demand is higher, or frequency varies. According to research, the global energy storage market for renewable energy grid integration is projected to rise 33 percent annually from 2017 to 2021. These storage systems are critical for allowing renewables to be more flexible, allowing them to be incorporated into the main power grid without causing imbalances.
Forecasting Demand with IoT Energy Monitoring
One of the most significant advantages of IoT technology is its ability to predict energy consumption. Energy providers can measure and compare power consumption with weather conditions, time of day, and other data using a cloud-based monitoring platform to determine usage trends across a region. Companies may paint a detailed picture of energy demand by comparing it to forecasted weather data and taking measures to meet it before it becomes expensive. IoT data will help renewable energy providers set targets for their renewable storage systems, resulting in more efficient use of renewable energy sources that compensate for renewable power generation's intermittency.
How Artificial Intelligence and Smart Grids Enhance Energy Demand Flexibility
Smart grid capabilities use two-way digital communication to track and respond to local changes in usage. There are already infrastructure projects in place around the world to update electric grids with smart grid capabilities. Smart grids employ various devices to determine grid reliability, automatically report outages, detect and recover from substation faults, reroute power around problems and perform other complex functions that increase performance while lowering energy demand and costs.
Artificial Intelligence (AI) is becoming an obvious partner for energy IoT and smart grids in achieving energy efficiency as its capabilities expand. AI systems will implement predictive algorithms to balance grids and determine the reliability of output and consumption figures using granular energy consumption data generated by IoT infrastructures and smart grids.
This information provides customers with a more detailed picture of their energy use and enables energy suppliers to provide incentives to increase demand-side flexibility. Providers may reduce the need for emergency power purchases or investments in peaker plants by controlling peak demand through incentive schemes and assisting grid operators in balancing intermittent renewable energy production.
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