Microgrid Dispatch Engine for Offline and Real-Time DER Control

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Solution Overview

Problem

Current microgrid management systems face challenges in optimizing peak shaving, energy arbitrage, and grid services due to complex technical and financial issues, leading to underutilization of resources and poor return-on-investment, with existing solutions requiring large computing infrastructure and manual processes.

Innovation Solution

A deterministic multi-stage optimal dispatch engine system using hardware-agnostic intelligent control algorithms to manage and optimize microgrids, comprising a server, controller, and processor, which performs optimizations in offline and online modes to determine optimal peak shaving limits and grid service recommendations, reducing operational expenses and creating revenue opportunities.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual processes are used to manage DERs, then operational flexibility is maintained, but optimization efficiency and productivity are reduced

Engineering Contradiction:

Improveoptimization efficiencyVSAvoidmanual management process

Core Design Contradiction:

ProductivityVSExtent of automation

Solution Approach 1:

The DERMS automatically manages distributed energy resources through intelligent control algorithms that autonomously optimize peak shaving, energy arbitrage, and grid services without requiring manual intervention, thereby improving productivity while maintaining operational flexibility through configurable parameters

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical management processes with electronic computational systems that use intelligent control algorithms to automatically dispatch and control DERs, transitioning from human-operated manual processes to automated electronic optimization systems

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If large computing infrastructure is deployed to optimize peak shaving and energy arbitrage, then optimization capability is improved, but device complexity and cost increase

Engineering Contradiction:

Improveoptimization capabilityVSAvoidcomputing infrastructure complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The optimization process is divided into discrete stages (peak shaving optimization, energy arbitrage optimization, grid services optimization) that can be executed sequentially or in parallel, allowing complex optimization tasks to be broken down into manageable computational segments that reduce overall system complexity

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The DERMS platform provides multiple optimization functions (peak shaving, energy arbitrage, grid services) through a single integrated system, eliminating the need for separate computing infrastructures for each function and reducing overall device complexity while maintaining comprehensive optimization capability

Inventive Principle:

Principle #6Universality (Multi-functionality)

3Reliability

If microgrids operate in island mode to improve power supply security, then reliability is improved, but loss of connection to wide-area grid resources increases

Engineering Contradiction:

Improvepower supply securityVSAvoidloss of grid resources

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

The microgrid system dynamically switches between grid-connected and island modes based on real-time operational conditions, allowing it to maintain reliability through autonomous island operation when necessary while recovering access to wide-area grid resources when conditions permit, thereby resolving the contradiction between reliability and resource access

Inventive Principle:

Principle #15Dynamics

4Productivity

If deterministic multi-stage optimization is implemented to reduce operational expenses, then cost efficiency is improved, but computational time and processing complexity increase

Engineering Contradiction:

Improvecost efficiencyVSAvoidcomputational time

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system performs preliminary optimization calculations in advance to determine optimal dispatch strategies, allowing it to pre-compute peak shaving limits and energy arbitrage opportunities before real-time operation, thereby reducing computational time during critical decision-making moments while maintaining cost efficiency

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The deterministic multi-stage optimization is executed periodically at scheduled intervals rather than continuously, with each stage performing specific optimization tasks at predetermined times, which reduces overall computational time and processing load while maintaining cost efficiency through regular optimization updates

Inventive Principle:

Principle #19Periodic action

Data Source

PatentUS12413093B2Engine system and methods for dispatching and controlling distributed energy resources

Publication Date: 2025.09.09 EATON INTELLIGENT POWER LTD

AI summary

An engine system and methods for dispatching and controlling a plurality of distributed energy resources, e.g., a plurality of microgrids, involving: a server; a controller configured to operably couple with the server and the plurality of DERs; and at least one processor configured to operably couple with the server and the controller, the at least one processor configured to operate the server and the controller in an online mode and an offline mode, whereby at least one of forecast information and real-time information is providable, operational expense is reducible, and at least one new revenue generation avenue is establishable.