Optimal Modeling of PV-Grid Collaborative Water Injection Systems

To address the issues of high energy consumption, high costs of traditional grid power supply, and significant carbon emissions in oilfield water injection systems, this study proposes an optimized model based on mixed-integer programming (MIP) for a photovoltaic (PV)-grid collaborative water injection system. With the goal of maximizing green power utilization, the model comprehensively considers PV generation volatility, dynamic water injection demand variations, and wellhead pressure safety constraints. It employs mixed-integer programming and dynamic optimization algorithms to establish an ultra-short-cycle water injection optimization framework that integrates “PV priority, off-peak power supplementation, and dynamic pressure regulation,” enabling low-carbon and efficient system operation. Results demonstrate that this optimization model achieves a PV utilization rate of 86.5%, reducing grid power consumption by over 45% compared to conventional methods. The proposed approach exhibits strong economic viability and practicality, providing both theoretical foundations and technical support for green and low-carbon oilfield production.