Microgrid Dispatch Control for Renewable-Priority Power Balancing
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Solution Overview
Problem
Microgrids and power plant networks face high energy costs due to reliance on fossil fuels, and existing control systems are complex and inefficient in managing distributed energy resources, particularly with the integration of intermittent renewable sources.
Innovation Solution
A system and method utilizing a dispatch controller with a programmable function block to manage microgrid networks by determining power demands, operational constraints, and adjusting energy resource outputs to optimize power distribution, prioritizing renewable energy sources and reducing fuel consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If dispatchable energy resources (fossil fuels) are used to ensure reliable power supply in microgrids, then energy security and reliability are improved, but energy costs increase significantly
Solution Approach 1:
The patent combines multiple energy resources (renewable and non-renewable) into a unified microgrid system that operates as an integrated whole. The controller merges power from solar panels, wind turbines, diesel generators, and battery storage systems to meet load demands, achieving both reliability and cost efficiency through resource diversification.
Solution Approach 2:
The system dynamically changes operational parameters by adjusting the mix of energy sources based on real-time conditions. The controller modifies the proportion of renewable versus fossil fuel usage, battery charging/discharging rates, and generator output levels to optimize both reliability and cost effectiveness under varying load and resource availability conditions.
2Use of energy by moving object
If renewable energy resources are incorporated to reduce energy costs, then energy cost decreases, but system complexity increases due to intermittent nature
Solution Approach 1:
The patent introduces a centralized controller as an intermediary that manages the complexity of coordinating multiple intermittent renewable sources with load demands. This controller acts as a mediator between unpredictable renewable generation and variable load requirements, simplifying the overall system management through automated decision-making algorithms.
Solution Approach 2:
The system performs preliminary actions by pre-charging battery storage systems when renewable energy is abundant and conditions favor storage. The controller anticipates future energy needs and prepares energy reserves in advance, reducing the immediate complexity of real-time balancing while maintaining cost efficiency.
3Productivity
If battery energy storage systems are added to balance load-generation, then energy efficiency improves, but device complexity and initial cost increase
Solution Approach 1:
The battery energy storage system serves multiple functions simultaneously: it stores excess renewable energy, provides backup power during shortages, stabilizes voltage fluctuations, and enables islanded operation. This multi-functionality justifies the added complexity by delivering diverse benefits from a single component type.
Solution Approach 2:
The controller implements self-service by automatically managing battery charging and discharging operations based on real-time system conditions. The system autonomously decides when to charge from renewables, when to discharge to meet loads, and how to prioritize energy sources, eliminating the need for complex manual intervention while maximizing energy efficiency.
4Productivity
If a centralized controller manages multiple DERs and loads, then power distribution optimization improves, but control system complexity increases
Solution Approach 1:
The control system is segmented into modular functional blocks, each responsible for specific tasks such as power flow management, battery control, generator management, and load prioritization. This segmentation allows the complex control function to be divided into manageable, independently configurable modules that can be developed and maintained separately while working together as an integrated system.
Data Source
AI summary
A system and method for controlling a microgrid network comprises a plurality of distributed energy resources that supply electrical power to a plurality of loads. A controller coupled to the microgrid network and to the distributed energy resources and the loads includes a processor and a memory configured to execute a dispatch controller function block. The function block is configured to cause the processor to receive a total power demand of all the loads coupled to the microgrid network and at least one operational constraint corresponding to the plurality of distributed energy resources and cause the processor to determine using the operational constraint if there is sufficient electrical power available from the plurality of distributed energy resources to power the loads. The function block is further configured to determine which of the plurality of available distributed energy resources are required to be adjusted to supply electrical power to the plurality of the loads, causing the controller to adjust the electrical power output by each of the distributed energy resources.