Rundown Blending Scheduling for Tankless Refinery Components
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Solution Overview
Problem
Existing multi-period blending optimization systems are not designed to optimize blending operations for components without storage tanks, which is a challenge faced by refineries like those in Eastern Europe.
Innovation Solution
The development of a multi-period blending optimization system that explicitly accounts for event sequencing, including static and rundown components, to optimize blending operations for components without storage tanks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multi-period blending optimization systems are designed for components with storage tanks, then inventory management and blending optimization can be achieved, but the system cannot optimize blending operations for components without storage tanks
Solution Approach 1:
The optimization system is designed to handle both components with storage tanks and rundown components (without storage tanks) within a unified framework. The system universally manages inventory constraints for stored components while simultaneously optimizing the immediate blending and shipment scheduling for rundown components, making the system adaptable to diverse refinery configurations without requiring separate systems
2Productivity
If the system optimizes blending operations for rundown components, then profitability increases through better scheduling, but the complexity of event sequencing and constraint management increases
Solution Approach 1:
The blending optimization problem is segmented into discrete events (blending events, shipment events, receipt events) that can be individually scheduled and optimized. Each event is treated as a separate unit with specific constraints, allowing the system to manage complexity by breaking down the overall scheduling problem into manageable segments that can be optimized independently and then integrated
Solution Approach 2:
The system dynamically adjusts the scheduling of blending events for rundown components based on real-time constraints and objectives. The optimization model dynamically determines the timing and sequencing of events to maximize profitability, adapting the schedule to changing conditions rather than using fixed predetermined schedules
3Reliability
If the system meets all shipment commitments and quality specifications, then customer satisfaction is ensured, but cost minimization becomes more challenging
Solution Approach 1:
The optimization system incorporates feedback loops that continuously monitor shipment commitments, quality specifications, and inventory levels. The model uses this feedback to adjust blending recipes and scheduling decisions, ensuring that all constraints are met while optimizing for cost minimization. The system evaluates the impact of each decision on constraint satisfaction and adjusts accordingly
Data Source
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AI summary
A blending control system optimizes refinery operations. Included are an input module enabling user specification of inventory information including at least one rundown component, and user specification of refinery product commitments, and a processor routine executable by a computer and coupled to the input module. The processor routine, in response to the user specification, sequences refinery operations into a schedule that matches refinery commitments with inventory and unit rundown operations, wherein the refinery operations include blending events. The processor routine determines the duration and timing of each rundown component for each blend in blend event periods.