Optimal on-off scheduling for intermittent pumping wells under grid-connected pv systems

Area of Science:

• Energy Engineering
• Artificial Intelligence
• Petroleum Engineering

Background:

• The
• dual carbon
• goal necessitates integrating renewable energy in oilfields.
• Intermittent wind-solar power generation conflicts with stable oil well energy demands, causing low green electricity use and high curtailment rates.
• Existing methods struggle with efficient green energy utilization in oilfield operations.

Purpose of the Study:

• To develop an optimization approach for oil well operation scheduling that couples photovoltaic power fluctuations with intermittent pumping technology.
• To minimize grid electricity consumption per unit of liquid production while maximizing green electricity share.
• To improve the efficiency and accuracy of optimization algorithms for renewable energy integration in oilfields.

Main Methods:

• A multiobjective optimization model was formulated to balance grid electricity consumption and green energy utilization.
• Run-length encoding was used to map on-off schedules into constrained binary sequences, reducing the solution space.
• The Non-dominated Sorting Genetic Algorithm II (NSGA-II) was enhanced with dual-mode initialization, key-gene-preserving crossover, and peak-valley-guided mutation strategies.

Main Results:

• The proposed method doubled green electricity consumption under stable production conditions.
• Grid electricity consumption per unit of liquid produced was reduced by 41.67%.
• Computational efficiency improved by two to three orders of magnitude, with a 26.69% enhancement in solution accuracy.

Conclusions:

• The developed optimization approach effectively addresses the mismatch between intermittent renewable energy sources and oilfield energy demands.
• The enhanced NSGA-II algorithm provides a practical and efficient solution for maximizing green energy utilization and economic benefits in oilfield operations.
• The method demonstrates strong applicability for achieving sustainable energy management in the petroleum industry under the
• dual carbon
• targets.