Decentralized Microgrid Control via Multi-Agent Systems
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Solution Overview
Problem
Conventional power systems face challenges such as high pollution, centralized nature, inefficiency, and variability in renewable energy sources, which hinder widespread deployment of distributed microgrids due to complexities in managing variable power sources and loads.
Innovation Solution
A decentralized software and hardware architecture utilizing multi-agent systems (MAS) and model-predictive control (MPC) to harmonize power production and consumption across independently owned and operated microgrid sources and loads, enabling distributed intelligence and fine-grained coordination through networked computer systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If distributed power systems with renewable energy sources are deployed, then pollution is reduced and environmental sustainability is improved, but the variability of power output and system complexity increase
Solution Approach 1:
The patent segments the power system into multiple independent microgrids, each capable of autonomous operation. This segmentation allows individual microgrids to manage their own variable renewable energy sources locally, reducing the impact of variability on the broader system while maintaining overall sustainability benefits.
Solution Approach 2:
The patent implements dynamic control mechanisms that allow microgrids to adapt their operation in real-time based on varying renewable energy output and load conditions. This dynamic adjustment enables the system to handle power variability while maintaining stability and reliability.
2Reliability
If microgrids with independently owned power sources are implemented, then decentralization and resilience are improved, but the complexity of coordinating multiple variable sources and loads increases
Solution Approach 1:
The patent enables each microgrid to autonomously manage its own power sources and loads through local control systems. This self-service capability reduces the need for complex centralized coordination while maintaining system reliability, as each microgrid can independently balance its own supply and demand.
Solution Approach 2:
The patent implements feedback mechanisms where microgrids continuously monitor their own operational status and adjust their control strategies accordingly. This distributed feedback approach simplifies coordination complexity by enabling autonomous decision-making at the microgrid level while maintaining overall system resilience.
3Productivity
If conventional centralized power systems are used, then power generation efficiency is maintained, but pollution increases and system vulnerability to disasters increases
Solution Approach 1:
The patent divides the centralized power system into multiple distributed microgrids, each capable of efficient local power generation using renewable energy sources. This segmentation eliminates the pollution associated with fossil fuel-based centralized generation while maintaining overall system productivity through coordinated microgrid operation.
4Object-affected harmful factors
If renewable energy sources are used to reduce carbon emissions, then environmental sustainability is improved, but the cost of building and operating the system increases
Solution Approach 1:
The patent segments the large-scale renewable energy system into smaller, modular microgrids that can be deployed incrementally. This segmentation reduces upfront construction costs by allowing phased implementation while maintaining environmental sustainability through the use of renewable energy sources in each microgrid.
Solution Approach 2:
The patent enables microgrids to operate autonomously and manage their own resources efficiently, reducing the need for expensive centralized infrastructure and operational overhead. This self-service capability lowers both construction and operating costs while maintaining low carbon emissions through renewable energy utilization.
Data Source
AI summary
A computing architecture that facilitates autonomously controlling operations of a microgrid is described herein. A microgrid network includes numerous computing devices that execute intelligent agents, each of which is assigned to a particular entity (load, source, storage device, or switch) in the microgrid. The intelligent agents can execute in accordance with predefined protocols to collectively perform computations that facilitate uninterrupted control of the microgrid.


