Flexibility quantification of desalination plants for demand response: An adaptive robust optimization methodology

The rapid and continuous development of renewable energy (RE) sources highlights the need for demand response (DR). DR involves consumers adjusting their electricity use in response to price signals or incentives, helping balance power supply and demand. Desalination, a critical process for addressing water scarcity, often demands high energy consumption but offers significant power regulation flexibility, making it an ideal resource for participating in DR. However, the flexibility of desalination plants in DR programs is not adequately modeled or quantified. This study introduces a new perspective on desalination plant flexibility, defined by the maximum power exchange intervals over time with the power distribution system (PDS). We categorize this flexibility into technical and economic intervals. The technical interval emphasizes the feasibility of the power intervals, while the economic interval requires both feasibility and financial viability. The adaptive robust optimization (ARO) methodology is introduced to quantify these intervals. Two ARO models incorporating detailed desalination processes and their two-stage algorithms based on the nested column and constraint generation (nested-C&CG) are developed to address binary decision variables involved in the two intervals. These intervals are then incorporated into an incentive-based DR scheme to improve plant-PDS interaction. Numerical results on a desalination plant using reverse osmosis (RO) technology indicate that with the proposed method, DR execution deviations were eliminated, reducing from 122 kWh to zero. Additionally, a substantial cost reduction of over 20% was realized for the plant. This study offers practical solutions to guide the PDS in issuing reasonable DR requirements and to make desalination plants more economical, enhancing their willingness to engage in DR. This contributes to a more sustainable power and water future.