FST Graduate Research Topic


Research Topic: AGI Research and Development: Dynamic Load Balancer in Smart Grids
Suggested By: Harris Wang
Last Update: September 28th, 2025

AGI Research and Development: Dynamic Load Balancer in Smart Grids


Constrained Object Hierarchies (COH) provide a neuroscience-inspired theoretical framework for modeling Artificial General Intelligence (AGI). As a flexible and robust foundation, COH supports the representation of general intelligent systems across diverse domains.


Formally, a COH is defined as a 9-tuple:


O = (C, A, M, N, E, I, T, G, D)


Where:



  • C: Components – sub-objects organized hierarchically

  • A: Attributes – state variables describing object properties

  • M: Methods – executable actions associated with components

  • N: Neural Components – adaptive models for learning and inference

  • E: Embedding Neural Component – semantic representation of the COH

  • I: Identity Constraints – rules ensuring object integrity

  • T: Trigger Constraints – event-condition-action rules for dynamic behavior

  • G: Goal Constraints – optimization objectives guiding intelligent behavior

  • D: Constraint Daemons – real-time monitors enforcing system constraints





Based on the COH framework, the modelling process and result of Dynamic Load Balancer in Smart Grids are as follows:


System Description and Significance: Modern power grids require intelligent balancing of electricity supply and demand amid fluctuating renewable generation and consumption patterns. This system's significance lies in enabling efficient integration of renewable energy sources while maintaining grid stability—a critical requirement for sustainable energy infrastructure.


Analysis and Design: The system must coordinate multiple generation and distribution components while responding to real-time changes in supply and demand. Identity constraints encode physical laws of grid stability, while neural components predict load patterns and renewable generation. The hierarchical structure mirrors the physical organization of power grids from generation to consumption.


Modelling Solution:



  • C: {PowerGenerationNodes, DistributionSubstations, ConsumerZones}

  • A: power_generated, power_demanded, grid_frequency, line_capacity

  • M: reroute_power(), shed_non_critical_load(), adjust_generator_output()

  • N: LoadForecastModel, RenewableGenerationPredictor

  • E: Embedding of overall grid stability and stress level

  • I: grid_frequency must remain within strict tolerance (physical stability)

  • T: IF frequency_drops_below_threshold THEN shed_load IN ConsumerZones

  • G: Minimize_cost_of_generation AND Minimize_transmission_losses

  • D: FrequencyStabilityDaemon monitoring grid_frequency


The COH model demonstrates how intelligent infrastructure systems can maintain stability through constraint governance while optimizing performance through adaptive prediction and control.





You may choose this topic and pursue one of the following routes:


📝 Essay



  • Survey existing methodologies for modeling, designing, and implementing similar intelligent systems.

  • Include:

    • Literature synthesis

    • COH framework analysis

    • Critical evaluation of competing approaches




🛠️ Project



  • Design and implement the system using the COH model.

  • Include:

    • System architecture and design

    • Development and testing

    • Demonstration of core functionality




🎓 Thesis



  • Explore COH’s theoretical foundations in depth.

  • Include:

    • Proposed enhancements or extensions

    • Implementation and evaluation

    • Development of an advanced intelligent system grounded in COH principles