Distributed Generator Forecast Control for Utility Ramp Compliance
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Solution Overview
Problem
Distributed generators face challenges in efficiently managing power output due to sudden changes in renewable resource inputs caused by weather events, leading to ramp rate issues that exceed utility company requirements, and existing energy storage solutions are costly and have limited lifetimes.
Innovation Solution
A system comprising a DG master controller that predicts weather events and adjusts power output from distributed generators by correlating performance data from sub-arrays and neighboring systems, using weather sensors and prediction maps to control inverters and energy storage systems in real-time, ensuring power ramp-up and ramp-down rates meet utility requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If energy storage systems are used to compensate for power degradations, then power stability is improved, but system cost increases and lifetime is reduced
Solution Approach 1:
The system performs preliminary actions by predicting weather events before they occur and proactively adjusting DG output power in anticipation of upcoming power degradations. This prevents the need for reactive energy storage compensation, eliminating the associated costs and complexity while maintaining power stability through forecast-based control.
Solution Approach 2:
The DG system serves itself by using weather prediction data to autonomously adjust its own power output without requiring external energy storage systems. The controller monitors predicted weather conditions and self-regulates power generation to meet utility ramp rate requirements, making the system self-sufficient and avoiding additional infrastructure costs.
2Speed
If DG output power is adjusted rapidly to follow renewable resource changes, then power generation responsiveness is improved, but utility ramp rate requirements are exceeded
Solution Approach 1:
The controller performs preliminary power adjustments based on predicted weather events before actual resource degradations occur. By proactively reducing DG output in anticipation of upcoming cloud coverage or wind drops, the system smooths power transitions and ensures ramp rates remain within utility requirements while maintaining responsive power generation control.
Solution Approach 2:
The system uses feedback from weather prediction data and actual power measurements to continuously adjust DG output. The controller compares predicted power changes with actual utility ramp rate requirements and dynamically modifies power generation to comply with utility constraints while responding efficiently to renewable resource variations.
3Productivity
If weather prediction and control systems are implemented, then power production optimization is improved, but system complexity increases
Solution Approach 1:
The controller performs multiple functions using a single integrated system: it receives weather prediction data, processes power optimization calculations, adjusts DG output power, and monitors compliance with utility ramp rate requirements. This multi-functional approach achieves comprehensive power production optimization without requiring separate specialized systems for each function, thereby limiting the increase in overall system complexity.
Data Source
AI summary
A method and apparatus for controlling power production. In one embodiment, the method comprises determining a predicted weather event; determining a predicted power production impact for a distributed generator (DG) array based on the predicted weather event; and controlling power production from one or more components of the DG array to compensate for the predicted power production impact.