• Energy Research

Distributed energy resources have demonstrated their potential to mitigate the limitations of large, centralized generation systems. This is achieved through the geographical distribution of generation sources that capitalize on the potential of their respective environments to satisfy local demand. In a microgrid, the control problem is inherently distributed, rendering traditional control techniques inefficient due to the impracticality of central governance. Instead, coordination among its components is essential. The challenge involves enabling these components to operate under optimal conditions, such as charging batteries with surplus solar energy or deactivating controllable loads when market prices rise. Consequently, there is a pressing need for innovative distributed strategies like emergent control. Inspired by phenomena such as the environmentally responsive behavior of ants, emergent control involves decentralized coordination schemes. This paper introduces an emergent control strategy for microgrids, grounded in the response threshold model, to establish an autonomous distributed control approach. The results, utilizing our methodology, demonstrate seamless coordination among the diverse components of a microgrid. For instance, system resilience is evident in scenarios where, upon the failure of certain components, others commence operation. Moreover, in dynamic conditions, such as varying weather and economic factors, the microgrid adeptly adapts to meet demand fluctuations. Our emergent control scheme enhances response times, performance, and on/off delay times. In various test scenarios, Integrated Absolute Error (IAE) metrics of approximately 0.01% were achieved, indicating a negligible difference between supplied and demanded energy. Furthermore, our approach prioritizes the utilization of renewable sources, increasing their usage from 59.7% to 86.1%. This shift not only reduces reliance on the public grid but also leads to significant energy cost savings.

Satisfying energy demand has become a global problem that is on the rise due to population growth, infrastructure deterioration, a decline in fossil fuel sources, and high costs for investment, among others. Smart grids, in addition to those challenges that they have at the level of energy generation, have other management challenges derived from the great diversity of components that make them up, such as energy storage systems (batteries, capacitors, etc.), the different types of consumers (controllable, non-controllable loads) and prosumers (electric vehicles, self-sustaining buildings, micro-grid, etc.), among others. Consequently, a distributed control problem is presented, mainly oriented to the coordination of its components. A possible solution is to achieve the participation of each component when conditions are more favorable, such as prioritizing production with renewable energy sources, or taking advantage of prosumers so that they can meet local demand, among other things. Therefore, new strategies with a distributed approach such as bio-inspired emergent controls are necessary. The objective of this work is the specification of an emergent control approach to coordinate a smart grid. This approach allows the coordination of the energy supply in various operating scenarios. The results obtained demonstrate a perfect synchronization between the different smart grid components (agents), prioritizing renewable energy sources, regardless of the operational context (for example, in cases of failures, unsuitable environmental conditions, etc.). TRUE pub