Flexible Base Load Mapping for Power Plant Dispatch Decisions
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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 demand with the shorter maintenance intervals and increased maintenance costs caused by peak-firing, leading to potential revenue losses and inefficient maintenance schedules.
Innovation Solution
A dispatch advisor system that generates a flexible base load map to help operators select optimal operating conditions by partitioning the map into segments based on firing temperature, inlet guide vane position, and fuel temperature, considering market conditions, to maximize revenue while managing maintenance and operational efficiency.
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 increased, but parts-life consumption increases and maintenance interval is shortened
Solution Approach 1:
The system dynamically adjusts gas turbine operating parameters (inlet guide vane position, firing temperature, compressor outlet temperature) based on real-time market conditions and maintenance schedules. The dispatch advisor continuously optimizes the balance between power output and parts-life consumption by modifying operational parameters rather than simply increasing or decreasing output capacity.
Solution Approach 2:
The invention changes physical operating parameters of the gas turbine (inlet guide vane angle, firing temperature, compressor outlet temperature) to achieve optimal trade-offs between power output and component life. By adjusting these parameters, the system can operate at higher power levels while minimizing parts-life consumption, or extend maintenance intervals while maintaining adequate power output.
2Productivity
If gas turbines are peak-fired frequently within maintenance interval, then extra power is produced, but maintenance costs increase due to shortened maintenance schedules
Solution Approach 1:
The dispatch advisor performs preliminary calculations and predictions of parts-life consumption based on planned peak-firing operations. By forecasting the impact of peak-firing on component life before executing operations, the system can proactively adjust maintenance schedules and operational parameters to avoid excessive maintenance costs while still capturing revenue opportunities from peak demand.
Solution Approach 2:
The system incorporates feedback loops that continuously monitor actual parts-life consumption against predicted consumption, market conditions, and maintenance schedules. This feedback enables real-time adjustments to operational parameters and maintenance planning, optimizing the balance between power production and maintenance cost avoidance.
3Loss of energy
If plant operators exercise peak-fire mode conservatively to preserve parts-life, then maintenance costs are reduced, but revenue opportunities are lost
Solution Approach 1:
The dispatch advisor dynamically determines the optimal level of peak-firing based on real-time market conditions, predicted parts-life consumption, and maintenance schedules. Rather than using static conservative or aggressive peak-firing strategies, the system continuously adapts operational parameters to maximize revenue while staying within acceptable maintenance cost thresholds.
Solution Approach 2:
The system changes operational parameters (inlet guide vane position, firing temperature, compressor outlet temperature) to enable more aggressive peak-firing when market conditions are favorable and predicted parts-life consumption is acceptable, while maintaining conservative operation when maintenance costs would be excessive. This dynamic parameter adjustment resolves the contradiction between revenue maximization and maintenance cost control.
Data Source
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AI summary
A dispatch advisor (18) to assist in selecting operating conditions of a power plant (10) that maximizes operational revenue is described. The dispatch advisor (18) obtains a base load map (42) for operating the power plant (10) to meet base load power demands. The base load map (42) includes a primary base load operating space (56) for attaining target plant power output and efficiency, and an expanded base load portion (58) for attaining higher plant power output and less than optimal efficiency. Both the primary base load operating space (56) and the expanded base load portion (58) associate power output and efficiency values of the power plant (10) that result from a subset of operational parameter values for operating the power plant (10) during base load. The dispatch advisor can transform the flexible base load map (42) into one or more visualizations (88) describing the revenue possibilities associated with operating the power plant (10) based on operating values and attained power output and efficiency.