Increasingly, energy management is becoming a topic of great social importance. In today’s post, I will explain how IoT (Internet of Things) together with technology Artificial Intelligence (AI), is improving energy management solutions for both the energy provider and the consumer.
Industrial Consumers – Building Management Systems
Industrial consumers are often faced with an ultimatum. How can they drive forward growth strategies without having to comprise on their commitment to environmental sustainability? The answer is by implementing Smart Building Management Systems.
Large industrial consumers may struggle to monitor network wide energy consumption trends due to their large scale of operations and complex structure. IoT technology offers large enterprises the ability to monitor energy usage easily and efficiently.
Smart Building Management Systems use IoT powered sensors to collect data across complex infrastructure networks. Using AI capabilities, this data is analysed automatically allowing inefficacies in usage patterns to be easily identified and targeted. This real-time reporting allows for smarter energy management decisions, reduced energy bills and a lower carbon footprint for the organisation.
IoT powered sensors also have the capability to coordinate with existing energy systems and supply networks. Energy usage can be adjusted automatically according to environmental conditions. This could be factors such as room occupancy, temperature and level of natural light. In this way, building occupants may not even notice a reduction in energy consumption in their environment. As IoT powered smart Building Management Systems are rolled out across extensive networks the potential reductions in network overall energy consumption is enormous, benefiting the enterprise both socially and finically.
Efficient Grid Management
The use of IoT sensors along distribution channels allows energy providers to easily monitor demand and consumption patterns. This allows providers to easily adjust supply along power lines. This can be done dynamically in accordance with real-time demand. The risk of oversupply in networks is therefore reduced, resulting in a decrease in energy wastage.
Due to the real-time nature of IoT sensor reporting, providers can understand in great detail the consumption habits of consumers. This information can be understood geographically, helping providers to plan targeted network expansions and upgrades, leading to a higher quality network infrastructure.
AI also plays a key role here. It is not feasible for technicians to manually adjust power requirements as often as demand changes. Through the compilation of consumption data, smart grid management systems can automatically adjust voltage along power lines. This allows suppliers to predict consumption changes so the grid is always prepared to supply the energy requirements of customers.
Smart Meters, the future for domestic consumers
IoT powered smart meters constantly collect energy consumption data and send it to both to service providers and customers. This allows suppliers to understand, in great detail, the consumption habits of their consumers. Suppliers can therefore adjust network capacities accordingly.
For the domestic consumer, sophisticated integrated IoT systems allow the consumer to understand the energy consumption of every device in the home. This helps to identify power-hungry appliances, reducing energy wastage. It is also helpful to the domestic consumer to understand, through detailed reporting, how a household may be able to save money on energy bills by changing consumption habits.
Conclusion
The use of IoT sensors and AI is the future of energy management. Large industrial consumers have the most to gain here. A network-wide smart energy management solution will provide lucrative savings for any large organisation, whilst allowing them to fulfil promises of environmentally sustainable practice. Domestic consumers also win through lower energy bills. IoT technology allows energy providers to be far more dynamic and flexible in their supply planning.
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