Generator Bank Load Management for Drilling Efficiency
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Solution Overview
Problem
Oil and gas drilling operations face challenges in managing power efficiently due to the high consumption and generation requirements, with existing systems struggling to optimize power distribution across generators to maximize efficiency.
Innovation Solution
A system comprising a generator bank with load-sharing capabilities, a computation component that calculates and optimizes the efficiency-capacity ratio of individual generators, and motors, allowing for dynamic adjustments to achieve higher overall efficiency by altering the operating capacity of generators based on calculated efficiency gains.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If generators operate at lower capacity to maintain reliability, then system stability is improved, but overall efficiency deteriorates
Solution Approach 1:
The system dynamically adjusts generator operating points in real-time based on load conditions, transitioning from static fixed-capacity operation to dynamic optimization. The computation component continuously calculates optimal operating points and adjusts generator capacity allocation, enabling the system to adapt to changing conditions and maintain high efficiency across varying load levels while preserving stability through controlled transitions.
Solution Approach 2:
The system changes the operating parameters of generators by adjusting their capacity output levels. Instead of operating at fixed capacity points, generators are dynamically repositioned to optimal operating points calculated based on efficiency curves and current system conditions. This parameter adjustment allows the system to operate generators in their most efficient ranges while maintaining reliable power supply.
2Power
If more generators are activated to meet power demand, then power availability is improved, but fuel consumption increases
Solution Approach 1:
The system optimizes the operating parameters of active generators by adjusting their capacity output to match optimal efficiency points. Rather than simply adding more generators at fixed operating points, the computation component calculates the most efficient capacity allocation across available generators, changing their operating parameters to minimize fuel consumption while meeting the required power demand.
Solution Approach 2:
The system implements feedback control by continuously monitoring generator performance, load conditions, and efficiency metrics. The computation component uses this feedback to dynamically adjust generator capacity allocation, comparing actual efficiency against target efficiency levels and making real-time adjustments to optimize fuel consumption while maintaining power availability.
3Loss of energy
If generators operate at varying capacity levels to optimize efficiency, then fuel consumption is reduced, but system complexity increases
Solution Approach 1:
The computation component serves as an intermediary that centralizes the complex optimization calculations and decision-making logic. Rather than requiring complex control mechanisms within each generator, the computation component performs the sophisticated efficiency optimization centrally and translates it into simple capacity adjustment commands for individual generators, managing system complexity in a centralized manner.
Solution Approach 2:
The system enables generators to self-adjust their operating capacity based on instructions from the computation component. Each generator autonomously modifies its output level in response to control signals, performing the actual efficiency optimization action without requiring complex external control mechanisms, thereby reducing overall system complexity while achieving fuel savings.
Data Source
AI summary
Systems and methods for operating a series of generators configured to provide power to a motor or motors. Generators generally operate at different efficiency levels depending on the operating capacity. A computation component can analyze the current efficiency of the generators and determine if there is an alternative power distribution among the existing generators that would result in a more efficient operation of the system.