Power Plant Dispatch Advisor for Peak-Firing Revenue Trade-Offs
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Solution Overview
Problem
Power plants using gas turbines face challenges in maximizing operational revenue due to the need to balance peak power demand with the accelerated wear and maintenance costs associated with peak-firing, which can lead to shortened maintenance intervals and increased service agreement charges.
Innovation Solution
A dispatch advisor system that generates a flexible base load map to help operators select optimal operating conditions for gas turbines, taking into account capacity remuneration mechanisms, market conditions, and parts-life consumption. This system includes interactive visualizations that allow operators to manipulate data and select operating conditions that maximize revenue.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If gas turbines are peak-fired above base capacity to meet peak demand, then power output is improved, but parts-life consumption increases and maintenance interval shortens
Solution Approach 1:
The system changes operational parameters by providing a flexible base load map that shows multiple operating points (different fuel temperatures, IGV positions, firing temperatures) allowing operators to select conditions that balance power output with parts-life consumption, rather than always operating at maximum capacity
Solution Approach 2:
The system incorporates feedback by calculating and displaying revenue metrics that account for both power generation and maintenance costs, allowing operators to see the financial impact of different operating decisions and adjust accordingly
2Productivity
If gas turbines are peak-fired often within maintenance interval, then extra power output is achieved, but maintenance costs increase due to shortened maintenance interval
Solution Approach 1:
The flexible base load map acts as an intermediary tool that translates complex relationships between operating conditions, parts-life consumption, and maintenance costs into visual representations, helping operators make informed decisions about peak-firing strategies
Solution Approach 2:
The system performs preliminary calculations of revenue and maintenance cost implications before operators make operating decisions, allowing them to anticipate the financial consequences of peak-firing actions and plan accordingly
3Loss of energy
If plant operators exercise peak-fire mode conservatively to preserve parts-life, then maintenance costs are reduced, but revenue opportunity is lost
Solution Approach 1:
The system introduces dynamics by allowing flexible adjustment of operating parameters within defined boundaries, enabling operators to adapt to changing market conditions while managing parts-life consumption, rather than using fixed conservative operating modes
Solution Approach 2:
The flexible base load map serves multiple functions simultaneously: it displays power output, efficiency, fuel consumption, and revenue metrics, allowing operators to evaluate trade-offs across multiple dimensions in a single tool
Data Source
AI summary
A dispatch advisor to assist in selecting operating conditions of a power plant that maximizes operational revenue is described. The dispatch advisor obtains a base load map for operating the power plant to meet base load power demands. The base load map includes a primary base load operating space for attaining target plant power output and efficiency, and an expanded base load portion for attaining higher plant power output and less than optimal efficiency. Both the primary base load operating space and the expanded base load portion associate power output and efficiency values of the power plant that result from a subset of operational parameter values for operating the power plant during base load. The dispatch advisor can transform the flexible base load map into one or more visualizations describing the revenue possibilities associated with operating the power plant based on operating values and attained power output and efficiency.