Intelligent power distribution system

Description of the technology

The research group of computer engineering and networks of computers of the University of Alicante has developed an innovative system that enables the distribution and management of the electricity in a more efficient and rational way. The system uses artificial intelligence techniques to predict energy demand and taking optimal decisions about sources of supply to be used and prioritizing those preferential consumption centers. These decisions are based on rational criteria, such as the characteristics of the consumption centers, the expectations of supply, demand characteristics and previous experiences. This technology allows to reduce consumption and optimize the operation of the electric system. It means greater energy efficiency and a considerable reduction in costs. It is also suitable for environments where power fluctuates or is scarce.

Specifications

The distribution and energy management system is structured in three subsystems listed below: 1. Decision-making unit. Processing algorithms and strategies to optimize energy management. 2. Power unit. It regulates the power supplied. t is composed by the inputs and outputs of the network. 3. Control Unit. Manages the behavior of consumption centres so that they conform to available energy supply. Each of these units, physically, is implemented through two different types of devices called modules and agents. The modules must be installed grouped with at least one decision-making module, while the agents are autonomous and can be deployed at any point in the installation. These devices are connected to the different elements of the system (power generators, consumption centers and storage devices) following an elaborate design established by the research group. The decision making units are capable of communicating among themselves and with the different agents in order to distribute the available power between the centres of consumption through distributed and scalable negotiation protocols. The actions to be performed by each of the modules and agents agreed between them using smart negotiation protocols. The data to make these decisions comes from the criteria of optimization, power data available in the centers of production and the energy requirements of the centres of consumption. The system is able to operate automatically, and depending on the circumstances, define sources of energy more cost-effective, optimal, use temporary storage of energy and prioritize, centers as well as enable or disable power consumption devices. Also the system can learn from the corrective measures introduced by the users, and information from external sources, such as the Internet (weather forecast, singular dates) to implement even more refined management strategies.

Main advantages of its use

• Can learn and receive information from external resources to make preventive decisions and optimize its performance.
• It guarantees the energy supply to consumption centres that are vital or have priority and allows to reduce energy consumption through selective shutdown of equipment and systems.
• Lets customize the system and adapt to the energy needs of the users or complex patterns.
• Optimizes the distribution of electrical energy in an environment using intelligent management of each of the elements of the system.
• Reduces costs to prioritize domestic energy sources and reducing the demands to the public distribution network. You can also set other savings mechanisms as the demand for energy when the electric rate is reduced.

Applications

• Corporate and institutional buildings, industrial buildings and homes.
• Installations of medium size, such as malls, industries, hospitals, University campuses, housing developments, sports and recreation, transport stations.
• Machinery, vehicles, robots.
• Networks of very high power, as well as those of high and medium power for transport and supply large areas, industrial areas, municipalities and urban areas.